From 6a872682b2b2d4246e5dbe74c7768f7bc0dc445e Mon Sep 17 00:00:00 2001 From: DouSam <28208639+DouSam@users.noreply.github.com> Date: Thu, 12 Mar 2026 05:16:45 +0000 Subject: [PATCH] Update translations from SlicerLanguageTranslations Processed tutorials: STC-GEN-101_WelcomeTutorial, STC-GEN-102_FourMinuteTutorial, STC-SEG-103_AIBasedSegmentationIn3DSlicer, STC-VIS-101_VisualizationTutorial Files: STC-GEN-101_en-US.ts,STC-GEN-101_es.ts,STC-GEN-101_fr.ts,STC-GEN-101_pt-BR.ts,STC-GEN-101_pt_PT.ts,STC-GEN-102_en-US.ts,STC-GEN-102_es.ts,STC-GEN-102_fr.ts,STC-GEN-102_pt-BR.ts,STC-GEN-102_pt_PT.ts,STC-SEG-103_ar-SA.ts,STC-SEG-103_en-US.ts,STC-SEG-103_es.ts,STC-SEG-103_fr.ts,STC-SEG-103_pt-BR.ts,STC-SEG-103_pt_PT.ts,STC-SEG-103_ta.ts,STC-SEG-103_th.ts,STC-SEG-103_uk.ts,STC-VIS-101_ar_SA.ts,STC-VIS-101_en-US.ts,STC-VIS-101_es.ts,STC-VIS-101_fr.ts,STC-VIS-101_pt-BR.ts,STC-VIS-101_pt_PT.ts --- .../Translations/text_dict_en-US.json | 52 ++++++++ .../Translations/text_dict_es.json | 65 ++++++++++ .../Translations/text_dict_fr.json | 65 ++++++++++ .../Translations/text_dict_pt-BR.json | 52 ++++++++ .../Translations/text_dict_pt_PT.json | 52 ++++++++ .../Translations/text_dict_en-US.json | 39 ++++++ .../Translations/text_dict_es.json | 51 ++++++++ .../Translations/text_dict_fr.json | 52 ++++++++ .../Translations/text_dict_pt-BR.json | 39 ++++++ .../Translations/text_dict_pt_PT.json | 39 ++++++ .../Translations/text_dict_ar-SA.json | 49 +++++++ .../Translations/text_dict_en-US.json | 49 +++++++ .../Translations/text_dict_es.json | 49 +++++++ .../Translations/text_dict_fr.json | 49 +++++++ .../Translations/text_dict_pt-BR.json | 49 +++++++ .../Translations/text_dict_pt_PT.json | 49 +++++++ .../Translations/text_dict_ta.json | 49 +++++++ .../Translations/text_dict_th.json | 49 +++++++ .../Translations/text_dict_uk.json | 49 +++++++ .../Translations/text_dict_ar_SA.json | 99 ++++++++++++++ .../Translations/text_dict_en-US.json | 99 ++++++++++++++ .../Translations/text_dict_es.json | 121 ++++++++++++++++++ .../Translations/text_dict_fr.json | 117 +++++++++++++++++ .../Translations/text_dict_pt-BR.json | 99 ++++++++++++++ .../Translations/text_dict_pt_PT.json | 99 ++++++++++++++ 25 files changed, 1581 insertions(+) create mode 100644 Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en-US.json create mode 100644 Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json create mode 100644 Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json create mode 100644 Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json create mode 100644 Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt_PT.json create mode 100644 Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en-US.json create mode 100644 Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json create mode 100644 Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json create mode 100644 Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json create mode 100644 Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt_PT.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en-US.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt_PT.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json create mode 100644 Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json create mode 100644 Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_ar_SA.json create mode 100644 Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en-US.json create mode 100644 Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json create mode 100644 Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json create mode 100644 Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json create mode 100644 Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt_PT.json diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en-US.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en-US.json new file mode 100644 index 00000000..aed6f1de --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en-US.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Slicer Welcome", + "1_TextBox_0": "Slicer Welcome", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "2_Goal_title": "Goal", + "6_WelcometoSlicer_title": "Welcome to Slicer", + "7_SlicerUserInterface_title": "Slicer User Interface", + "7_ArrowText_0": "Toolbar", + "7_TextBox_1": "3D viewer", + "7_ArrowText_6": "2D anatomical viewers", + "7_TextBox_5": "Data probe", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.", + "3_TextBox_0": "Slicer5 Basics", + "4_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.", + "5_TextBox_0": "Supported Platforms", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module", + "8_WelcomeModule_title": "Welcome Module", + "9_WelcomeModule_title": "Welcome Module", + "13_WelcomeModule_title": "Welcome Module", + "8_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.", + "9_TextBox_0": "The Welcome module panel contains shortcuts for loading different types of data. A series of sample data are also available.\n\nClick on Download Sample Data to access the Sample Data Module", + "10_SampleData_title": "Sample Data", + "11_SampleData_title": "Sample Data", + "12_SampleData_title": "Sample Data", + "10_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.", + "11_TextBox_0": "Brain MR", + "11_TextBox_1": "Chest CT", + "11_TextBox_2": "Cardiac CT", + "11_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset", + "11_TextBox_4": "Brain MRI (tumor patient)", + "12_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.", + "13_TextBox_0": "The MR scan of the brain appears\nin the 2D viewers.", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Going Further", + "18_TextBox_0": "Going Further", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)", + "14_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "15_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "16_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "19_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json new file mode 100644 index 00000000..e98f1583 --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json @@ -0,0 +1,65 @@ +{ + "0_TextBox_0": "Bienvenido a Slicer", + "1_TextBox_0": "Bienvenido a Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "28/08/2024", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "2_Goal_title": "Meta", + "1_Goal_body": "Este tutorial es una breve introducción al módulo de bienvenida del software de código abierto Slicer. ", + "2_3DSlicerversion48_title": "3D Slicer versión 4.8", + "6_WelcometoSlicer_title": "Bienvenido a Slicer", + "3_TextBox_0": "Slicer5 Basics", + "7_SlicerUserInterface_title": "Interfaz de Usuario Slicer", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.", + "7_ArrowText_0": "B. Herramientas", + "7_TextBox_1": "Visor 3D", + "7_ArrowText_6": "Visores 2D anatómicos", + "7_TextBox_5": "Prueba de datos", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.", + "4_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ", + "5_TextBox_0": "La\tDocumentación y\tTutoriales\t\nlengüeta\tcontiene\tenlaces\tpara\tel\tentrenamiento\t\ncompendio\ty\tdocumentación páginas\tde\t3D\tSlicer\tversión\t4.8.\t", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module", + "8_WelcomeModule_title": "Módulo Bienvenido", + "9_WelcomeModule_title": "Módulo Bienvenido", + "13_WelcomeModule_title": "Módulo Bienvenido", + "8_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.", + "9_TextBox_0": "La resonancia magnética del cerebro aparece\nen los visores 2D.", + "10_SampleData_title": "Sample Data", + "11_SampleData_title": "Sample Data", + "12_SampleData_title": "Sample Data", + "10_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.", + "11_TextBox_0": "Pulse en el icono de enlace para vincular los tres\nvisores 2D y en el icono del ojo que se encuentra\njunto a él para mostrar los cortes en el visor 3D. );", + "11_TextBox_1": "Chest CT", + "11_TextBox_2": "Cardiac CT", + "11_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset", + "11_TextBox_4": "Brain MRI (tumor patient)", + "12_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.", + "13_TextBox_0": "Para obtener más información sobre Slicer y\nsus diferentes funcionalidades, visite el compendio de Slicer4.8", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Going Further", + "18_TextBox_0": "Going Further", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)", + "6_TextBox_0": "El panel del módulo de bienvenida\ncontiene accesos directos para\ncargar diferentes tipos de datos.\nTambién hay disponibles datos de muestra.\n\nPulse sobre \"Descargar datos de muestra\" para\nacceder al módulo de datos de muestra.\t", + "7_Sampledata_title": "Datos de muestra", + "8_Sampledata_title": "Datos de muestra", + "7_TextBox_0": "El módulo Datos de muestra contiene\nenlaces a diferentes conjuntos de datos\nde muestra que pueden descargarse\nen Slicer.\t", + "8_ArrowText_0": "Pulse\ten\tMRHead para\tdescargar\tel\t\ndataset\ten\tSlicer.\t", + "14_MRBrainSampleDataset_title": "Dataset de Muestra del Cerebro MR", + "15_MRBrainSampleDataset_title": "Dataset de Muestra del Cerebro MR", + "16_MRBrainSampleDataset_title": "Dataset de Muestra del Cerebro MR", + "10_ArrowText_0": "Posicionar el ratón en el pin pequeño\t\nicono\ten la cima izquierda de esquina del visor rojo para exhibir el menú del visor", + "12_MRBrainSampleDataset_title": "Pulse en el icono de enlace para vincular los tres\nvisores 2D y en el icono del ojo que se encuentra\njunto a él para mostrar los cortes en el visor 3D. );", + "12_TextBox_0": "Los cortes axial, coronal y sagital\naparecen en el visor 3D. Vuelva al\nmódulo de bienvenida usando la\nflecha verde de la barra de herramientas );", + "13_GoingFurther_title": "Los cortes axial, coronal y sagital\naparecen en el visor 3D. Vuelva al\nmódulo de bienvenida usando la\nflecha verde de la barra de herramientas );", + "19_TextBox_0": "Agradecimientos", + "14_TextBox_1": "Alianza Nacional para Cómputo de Imagen Médcia\nNIH U54EB005148\n\nCentro de Análisis Neuroimagen\nNIH P41EB015902" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json new file mode 100644 index 00000000..3268c1c5 --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json @@ -0,0 +1,65 @@ +{ + "0_TextBox_0": "Bienvenue dans Slicer", + "1_TextBox_0": "Bienvenue dans Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "28/08/2024", + "0_TextBox_3": "Professeur adjoint en radiologie\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "2_Goal_title": "Objectif", + "1_Goal_body": "Ce tutoriel est une brève introduction au module Welcome du logiciel open-source Slicer. ", + "2_3DSlicerversion48_title": "3D Slicer version 4.8", + "6_WelcometoSlicer_title": "Bienvenue dans Slicer", + "3_TextBox_0": "Notions de base Slicer5", + "7_SlicerUserInterface_title": "Interface utilisateur de Slicer", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 comprend plus de 100 modules et plus de 190 extensions pour la segmentation d’images, le recalage et la visualisation 3D de données d’imagerie médicale.", + "7_ArrowText_0": "Barre d’outils", + "7_TextBox_1": "Visionneuse 3D", + "7_ArrowText_6": "Visionneuses anatomiques 2D", + "7_TextBox_5": "Sonde de données", + "1_TextBox_3": "Professeur adjoint en radiologie\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "Ce tutoriel est une courte introduction au module Bienvenue du logiciel open-source Slicer.", + "4_TextBox_0": "Notions de base Slicer5", + "3_TextBox_1": "*Slicer est un logiciel open-source dédié à la segmentation, au recalage et à la visualisation de données d’imagerie médicale.\n*La plateforme est développée grâce à un effort multi-institutionnel impliquant plusieurs grands consortiums financés par le NIH.\n*Slicer est destiné uniquement à la recherche médicale et n’est pas approuvé par la FDA. ", + "5_TextBox_0": "L’onglet Documentation & Tutoriels \ncontient des liens vers \nle compendium de formation et les pages de documentation de la version 4.8 de 3D Slicer.\t", + "5_TextBox_1": "*Slicer est un logiciel multiplateforme développé et maintenu sur Mac OS X, Linux et Windows.\n\n*Slicer nécessite au minimum 2 Go de mémoire vive (RAM) ainsi qu’un accélérateur graphique dédié disposant de 64 Mo de mémoire vidéo embarquée.* ", + "6_TextBox_1": "Chaque module de Slicer comprend une série d’onglets qui donnent accès à différentes fonctionnalités.\n\nCliquez sur le symbole en forme de flèche pour afficher le contenu de chaque onglet. ", + "7_TextBox_3": "Panneau d’interface utilisateur (UI) du module Bienvenue de Slicer", + "8_WelcomeModule_title": "Module Bienvenue", + "9_WelcomeModule_title": "Module Bienvenue", + "13_WelcomeModule_title": "Module Bienvenue", + "8_TextBox_1": "L’onglet Documentation & Tutorials contient des liens vers le compendium de formation et les pages de documentation de 3D Slicer.", + "9_TextBox_0": "Le scan IRM du cerveau apparaît dans les visionneuses 2D.", + "10_SampleData_title": "Exemple de données", + "11_SampleData_title": "Exemple de données", + "12_SampleData_title": "Exemple de données", + "10_TextBox_1": "Le module Sample Data contient des liens vers différents jeux de données exemples pouvant être téléchargés dans Slicer.", + "11_TextBox_0": "Cliquez sur l’icône de lien pour relier les trois visionneuses 2D, puis sur l’icône en forme d’œil à côté pour afficher les coupes dans la visionneuse 3D\t) ;", + "11_TextBox_1": "Scanner thoracique", + "11_TextBox_2": "Scanner cardiaque", + "11_TextBox_3": "Jeu de données d’imagerie par tenseur de diffusion (DTI)", + "11_TextBox_4": "IRM cérébrale (patient atteint d’une tumeur)", + "12_ArrowText_0": "Cliquez sur MRHead pour télécharger le jeu de données dans Slicer.", + "13_TextBox_0": "Pour en savoir plus sur Slicer et ses différentes fonctionnalités, consultez le compendium de Slicer 4.8.", + "14_TextBox_0": "Placez la souris sur la petite icône en forme d’épingle dans le coin supérieur gauche du visionneur rouge pour afficher le menu du visionneur", + "15_TextBox_1": "Cliquez sur l’icône de lien pour lier les trois visionneurs 2D, puis sur l’icône œil à côté pour afficher les coupes dans le visionneur 3D.", + "16_TextBox_0": "Les coupes axiales, coronales et sagittales apparaissent dans le visualiseur 3D.\nRevenez au module Welcome en utilisant la flèche verte dans la barre d’outils.", + "17_GoingFurther_title": "Pour aller plus loin", + "18_TextBox_0": "Pour aller plus loin", + "17_TextBox_0": "Pour en savoir plus sur Slicer et ses différentes fonctionnalités, consultez le Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)", + "6_TextBox_0": "Le panneau du module Welcome contient des raccourcis pour charger différents types de données. Une série de données d’exemple est également disponible.\n\nCliquez sur Download Sample Data pour accéder au module Sample Data.\t", + "7_Sampledata_title": "Données d’exemple", + "8_Sampledata_title": "Données d’exemple", + "7_TextBox_0": "Le module Sample Data contient des liens vers différents ensembles de données d’exemple pouvant être téléchargés dans Slicer\t", + "8_ArrowText_0": "Cliquez sur MRHead pour télécharger l’ensemble de données dans Slicer\t", + "14_MRBrainSampleDataset_title": "Jeu de données d’exemple IRM du cerveau", + "15_MRBrainSampleDataset_title": "Jeu de données d’exemple IRM du cerveau", + "16_MRBrainSampleDataset_title": "Jeu de données d’exemple IRM du cerveau", + "10_ArrowText_0": "Placez la souris sur la petite icône en forme d’épingle dans le coin supérieur gauche de la visionneuse rouge pour afficher le menu de la visionneuse", + "12_MRBrainSampleDataset_title": "Cliquez sur l’icône de lien pour relier les trois visionneuses 2D, puis sur l’icône en forme d’œil à côté pour afficher les coupes dans la visionneuse 3D\t) ;", + "12_TextBox_0": "Les coupes axiale, coronale et sagittale apparaissent dans la visionneuse 3D.\nRetournez au module Welcome en utilisant la flèche verte dans la barre d’outils\t) ;", + "13_GoingFurther_title": "Les coupes axiale, coronale et sagittale apparaissent dans la visionneuse 3D.\nRetournez au module Welcome en utilisant la flèche verte dans la barre d’outils\t) ;", + "19_TextBox_0": "Remerciements", + "14_TextBox_1": "Alliance nationale pour l’informatique de l’imagerie médicale\nNIH U54EB005148\n\nCentre d’analyse neuroimagerie\nNIH P41EB015902" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..fe8c96fb --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Bem-vindo ao Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Professor Assistente de Radiologia\nHospital Brigham and Women's\nFaculdade de Medicina de Harvard\n", + "1_TextBox_0": "Slicer Welcome", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_3": "Professor Assistente de Radiologia\nHospital Brigham and Women's\nFaculdade de Medicina de Harvard\n", + "2_Goal_title": "Objetivo", + "2_Goal_body": "Este tutorial é uma breve introdução ao módulo de boas-vindas do software de código aberto Slicer.", + "3_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer é um software de código aberto para segmentação, registro e visualização de dados de imagens médicas. \n*A plataforma foi desenvolvida por meio de um esforço multi-institucional, com vários consórcios de grande escala financiados pelo NIH.\n*O Slicer destina-se exclusivamente à pesquisa médica e não possui aprovação da FDA. ", + "4_TextBox_0": "Básico do Slicer5", + "4_TextBox_1": "O 3D Slicer 5 versão 5.10.0 inclui mais de 100 módulos e mais de 190 extensões para segmentação de imagens, registro e visualização 3D de dados de imagens médicas.", + "5_TextBox_0": "Plataformas Suportadas", + "5_TextBox_1": "*O Slicer é um software multiplataforma desenvolvido e mantido para Mac OSX, Linux e Windows.\n*O Slicer requer, no mínimo, 2 GB de RAM e uma placa de vídeo dedicada com 64 MB de memória gráfica integrada. ", + "6_WelcometoSlicer_title": "Bem-vindo ao Slicer", + "6_TextBox_1": "Cada módulo do Slicer inclui uma série de abas que dão acesso a diferentes funcionalidades. Clique no símbolo de seta para exibir o conteúdo de cada aba. ", + "7_SlicerUserInterface_title": "Interface do Usuário no Slicer", + "7_ArrowText_0": "Barra de ferramentas", + "7_TextBox_1": "Visualizador 3D", + "7_TextBox_3": "Painel da interface do usuário do módulo de boas-vindas do Slicer", + "7_TextBox_5": "Sonda de dados", + "7_ArrowText_6": "Visualizadores anatômicos 2D", + "8_WelcomeModule_title": "Welcome Module", + "8_TextBox_1": "A aba Documentação e Tutoriais contém links para o compêndio de treinamento e páginas de documentação do 3D Slicer.", + "9_WelcomeModule_title": "Welcome Module", + "9_TextBox_0": "O painel do módulo de boas-vindas contém atalhos para carregar diferentes tipos de dados.\nUma série de dados de exemplo também está disponível. \nClique em \"Baixar dados de exemplo\" para acessar o módulo de dados de exemplo.", + "10_SampleData_title": "Sample Data", + "10_TextBox_1": "O módulo Dados de Exemplo contém links para diferentes conjuntos de dados de exemplos que podem ser baixados no Slicer.", + "11_SampleData_title": "Sample Data", + "11_TextBox_0": "RM Cerebral", + "11_TextBox_1": "TC Peito", + "11_TextBox_2": "TC Cardíaco", + "11_TextBox_3": "Conjunto de dados de imagem por tensor de difusão (DTI)", + "11_TextBox_4": "RM Cerebral (paciente com tumor)", + "12_SampleData_title": "Dados de Exemplo", + "12_ArrowText_0": "Clique em MRHead para baixar o conjunto\nde dados no Slicer.", + "13_WelcomeModule_title": "Modulo de Boas-vindas", + "13_TextBox_0": "A imagem de ressonância magnética\ndo cérebro aparece nos visualizadores 2D.", + "14_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "14_TextBox_0": "Posicione o cursor do mouse sobre o pequeno ícone de alfinete no canto superior esquerdo do visualizador vermelho para exibir o menu do visualizador.", + "15_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "15_TextBox_1": "Clique no ícone de link para conectar os três visualizadores 2D e no ícone de olho ao lado\npara exibir as fatias no visualizador 3D.", + "16_MRBrainSampleDataset_title": "RM Cerebral conjunto de dados de exemplo", + "16_TextBox_0": "As imagens axiais, coronais e sagitais são exibidas no visualizador 3D. \nRetorne ao módulo de boas-vindas usando a seta verde na barra de ferramentas.", + "17_GoingFurther_title": "Going Further", + "17_TextBox_0": "Para saber mais sobre o Slicer e suas diferentes funcionalidades, visite o Compêndio do Slicer.", + "18_TextBox_0": "Indo Além", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_0": "Agradecimentos", + "19_TextBox_1": "Aliança Nacional para Computação de\nImagens Médicas\nNIH U54EB005149\n\nCentro de Análise de Neuroimagens\nNIH P41EB015902 \n\nIniciativa Chan Zuckerberg (CZI)" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt_PT.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt_PT.json new file mode 100644 index 00000000..aaf48875 --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt_PT.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Bem-vindo ao Slicer", + "1_TextBox_0": "Bem-vindo ao Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "2_Goal_title": "Objetivo", + "6_WelcometoSlicer_title": "Bem-vindo ao Slicer", + "7_SlicerUserInterface_title": "Interface do Utilizador no Slicer", + "7_ArrowText_0": "Barra de ferramentas", + "7_TextBox_1": "Visualizador 3D", + "7_ArrowText_6": "Visualizadores anatômicos 2D", + "7_TextBox_5": "Sonda de dados", + "0_TextBox_3": "Professor Assistente de Radiologia\nHospital Brigham and Women's\nFaculdade de Medicina de Harvard\n", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "Este tutorial é uma breve introdução ao módulo de boas-vindas do software de código aberto Slicer.", + "3_TextBox_0": "Básico do Slicer5", + "4_TextBox_0": "Básico do Slicer5", + "3_TextBox_1": "*Slicer é um software de código aberto para segmentação, registo e visualização de dados de imagens médicas. \n*A plataforma foi desenvolvida por meio de um esforço multi-institucional, com vários consórcios de grande escala financiados pelo NIH.\n*O Slicer destina-se exclusivamente à pesquisa médica e não possui aprovação da FDA. ", + "4_TextBox_1": "O 3D Slicer 5 versão 5.10.0 inclui mais que 100 módulos e mais que 190 extensões para segmentação de imagens, registo e visualização 3D de dados de imagens médicas.", + "5_TextBox_0": "Plataformas Suportadas", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_TextBox_3": "Painel da interface do utilizador do módulo de boas-vindas do Slicer", + "8_WelcomeModule_title": "Modulo de Boas-vindas", + "9_WelcomeModule_title": "Modulo de Boas-vindas", + "13_WelcomeModule_title": "Modulo de Boas-vindas", + "8_TextBox_1": "A guia Documentação e Tutoriais contém ligações para o compêndio de treino e páginas de documentação do 3D Slicer.", + "9_TextBox_0": "The Welcome module panel contains shortcuts for loading different types of data. A series of sample data are also available.\n\nClick on Download Sample Data to access the Sample Data Module", + "10_SampleData_title": "Dados de Exemplo", + "11_SampleData_title": "Dados de Exemplo", + "12_SampleData_title": "Dados de Exemplo", + "10_TextBox_1": "O módulo Dados de Exemplo contém ligações para conjuntos de dados de exemplos diferentes que podem ser descarregados no Slicer.", + "11_TextBox_0": "RM Cerebral", + "11_TextBox_1": "TC Peito", + "11_TextBox_2": "TC Cardíaco", + "11_TextBox_3": "Conjunto de dados de imagem por tensor de difusão (DTI)", + "11_TextBox_4": "RM Cerebral (utente com tumor)", + "12_ArrowText_0": "Clique em MRHead para descarregar o conjunto\nde dados no Slicer.", + "13_TextBox_0": "A imagem de ressonância magnética\ndo cérebro aparece nos visualizadores 2D.", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Indo Além", + "18_TextBox_0": "Indo Além", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "Aliança Nacional para Computação de\nImagens Médicas\nNIH U54EB005149\n\nCentro de Análise de Neuroimagens\nNIH P41EB015902 \n\nIniciativa Chan Zuckerberg (CZI)", + "14_MRBrainSampleDataset_title": "RM Cerebral conjunto de dados de exemplo", + "15_MRBrainSampleDataset_title": "RM Cerebral conjunto de dados de exemplo", + "16_MRBrainSampleDataset_title": "RM Cerebral conjunto de dados de exemplo", + "19_TextBox_0": "Agradecimentos" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en-US.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en-US.json new file mode 100644 index 00000000..42c07552 --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en-US.json @@ -0,0 +1,39 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Slicer4 minute tutorial", + "16_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ", + "2_TextBox_0": "Slicer5 software & dataset", + "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "3D Slicer Scene", + "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.", + "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset", + "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer", + "6_Slicer4minuteScene_title": "Slicer4minute Scene", + "6_TextBox_1": "Slicer displays the elements of the slicer4minute scene. The scene contains and MRI scan and 3D surface models of the brain.", + "7_TextBox_0": "Select the module Models", + "8_3Dvisualization_title": "3D visualization", + "8_TextBox_0": "Click on the pin icon on the top left corner of the red slice to display the slice viewer menu.\nClick on the eye icon to display the axial slice in the 3D viewer", + "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer", + "10_TextBox_0": "Select the Skin model and lower its opacity using the Opacity slider in the 3D Display tab", + "10_TextBox_1": "The skull_bone.vtk model appears through the skin.", + "11_TextBox_0": "Position the mouse in the 3D viewer, click on the left-mouse button to drag and rotate the model. \nClick on the right-mouse button to zoom in and out", + "12_AnatomicalViews_title": "Anatomical Views", + "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer", + "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model", + "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer", + "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'", + "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n", + "7_3DVisualization_title": "3D Visualization", + "9_3DVisualization_title": "3D Visualization", + "10_3DVisualization_title": "3D Visualization", + "11_3DVisualization_title": "3D Visualization", + "13_3DVisualization_title": "3D Visualization", + "14_3DVisualization_title": "3D Visualization", + "15_3DVisualization_title": "3D Visualization", + "17_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json new file mode 100644 index 00000000..e2a70141 --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json @@ -0,0 +1,51 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "Profesor\tAdjunto\tde\tRadiología\nHospital\tBrigham\tand\tWomen's\nFacultad\tde\tMedicina\tde\tHarvard\t", + "1_Slicer4minutetutorial_title": "Tutorial de Slicer4 minutos\t);", + "1_Slicer4minutetutorial_body": "Tutorial de Slicer4 minutos\t);", + "2_3DSlicerversion48_title": "3D Slicer versión 4.8\t", + "3_3DSlicerversion48_title": "3D Slicer versión 4.8", + "3_TextBox_0": "Arrastre y suelte el archivo\nslicer4minute.mrb para\ncargar la escena en Slicer", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Slicer4 minute tutorial", + "16_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ", + "2_TextBox_0": "Slicer5 software & dataset", + "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "Slicer muestra los elementos\nde la escena de slicer4minute.\nLa escena contiene una resonancia\nmagnética y modelos de superficie\n3D del cerebro.\t", + "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.", + "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset", + "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer", + "6_Slicer4minuteScene_title": "Escena Slicer4minute", + "6_TextBox_1": "Pulse en el icono del alfiler en la esquina superior izquierda del corte rojo\npara abrir el menú del visor de cortes.\nPulse en el icono del ojo para ver el corte axial en el visor 3D", + "7_TextBox_0": "Select the module Models", + "8_3Dvisualization_title": "3D visualization", + "8_TextBox_0": "Click on the pin icon on the top left corner of the red slice to display the slice viewer menu.\nClick on the eye icon to display the axial slice in the 3D viewer", + "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer", + "10_TextBox_0": "Pulse en los iconos de alfiler en\nla esquina superior izquierda del\nvisor rojo y verde para abrir el\nmenú del visor de cortes.\n\nPulse en el icono del ojo para mostrar los\ncortes axial y coronal en el visor 3D", + "10_TextBox_1": "The skull_bone.vtk model appears through the skin.", + "11_TextBox_0": "Apaga\tla\tvisibilidad\tdel\tcráneo\npara\texhibir\tel\tcerebro\ten\nmodo\tmapa\tblanco", + "12_AnatomicalViews_title": "Anatomical Views", + "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer", + "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model", + "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer", + "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'", + "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n", + "7_3DVisualization_title": "Visualización 3D", + "9_3DVisualization_title": "Visualización 3D", + "10_3DVisualization_title": "Visualización 3D", + "11_3DVisualization_title": "Visualización 3D", + "13_3DVisualization_title": "Visualización 3D", + "14_3DVisualization_title": "Visualización 3D", + "15_3DVisualization_title": "Visualización 3D", + "5_TextBox_0": "Selecciona el módulo Modelos\t", + "6_ArrowText_0": "Conmutar la visibilidad de los cortes en la vista 3D", + "9_TextBox_0": "Coloque el ratón en el visor 3D y pulse con el botón izquierdo para arrastrar y rotar el modelo.\nPulse con el botón derecho para acercar o alejar la imagen", + "10_Anatomicalviews_title": "Vistas anatómicas", + "12_TextBox_3": "Seleccione\tel\tmodelo\themispheric_white\tmatter.vtk\n\nMarque\tla\topción\tRecorte\ten\tla\tpestaña\tVisualización\t3D.\n\nEn\tla\tpestaña\tPlanos\tde\tRecorte,\tseleccione\tla\topción\t\"Recorte\tde\tCorte\tVerde\"\ty\tmarque\t\"Negativo\"", + "17_TextBox_0": "Agradecimientos", + "13_TextBox_1": "Alianza Nacional para la Computación de Imágenes Médicas\nNIH U54EB005149\n\nCentro de Análisis de Neuroimágenes\nNIH P41EB015902\n\nIniciativa Chan Zuckerberg\nSubvención de Código Abierto Esencial para la Ciencia n.° 2022-252572 (5022)" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json new file mode 100644 index 00000000..5411777f --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "Professeure adjointe de radiologie\nBrigham and Women’s Hospital\nHarvard Medical School\t", + "1_Slicer4minutetutorial_title": "Tutoriel Slicer4 minute \t);", + "1_Slicer4minutetutorial_body": "Tutoriel Slicer4 minute \t);", + "2_3DSlicerversion48_title": "3D Slicer version 4.8\t", + "3_3DSlicerversion48_title": "3D Slicer version 4.8", + "3_TextBox_0": "Glissez-déposez le fichier slicer4minute.mrb pour charger la scène dans Slicer.", + "0_TextBox_3": "Professeur adjoint en radiologie\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Tutoriel Slicer4 minute", + "16_TextBox_0": "Tutoriel Slicer4 minute", + "1_TextBox_1": "Ce tutoriel est une introduction de 4 minutes aux capacités de visualisation 3D du logiciel Slicer5 pour l’analyse d’images médicales. ", + "2_TextBox_0": "Logiciel et jeu de données Slicer5", + "2_TextBox_1": "*Téléchargez le logiciel Slicer5 disponible à l’adresse http://download.slicer.org\n\n*Téléchargez le jeu de données Slicer4minute disponible à l’adresse \nhttps://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "Slicer affiche les éléments de la scène slicer4minute.\nLa scène contient une IRM ainsi que des modèles de surface 3D du cerveau.\t", + "4_TextBox_1": "*Une scène Slicer est un fichier MRML (Medical Reality Modeling Language) qui contient une liste d’éléments chargés dans Slicer (volumes, modèles, repères, transformations, etc.)\n*Dans l’exemple suivant, nous utilisons une scène « Slicer4minute.mrml » composée d’une IRM et de modèles 3D de la tête.\n*Le fichier de scène et les jeux de données ont été enregistrés sous forme de fichier MRB (Medical Reality Bundle).\n*Le format de fichier MRB est le format d’archive de Slicer.", + "5_LoadingtheSlicer4minutedataset_title": "Chargement du jeu de données Slicer4minute", + "5_TextBox_1": "Glissez et déposez le fichier slicer4minute.mrb pour charger la scène dans Slicer", + "6_Slicer4minuteScene_title": "Scène Slicer4minute", + "6_TextBox_1": "Cliquez sur l’icône en forme d’épingle dans le coin supérieur gauche de la coupe rouge pour afficher le menu de la visionneuse de coupes\nCliquez sur l’icône en forme d’œil pour afficher la coupe axiale dans la Visionneuse 3D", + "7_TextBox_0": "Utilisez le curseur de la visionneuse rouge pour parcourir les coupes axiales de l’IRM\nSlicer affiche simultanément la coupe axiale dans la visionneuse 3D\t", + "8_3Dvisualization_title": "Visualisation 3D", + "8_TextBox_0": "Sélectionnez le modèle Skin et réduisez son opacité en utilisant le curseur Opacity dans l’onglet 3D Display\t", + "9_TextBox_1": "Utilisez le curseur du visionneur rouge pour parcourir les coupes axiales de l’IRM.\n\nSlicer affiche simultanément la coupe axiale dans le visionneur 3D", + "10_TextBox_0": "Cliquez sur les icônes en forme d’épingle dans le coin supérieur gauche des visionneuses rouge et verte pour afficher le menu de la visionneuse de coupes\n\nCliquez sur l’icône en forme d’œil pour afficher les coupes axiale et coronale dans la visionneuse 3D", + "10_TextBox_1": "Le modèle skull_bone.vtk apparaît à travers la peau.", + "11_TextBox_0": "Désactivez la visibilité du crâne pour afficher le cerveau en mode maPer blanche", + "12_AnatomicalViews_title": "Vues anatomiques", + "12_TextBox_0": "Cliquez sur les icônes en forme d’épingle dans le coin supérieur gauche des visualiseurs rouge et vert pour afficher le menu du visualiseur de coupes.\n\nCliquez sur l’icône œil pour afficher les coupes axiale et coronale dans le visionneur 3D", + "13_TextBox_0": "Désactivez la visibilité du crâne pour afficher le modèle de la matière blanche du cerveau", + "14_TextBox_0": "La surface de la matière blanche, ainsi que les nerfs optiques gauche et droit, apparaissent dans le visionneur", + "15_TextBox_0": "Sélectionnez le modèle hemispheric_white_matter.vtk\n\nCochez Découpage dans l’onglet 3D Display\n\nDans l’onglet Plan de découpage, sélectionnez l’option 'Découpage selon la tranche verte' et cochez 'Negatif'", + "16_TextBox_1": "*Ce tutoriel était une courte introduction à la visualisation 3D interactive des données IRM et des modèles 3D dans Slicer.\n\n*Le compendium de formation Slicer5 contient une série de tutoriels et de jeux de données pré-calculés pour apprendre à utiliser le logiciel.", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n", + "7_3DVisualization_title": "Visualisation 3D", + "9_3DVisualization_title": "Visualisation 3D", + "10_3DVisualization_title": "Visualisation 3D", + "11_3DVisualization_title": "Visualisation 3D", + "13_3DVisualization_title": "Visualisation 3D", + "14_3DVisualization_title": "Visualisation 3D", + "15_3DVisualization_title": "Visualisation 3D", + "5_TextBox_0": "Sélectionnez le module Models\t", + "6_ArrowText_0": "Basculer la visibilité des coupes dans la vue 3D", + "8_TextBox_1": "Le modèle skull_bone.vtk apparaît à travers la peau\t", + "9_TextBox_0": "Placez la souris dans la visionneuse 3D, cliquez sur le bouton gauche de la souris pour déplacer et faire pivoter le modèle\nCliquez sur le bouton droit de la souris pour zoomer avant et arrière", + "10_Anatomicalviews_title": "Vues anatomiques", + "12_TextBox_3": "Sélectionnez le modèle hemispheric_white matter.vtk\n\nCochez Clipping dans l’onglet 3D Display\n\nDans l’onglet Clipping Planes, sélectionnez l’option Green Slice Clipping et cochez Negative", + "17_TextBox_0": "Remerciements", + "13_TextBox_1": "National Alliance for Medical Imaging Computing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative\nEssential Open Source for Science Grant #2022-252572 (5022)" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..40db33b1 --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json @@ -0,0 +1,39 @@ +{ + "0_TextBox_0": "Slicer em 4 Minutos\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Professor Assistente de Radiologia\nHospital Brigham and Women's\nFaculdade de Medicina de Harvard", + "1_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "Este tutorial é uma introdução de 4 minutos às capacidades de visualização 3D do software Slicer5 para análise de imagem médica. ", + "2_TextBox_0": "Software Slicer5 e conjunto de dados", + "2_TextBox_1": "*Baixe o software Slicer5 disponível em http://download.slicer.org\n\n*Baixe o conjunto de dados Slicer4minute disponível em https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer versão 5", + "4_TextBox_0": "Cena 3D Slicer", + "4_TextBox_1": "*A cena Slicer é um arquivo MRML (Medical Reality Modeling Language) que contém uma lista de elementos carregados em Slicer (volumes, modelos, fiduciais, transformas, etc.)\n*No exemplo a seguir, usamos uma cena 'Slicer4minute.mrml' composta por uma varredura de RM e modelos 3D da cabeça.\n*O arquivo de cena e conjuntos de dados foram salvos como um arquivo MRB (Medical Reality Bundle).\n*O formato de arquivo MRB é o formato de arquivo Slicer.", + "5_LoadingtheSlicer4minutedataset_title": "Carregando o conjunto de dados Slicer4minute", + "5_TextBox_1": "Arraste e solte o slicer4minute.mrb para carregar a cena no Slicer", + "6_Slicer4minuteScene_title": "Cena Slicer em 4 minutos", + "6_TextBox_1": "Slicer exibe os elementos da cena slicer4minute. A cena contém e ressonância magnética e modelos de superfície 3D do cérebro.", + "7_3DVisualization_title": "3D Visualization", + "7_TextBox_0": "Selecione o módulo Modelos", + "8_3Dvisualization_title": "Visualização 3D", + "8_TextBox_0": "Clique no ícone de alfinete no canto superior esquerdo da fatia vermelha para exibir o menu do visualizador de fatias.\nClique no ícone de olho para exibir a fatia axial no visualizador 3D", + "9_3DVisualization_title": "3D Visualization", + "9_TextBox_1": "Use o controle deslizante do visualizador vermelho para navegar pelos cortes de RM axial.\n\nSlicer exibe simultaneamente a fatia axial no espectador 3D", + "10_3DVisualization_title": "3D Visualization", + "10_TextBox_0": "Selecione o modelo de pele e baixe sua opacidade usando o controle deslizante de opacidade na guia Display 3D", + "10_TextBox_1": "O modelo skull_bone.vtk aparece através da pele.", + "11_3DVisualization_title": "3D Visualization", + "11_TextBox_0": "Posicione o mouse no visualizador 3D, clique no botão esquerdo para arrastar e girar o modelo.\nClique no botão direito do mouse para ampliar e sair", + "12_AnatomicalViews_title": "Visões anatômicas", + "12_TextBox_0": "Clique nos ícones de alfinete no canto superior esquerdo do visor vermelho e verde para exibir o menu do espectador de cortes\n\nClique no ícone do olho para exibir o corte axial e coronal no visualizador 3D", + "13_3DVisualization_title": "3D Visualization", + "13_TextBox_0": "Desligue a visibilidade do crânio para exibir o modelo de matéria branca do cérebro", + "14_3DVisualization_title": "3D Visualization", + "14_TextBox_0": "A superfície da matéria branca, bem como os nervos ópticos esquerdo e direito, aparecem no visualizador", + "15_3DVisualization_title": "Visualização 3D", + "15_TextBox_0": "Selecione o modelo hemispheric_white_matter.vtk\n\nVerificar Clipping na guia Display 3D\n\nNa guia Clipping Planes, selecione a opção 'Green Slice Clipping' e verifique 'Negativo'", + "16_TextBox_0": "Tutorial de 4 minutos do Slicer", + "16_TextBox_1": "*Este tutorial foi uma breve introdução na visualização 3D interativa de dados de RM e modelos 3D em Slicer.\n\n*O Compêndio de treinamento Slicer5 contém uma série de tutoriais e conjuntos de dados pré-computados para aprender a usar o software.", + "17_TextBox_0": "Agradecimentos", + "17_TextBox_1": "Aliança Nacional para Computação de\nImagem Médica\nNIH U54EB005149\n\nCentro de Análise de Neuroimagem\nNIH P41EB015902\n" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt_PT.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt_PT.json new file mode 100644 index 00000000..8660761d --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt_PT.json @@ -0,0 +1,39 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Professor Assistente de Radiologia\nHospital Brigham and Women's\nFaculdade de Medicina de Harvard", + "1_TextBox_0": "Tutorial de 4 minutos do Slicer", + "16_TextBox_0": "Tutorial de 4 minutos do Slicer", + "1_TextBox_1": "Este tutorial é uma introdução de 4 minutos às capacidades de visualização 3D do software Slicer5 para análise de imagem médica. ", + "2_TextBox_0": "Software Slicer5 e conjunto de dados", + "2_TextBox_1": "*Descarregue o software Slicer5 disponível em http://download.slicer.org\n\n*Descarregue o conjunto de dados Slicer4minute disponível em https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer versão 5", + "4_TextBox_0": "Cena 3D Slicer", + "4_TextBox_1": "*A cena Slicer é um ficheiro MRML (Medical Reality Modeling Language) que contém uma lista de elementos carregados em Slicer (volumes, modelos, fiduciais, transformas, etc.)\n*No exemplo a seguir, usamos uma cena 'Slicer4minute.mrml' composta por uma varredura de RM e modelos 3D da cabeça.\n*O ficheiro de cena e conjuntos de dados foram gravados como um ficheiro MRB (Medical Reality Bundle).\n*O formato de ficheiro MRB é o formato de ficheiro Slicer.", + "5_LoadingtheSlicer4minutedataset_title": "A carregar o conjunto de dados Slicer4minute", + "5_TextBox_1": "Arraste e solte o slicer4minute.mrb para carregar a cena no Slicer", + "6_Slicer4minuteScene_title": "Cena Slicer em 4 minutos", + "6_TextBox_1": "Slicer exibe os elementos da cena slicer4minute. A cena contém e ressonância magnética e modelos de superfície 3D do cérebro.", + "7_TextBox_0": "Selecione o módulo Modelos", + "8_3Dvisualization_title": "Visualização 3D", + "8_TextBox_0": "Clique no ícone de alfinete no canto superior esquerdo da fatia vermelha para exibir o menu do visualizador de fatias.\nClique no ícone de olho para exibir a fatia axial no visualizador 3D", + "9_TextBox_1": "Use o controlo deslizante do visualizador vermelho para navegar pelos cortes de RM axial.\n\nSlicer exibe simultaneamente a fatia axial no espectador 3D", + "10_TextBox_0": "Selecione o modelo de pele e baixe a sua opacidade usando o controlo deslizante de opacidade na guia Display 3D", + "10_TextBox_1": "O modelo skull_bone.vtk aparece através da pele.", + "11_TextBox_0": "Posicione o rato no visualizador 3D, clique no botão esquerdo para arrastar e girar o modelo.\nClique no botão direito do rato para ampliar e sair", + "12_AnatomicalViews_title": "Visões anatômicas", + "12_TextBox_0": "Clique nos ícones de alfinete no canto superior esquerdo do visor vermelho e verde para exibir o menu do espectador de cortes\n\nClique no ícone do olho para exibir o corte axial e coronal no visualizador 3D", + "13_TextBox_0": "Desligue a visibilidade do crânio para exibir o modelo de matéria branca do cérebro", + "14_TextBox_0": "A superfície da matéria branca, bem como os nervos óticos esquerdo e direito, aparecem no visualizador", + "15_TextBox_0": "Selecione o modelo hemispheric_white_matter.vtk\n\nVerificar Clipping na guia Display 3D\n\nNa guia Clipping Planes, selecione a opção 'Green Slice Clipping' e verifique 'Negativo'", + "16_TextBox_1": "*Este tutorial foi uma breve introdução na visualização 3D interativa de dados de RM e modelos 3D em Slicer.\n\n*O Compêndio de treino Slicer5 contém uma série de tutoriais e conjuntos de dados pré-computados para aprender a usar o software.", + "17_TextBox_1": "Aliança Nacional para Computação de\nImagem Médica\nNIH U54EB005149\n\nCentro de Análise de Neuroimagem\nNIH P41EB015902\n", + "7_3DVisualization_title": "Visualização 3D", + "9_3DVisualization_title": "Visualização 3D", + "10_3DVisualization_title": "Visualização 3D", + "11_3DVisualization_title": "Visualização 3D", + "13_3DVisualization_title": "Visualização 3D", + "14_3DVisualization_title": "Visualização 3D", + "15_3DVisualization_title": "Visualização 3D", + "17_TextBox_0": "Agradecimentos" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json new file mode 100644 index 00000000..f7d01c66 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D. \nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Tutorial", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets\n\nSelect the dataset3_ProstateMRI and click on Open", + "11_TextBox_0": "Slicer loads the prostate MRI dataset", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelect the MONAIAuto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-t2 and the Input ADC volume msd-prostate-01-adc", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer starts the inference", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Acknowledgements", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en-US.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en-US.json new file mode 100644 index 00000000..f7d01c66 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en-US.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D. \nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Tutorial", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets\n\nSelect the dataset3_ProstateMRI and click on Open", + "11_TextBox_0": "Slicer loads the prostate MRI dataset", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelect the MONAIAuto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-t2 and the Input ADC volume msd-prostate-01-adc", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer starts the inference", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Acknowledgements", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json new file mode 100644 index 00000000..3aa2aa14 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AIBasedSegmentationIn3DSlicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Segmentación basada en IA en 3D Slicer", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Clic en Agregar datos en el módulo Bienvenido a \tSlicer", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Tutorial", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Clic en Crear nueva segmentación en\nAplicar", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation", + "8_TextBox_0": "Slicer muestra el resultado de la segmentación prostática basada en AI", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Selecciona el modelo Segmentación de Tumor Cerebral\n(BRATS) GLI", + "11_TextBox_0": "Ingrese los volúmenes de entrada de la siguiente manera:\nVolumen de entrada T2F: BraTS-GLI_00005-000-t12f\nVolumen de entrada T1C: BraTS-GLI_00005-000-t1c\nVolumen de entrada T1N: BraTS-GLI_00005-000-t1n\nVolumen de entrada T2W: BraTS-GLI_00005-000-t2w\nClic en Crear nueva segmentación al Aplicar\nClic en Aplicar para iniciar la segmentación", + "12_TextBox_0": "Slicer comienza a ejecutar la tarea de inferencia", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Seleccione el modelo Próstata – Multisecuencia", + "14_TextBox_0": "En el añadir módulo de datos DICOM\nseleccione al Paciente paciente1 y\ndoble clic en la imagen\nCT_Torax_Abdomen para cargarlo en\nSlicer", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer inicia la inferencia", + "16_TextBox_0": "Seleccionar el input Volumen 6: CT_Torax_Abdomen\nClic en Crear nueva Segmentación en Aplicar\nClic en Aplicar para iniciar la segmentación", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Agradecimientos", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json new file mode 100644 index 00000000..5e33ee75 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AIBasedSegmentationIn3DSlicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Segmentation basée sur l'IA dans 3D Slicer", + "1_TextBox_0": "Segmentation manuelle vs segmentation assistée par IA", + "2_TextBox_0": "Segmentation manuelle vs segmentation assistée par IA", + "1_TextBox_1": "Cliquez sur Add Data dans le module Welcome to Slicer", + "2_TextBox_1": "Au cours de la dernière décennie, la segmentation d’images a été révolutionnée par le développement d’algorithmes de deep learning (par exemple nnUnet développé par le German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nLes outils de segmentation assistés par IA peuvent réduire le temps de segmentation et fournir des résultats plus reproductibles.", + "3_TextBox_0": "Terminologie de l’IA", + "3_TextBox_1": "Un modèle est un algorithme d’IA entraîné pour accomplir une tâche spécifique (par exemple, un modèle de segmentation de tumeur cérébrale).\n\nLes poids d’un modèle d’IA sont de petits nombres qui déterminent l’importance que le modèle attribue aux différentes caractéristiques de l’image.\n\nLors de la phase d’entraînement, un modèle apprend des motifs à partir de données étiquetées par des experts et ajuste ses poids pour améliorer ses prédictions.\n\nLors de la phase de Validation/Test, le modèle est évalué sur un ensemble de données distinct, non utilisé pendant l’entraînement.\n\nLors de l’inférence, le modèle est appliqué à de nouveaux jeux de données pour réaliser la tâche spécifique pour laquelle il a été entraîné.", + "4_TextBox_0": "Tutoriel IA 3D Slicer", + "4_TextBox_1": "Ce tutoriel se concentre sur l’exécution de tâches d’inférence en utilisant différents modèles d’IA pré-entraînés pour la segmentation automatisée de structures anatomiques et pathologiques.", + "5_TextBox_0": "Extension Slicer MONAIAuto3DSeg", + "6_TextBox_0": "Extension Slicer MONAIAuto3DSeg", + "5_TextBox_1": "Ce tutoriel utilise les modèles pré-entraînés de l’extension Slicer MONAIAuto3DSeg.\n\n\nL’outil est conçu pour fonctionner sur des ordinateurs portables ou des ordinateurs de bureau standards sans GPU.", + "6_TextBox_1": "Cliquez sur Create new segmentation sur Apply", + "7_TextBox_0": "Tutoriel IA Slicer : Tâches de segmentation", + "7_TextBox_1": "Tâche de segmentation #1 : Prostate\n\n\nTâche de segmentation #2 : Gliome cérébral\n\n\nTâche de segmentation #3 : Segmentation du corps entier", + "8_TextBox_0": "Slicer affiche le résultat de la segmentation de la prostate basée sur l’IA", + "9_TextBox_1": "Segmentation assistée par IA de la zone périphérique (PZ) et de la zone de transition (TZ) de la prostate sur des images IRM pondérées en T2.\n\n\nJeux de données :\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Sélectionner le modèle Brain Tumor Segmentation\n(BRATS) GLI", + "11_TextBox_0": "Saisissez les volumes d’entrée comme suit :\nVolume T2F d’entrée : BraTS-GLI_00005-000-t12f\nVolume T1C d’entrée : BraTS-GLI_00005-000-t1c\nVolume T1N d’entrée : BraTS-GLI_00005-000-t1n\nVolume T2W d’entrée : BraTS-GLI_00005-000-t2w\nCliquez sur Create new Segmentation dans Apply\nCliquez sur Apply pour démarrer la segmentation", + "12_TextBox_0": "Slicer commence l’exécution de la tâche d’inférence", + "13_TextBox_0": "Saisissez le nom du modèle Prostate dans le menu Segmentation model", + "13_TextBox_1": "Sélectionner le modèle Prostate - Multiséquence", + "14_TextBox_0": "Dans le module Add DICOM Data, sélectionnez le patient patient1 et double-cliquez sur l’image CT_Thorax_Abdomen pour la charger dans Slicer", + "14_TextBox_1": "Cliquez sur Créer une nouvelle segmentation puis sur Appliquer", + "15_TextBox_0": "Slicer démarre l’inférence", + "16_TextBox_0": "Sélectionnez le volume d’entrée 6 : CT_Thorax_Abdomen\nCliquez sur Create new Segmentation dans Apply \nCliquez sur Apply pour démarrer la segmentation", + "17_TextBox_0": "Segmentation IA Tâche #2 : Gliome cérébral", + "18_TextBox_1": "Segmentation assistée par IA des néoplasmes, de la nécrose et de l’œdème dans les images IRM cérébrales.\n\n\nJeux de données :\n1) BraTS-GLI_00005-000-t1n (pondérée en T1)\n2) BraTS-GLI_00005-000-t1c (pondérée en T1 post-Gd)\n3) BraTS-GLI_00005-000-t2w (pondérée en T2)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR)", + "19_TextBox_1": "Cliquez sur Ajouter données dans le module Bienvenue sur Slicer.\n\nCliquez sur Choisir Fichier(s) à Ajouter et naviguez jusqu’à l’emplacement des jeux de données Slicer.\n\nDans le sous-répertoire dataset4_BrainMRI_Glioma, sélectionnez les quatre jeux de données : BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz.\n\nCliquez sur Ouvrir", + "20_TextBox_0": "Sélectionnez le module MONAIAuto3DSeg et saisissez le nom du modèle Brain Tumor Segmentation dans le menu Segmentation model", + "20_TextBox_1": "Sélectionnez le modèle Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Saisissez les volumes d’entrée comme suit :\n\nVolume T2F : BraTS-GLI_00005-000-t2f\nVolume T1C : BraTS-GLI_00005-000-t1c\nVolume T1N : BraTS-GLI_00005-000-t1n\nVolume T2W : BraTS-GLI_00005-000-t2w\n\n\nCliquez sur Créer une nouvelle segmentation\n\nCliquez sur Appliquez pour lancer la segmentation", + "22_TextBox_1": "Slicer commence l’exécution de la tâche d’inférence\n\nUne fois la segmentation terminée, Processing finished apparaît dans l’interface de Slicer", + "23_TextBox_1": "Cliquez sur Affichage 3D pour afficher les segments 3D dans le visionneur 3D", + "24_TextBox_0": "Segmentation IA tâche #3 : Segmentation du corps entier", + "25_TextBox_1": "Segmentation assistée par IA de l’ensemble du corps.\n\n\nJeu de données : \nCT_ThoraxAbdomen", + "26_TextBox_0": "Dans le module Ajouter Données DICOM, sélectionnez le patient patient1 et double-cliquez sur l’image CT_Thorax_Abdomen pour la charger dans Slicer", + "27_TextBox_0": "Sélectionnez le module MONAIAuto3DSeg et saisissez le nom du modèle Whole Body Segmentation dans le menu Segmentation model", + "27_TextBox_1": "Sélectionnez le modèle Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Sélectionnez le volume d’entrée 6 : CT_Thorax_Abdomen,\n\nCliquez sur Créer une nouvelle segmentation\n\nCliquez sur Appliquez pour lancer la segmentation", + "29_TextBox_0": "Slicer affiche les résultats de la segmentation assistée par IA en utilisant le modèle Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "L’extension MONAIAuto3DSeg de 3D Slicer permet une segmentation rapide assistée par IA des structures anatomiques et pathologiques.\n\n\nLe module peut fonctionner sur des ordinateurs portables et de bureau standards, sans GPU.", + "31_TextBox_0": "Remerciements", + "31_TextBox_1": "Le projet d’internationalisation de 3D Slicer et le projet 3D Slicer pour l’Amérique latine ont été rendus possibles grâce au financement de la Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..21a5acba --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "Segmentação baseada em IA no 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital ,\nEscola de Medicina de Harvard\nBoston, MA", + "0_TextBox_3": "Oficina de Slicer Ribeirão Preto\n30 de junho de 2025", + "1_TextBox_0": "Segmentação Manual vs por IA", + "2_TextBox_0": "Segmentação Manual vs por IA", + "1_TextBox_1": "As imagens médicas têm sido tradicionalmente segmentadas manualmente, o que é um processo demorado que requer esforço intensivo de radiologistas e está sujeito à variabilidade inter-reader.", + "2_TextBox_1": "Na última década, a segmentação de imagem tem sido alimentada pelo desenvolvimento de algoritmos de aprendizagem profunda (por exemplo, nnUnet pelo Centro Alemão de Pesquisa de Câncer (DKFZ)/Helmholtz Research).\nAs ferramentas de segmentação alimentadas por IA podem reduzir o tempo de segmentação e proporcionar resultados mais reprodutíveis.", + "3_TextBox_0": "Terminologia", + "3_TextBox_1": "Um Modelo é um algoritmo de IA que foi treinado para executar uma tarefa específica (por exemplo, modelo de segmentação de tumor cerebral).\n\nOs Pesos de um modelo de IA são números pequenos que determinam quanta importância o modelo dá a diferentes características da imagem.\n\nDurante a fase de Treinamento, um modelo aprende padrões de dados rotulados por especialistas e ajusta seus pesos para melhorar suas previsões.\n\nDurante a fase de Validação/Teste, o modelo é avaliado em um conjunto separado de dados não usados durante a fase de Treinamento.\n\nDurante a Inferência, o modelo é aplicado a novos conjuntos de dados para executar a tarefa específica para a qual foi treinado.", + "4_TextBox_0": "Tutorial de IA do 3D Slicer", + "4_TextBox_1": "Este tutorial se concentra na execução de tarefas de inferência usando vários modelos de IA pré-treinados para segmentação automatizada de estruturas anatômicas e patológicas.", + "5_TextBox_0": "Extensão MONAIAuto3DSeg do Slicer", + "6_TextBox_0": "Extensão MONAIAuto3DSeg do Slicer", + "5_TextBox_1": "Este tutorial usa os modelos pré-treinados da extensão MONAIAuto3DSeg do Slicer.\n\n\nA ferramenta foi projetada para funcionar em laptops ou computadores desktop médios sem GPU.", + "6_TextBox_1": "Suporte a múltiplas modalidades (TC, RM).\n\n\nMúltiplas anatomias (cabeça, tórax, abdome, pelve, etc.).\n\n\nMúltiplas patologias (tumor, hemorragia, edema).", + "7_TextBox_0": "Tutorial de IA do Slicer: Tarefas de Segmentação", + "7_TextBox_1": "Tarefa de Segmentação #1: Próstata\n\n\nTarefa de Segmentação #2: Glioma Cerebral\n\n\nTarefa de Segmentação #3: Segmentação de Corpo Inteiro", + "8_TextBox_0": "Tarefa de Segmentação por IA #1: Próstata", + "9_TextBox_1": "Segmentação baseada em IA da Zona Periférica (ZP) e Zona de Transição (ZT) da próstata em imagens de RM ponderadas em T2.\n\n\nConjunto de dados:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Clique em Adicionar Dados no módulo Welcome to Slicer\n\nClique em Escolher Diretório para Adicionar e navegue até o local dos conjuntos de dados do Slicer\n\nSelecione dataset3_ProstateMRI e clique em Abrir", + "11_TextBox_0": "O Slicer carrega o conjunto de dados de RM de próstata", + "12_TextBox_0": "Clique em Welcome to Slicer no menu de Módulos e navegue até a categoria Segmentation\n\nSelecione o módulo MONAIAuto3DSeg", + "13_TextBox_0": "Digite o nome do modelo Prostate no menu de modelo de Segmentação", + "13_TextBox_1": "Selecione o modelo Prostate - Multisequence", + "14_TextBox_0": "Digite o volume T2 de entrada msd-prostate-01-t2 e o volume ADC de entrada msd-prostate-01-adc", + "14_TextBox_1": "Clique em Criar nova segmentação em Aplicar", + "15_TextBox_0": "O Slicer inicia a inferência", + "16_TextBox_0": "O Slicer mostra os resultados da segmentação de próstata baseada em IA", + "17_TextBox_0": "Tarefa de Segmentação por IA #2: Glioma Cerebral", + "18_TextBox_1": "Segmentação baseada em IA de Neoplasia, Necrose e Edema em imagens de RM cerebral.\n\n\nConjuntos de dados:\n1) BraTS-GLI_00005-000-t1n (ponderado em T1)\n2) BraTS-GLI_00005-000-t1c (ponderado em T1 pós-Gd)\n3) BraTS-GLI_00005-000-t2w (ponderado em T2)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR)", + "19_TextBox_1": "Clique em Adicionar Dados no módulo Welcome to Slicer\n\nClique em Escolher Arquivo(s) para Adicionar e navegue até o local dos conjuntos de dados do Slicer\n\nNo subdiretório dataset4_BrainMRI_Glioma, selecione os quatro conjuntos de dados BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClique em Abrir", + "20_TextBox_0": "Selecione o módulo MONAIAuto3DSeg e digite o nome do modelo Brain Tumor Segmentation no menu de modelo de Segmentação", + "20_TextBox_1": "Selecione o modelo Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Digite os volumes de entrada como segue:\n\nVolume T2F de entrada: BraTS-GLI_00005-000-t2f\nVolume T1C de entrada: BraTS-GLI_00005-000-t1c\nVolume T1N de entrada: BraTS-GLI_00005-000-t1n\nVolume T2W de entrada: BraTS-GLI_00005-000-t2w\n\n\nClique em Criar nova Segmentação em Aplicar\n\nClique em Aplicar para iniciar a segmentação", + "22_TextBox_1": "O Slicer começa a executar a tarefa de inferência\n\nQuando a segmentação é concluída, 'Processamento finalizado' aparece na interface do Slicer", + "23_TextBox_1": "Clique em Mostrar 3D para exibir os segmentos 3D no Visualizador 3D", + "24_TextBox_0": "Tarefa de Segmentação por IA #3: Segmentação de Corpo Inteiro", + "25_TextBox_1": "Segmentação baseada em IA do corpo inteiro.\n\n\nConjunto de dados:\nCT_ThoraxAbdomen", + "26_TextBox_0": "No módulo Adicionar Dados DICOM, selecione o Paciente patient1 e clique duas vezes na imagem CT_Thorax_Abdomen para carregá-la no Slicer", + "27_TextBox_0": "Selecione o módulo MONAIAuto3DSeg e digite o nome do modelo Whole Body Segmentation no menu de modelo de Segmentação", + "27_TextBox_1": "Selecione o modelo Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Selecione o Volume de entrada 6:CT_Thorax_Abdomen,\n\nClique em Criar nova Segmentação em Aplicar\n\nClique em Aplicar para iniciar a segmentação", + "29_TextBox_0": "O Slicer exibe os resultados da segmentação baseada em IA usando o Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusão", + "30_TextBox_1": "A extensão MONAIAuto3DSeg do 3D Slicer fornece segmentação rápida baseada em IA de estruturas anatômicas e patológicas.\n\n\nO módulo pode ser executado em laptops e computadores desktop padrão sem GPU.", + "31_TextBox_0": "Agradecimentos", + "31_TextBox_1": "O projeto de internacionalização do 3D Slicer e o projeto 3D Slicer para América Latina foram possíveis através do financiamento da Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt_PT.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt_PT.json new file mode 100644 index 00000000..f860b2fd --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt_PT.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "Segmentação baseada em IA no 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital ,\nEscola de Medicina de Harvard\nBoston, MA", + "0_TextBox_3": "Oficina de Slicer Ribeirão Preto\n30 de junho de 2025", + "1_TextBox_0": "Segmentação Manual vs por IA", + "2_TextBox_0": "Segmentação Manual vs por IA", + "1_TextBox_1": "As imagens médicas têm sido tradicionalmente segmentadas manualmente, um processo demorado que requer esforço intensivo de radiologistas e sujeito à variabilidade inter-reader.", + "2_TextBox_1": "Na última década, a segmentação de imagens tem sido alimentada pelo desenvolvimento de algoritmos de aprendizagem profunda (por exemplo, nnUnet pelo Centro Alemão de Pesquisa de Câncer (DKFZ)/Helmholtz Research).\n\n\nAs ferramentas de segmentação alimentadas por IA podem reduzir o tempo de segmentação e proporcionar resultados mais reprodutíveis.", + "3_TextBox_0": "Terminologia", + "3_TextBox_1": "Um Modelo é um algoritmo de IA que foi treinado para executar uma tarefa específica (por exemplo, modelo de segmentação de tumor cerebral).\n\nOs Pesos de um modelo de IA são números pequenos que determinam quanta importância o modelo dá a diferentes características da imagem.\n\nDurante a fase de Treino, um modelo aprende padrões de dados rotulados por especialistas e ajusta os seus pesos para melhorar as suas previsões.\n\nDurante a fase de Validação/Teste, o modelo é avaliado num conjunto separado de dados não usados durante a fase de Treino.\n\nDurante a Inferência, o modelo é aplicado a novos conjuntos de dados para executar a tarefa específica para a qual foi treinado.", + "4_TextBox_0": "Tutorial de IA do 3D Slicer", + "4_TextBox_1": "Este tutorial concentra-se na execução de tarefas de inferência usando vários modelos de IA pré-treinados para segmentação automatizada de estruturas anatômicas e patológicas.", + "5_TextBox_0": "Extensão MONAIAuto3DSeg do Slicer", + "6_TextBox_0": "Extensão MONAIAuto3DSeg do Slicer", + "5_TextBox_1": "Este tutorial usa os modelos pré-treinados da extensão MONAIAuto3DSeg do Slicer.\n\n\nA ferramenta foi projetada para funcionar em portátis ou computadores desktop médios sem GPU.", + "6_TextBox_1": "Apoio a múltiplas modalidades (TC, RM).\n\n\nMúltiplas anatomias (cabeça, tórax, abdome, pelve, etc.).\n\n\nMúltiplas patologias (tumor, hemorragia, edema).", + "7_TextBox_0": "Tutorial de IA do Slicer: Tarefas de Segmentação", + "7_TextBox_1": "Tarefa de Segmentação #1: Próstata\n\n\nTarefa de Segmentação #2: Glioma Cerebral\n\n\nTarefa de Segmentação #3: Segmentação de Corpo Inteiro", + "8_TextBox_0": "Tarefa de Segmentação por IA #1: Próstata", + "9_TextBox_1": "Segmentação baseada em IA da Zona Periférica (ZP) e Zona de Transição (ZT) da próstata em imagens de RM ponderadas em T2.\n\n\nConjunto de dados:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Clique em Adicionar Dados no módulo Welcome to Slicer\n\nClique em Escolher Diretório para Adicionar e navegue até o local dos conjuntos de dados do Slicer\n\nSelecione dataset3_ProstateMRI e clique em Abrir", + "11_TextBox_0": "O Slicer carrega o conjunto de dados de RM de próstata", + "12_TextBox_0": "Clique em Welcome to Slicer no menu de Módulos e navegue até a categoria Segmentation\n\nSelecione o módulo MONAIAuto3DSeg", + "13_TextBox_0": "Digite o nome do modelo Prostate no menu de modelo de Segmentação", + "13_TextBox_1": "Selecione o modelo Prostate - Multisequence", + "14_TextBox_0": "Digite o volume T2 de entrada msd-prostate-01-t2 e o volume ADC de entrada msd-prostate-01-adc", + "14_TextBox_1": "Clique em Criar segmentação em Aplicar", + "15_TextBox_0": "O Slicer inicia a inferência", + "16_TextBox_0": "O Slicer mostra os resultados da segmentação de próstata baseada em IA", + "17_TextBox_0": "Tarefa de Segmentação por IA #2: Glioma Cerebral", + "18_TextBox_1": "Segmentação baseada em IA de Neoplasia, Necrose e Edema em imagens de RM cerebral.\n\n\nConjuntos de dados:\n1) BraTS-GLI_00005-000-t1n (ponderado em T1)\n2) BraTS-GLI_00005-000-t1c (ponderado em T1 pós-Gd)\n3) BraTS-GLI_00005-000-t2w (ponderado em T2)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR)", + "19_TextBox_1": "Clique em Adicionar Dados no módulo Welcome to Slicer\n\nClique em Escolher Ficheiro(s) para Adicionar e navegue até o local dos conjuntos de dados do Slicer\n\nNo subdiretório dataset4_BrainMRI_Glioma, selecione os quatro conjuntos de dados BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClique em Abrir", + "20_TextBox_0": "Selecione o módulo MONAIAuto3DSeg e digite o nome do modelo Brain Tumor Segmentation no menu de modelo de Segmentação", + "20_TextBox_1": "Selecione o modelo Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Digite os volumes de entrada como a seguir:\n\nVolume T2F de entrada: BraTS-GLI_00005-000-t2f\nVolume T1C de entrada: BraTS-GLI_00005-000-t1c\nVolume T1N de entrada: BraTS-GLI_00005-000-t1n\nVolume T2W de entrada: BraTS-GLI_00005-000-t2w\n\n\nClique em Criar Segmentação em Aplicar\n\nClique em Aplicar para iniciar a segmentação", + "22_TextBox_1": "O Slicer começa a executar a tarefa de inferência\n\nQuando a segmentação é concluída, 'Processamento finalizado' aparece na interface do Slicer", + "23_TextBox_1": "Clique em Mostrar 3D para exibir os segmentos 3D no Visualizador 3D", + "24_TextBox_0": "Tarefa de Segmentação por IA #3: Segmentação de Corpo Inteiro", + "25_TextBox_1": "Segmentação baseada em IA do corpo inteiro.\n\n\nConjunto de dados:\nCT_ThoraxAbdomen", + "26_TextBox_0": "No módulo Adicionar Dados DICOM, selecione o Utente patient1 e clique duas vezes na imagem CT_Thorax_Abdomen para carregá-la no Slicer", + "27_TextBox_0": "Selecione o módulo MONAIAuto3DSeg e digite o nome do modelo Whole Body Segmentation no menu de modelo de Segmentação", + "27_TextBox_1": "Selecione o modelo Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Selecione o Volume de entrada 6:CT_Thorax_Abdomen,\n\nClique em Criar Segmentação em Aplicar\n\nClique em Aplicar para iniciar a segmentação", + "29_TextBox_0": "O Slicer exibe os resultados da segmentação baseada em IA usando o Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusão", + "30_TextBox_1": "A extensão MONAIAuto3DSeg do 3D Slicer fornece segmentação rápida baseada em IA de estruturas anatômicas e patológicas.\n\n\nO módulo pode ser executado em portátis e computadores desktop padrão sem GPU.", + "31_TextBox_0": "Agradecimentos", + "31_TextBox_1": "O projeto de internacionalização do 3D Slicer e o projeto 3D Slicer para América Latina foram possíveis através do financiamento da Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json new file mode 100644 index 00000000..66a9ff1e --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D. \nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Tutorial", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "மூளை கட்டி பிரிவின் மாதிரியைத் தேர்ந்தெடுக்கவும் \n(பிராட்ச்) சி.எல்.ஐ", + "11_TextBox_0": "Slicer loads the prostate MRI dataset", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelect the MONAIAuto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "ப்ரோச்டேட் - மல்டிசீக்வென்ச் மாதிரியைத் தேர்ந்தெடுக்கவும்", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-t2 and the Input ADC volume msd-prostate-01-adc", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer starts the inference", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Acknowledgements", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json new file mode 100644 index 00000000..f7d01c66 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D. \nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Tutorial", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets\n\nSelect the dataset3_ProstateMRI and click on Open", + "11_TextBox_0": "Slicer loads the prostate MRI dataset", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelect the MONAIAuto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-t2 and the Input ADC volume msd-prostate-01-adc", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer starts the inference", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Acknowledgements", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json new file mode 100644 index 00000000..5e18e66a --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AIBasedSegmentationIn3DSlicer", + "0_TextBox_1": "Соня Пуйоль, доктор філ.", + "0_TextBox_3": "AI - Сегментація на основі 3D Slicer", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Натисніть кнопку «Додати дані» у вікні привітання \tМодуль Slicer", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Tutorial", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Натисніть кнопку «Створити нову сегментацію» на сторінці\n«Застосувати»", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation", + "8_TextBox_0": "Slicer показує результат сегментації простати на основі штучного інтелекту", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Виберіть модель сегментації пухлини головного мозку\n(BRATS) GLI", + "11_TextBox_0": "Введіть вхідні об'єми наступним чином:\nВхідний об'єм T2F: BraTS-GLI_00005-000-t12f\nВхідний об'єм T1C: BraTS-GLI_00005-000-t1c\nВхідний об'єм T1N: BraTS-GLI_00005-000-t1n\nВхідний об'єм T2W: BraTS-GLI_00005-000-t2w\nНатисніть «Створити нову сегментацію» на кнопці «Застосувати»\nНатисніть «Застосувати», щоб розпочати сегментацію", + "12_TextBox_0": "Зрізальник починає виконувати завдання виведення", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Виберіть модель Простата - Мультисеквенція", + "14_TextBox_0": "У модулі «Додати дані DICOM»\nвиберіть пацієнта patient1 та\nдвічі клацніть на зображенні\nCT_Thorax_Abdomen, щоб завантажити його в\nSlicer", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer починає висновок", + "16_TextBox_0": "Виберіть вхідний том 6: КТ_Грудної_черевної_плоди,\nНатисніть «Створити нову сегментацію» на кнопці «Застосувати»\nНатисніть «Застосувати», щоб розпочати сегментацію", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Подяки", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative." +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_ar_SA.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_ar_SA.json new file mode 100644 index 00000000..fafa50dc --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_ar_SA.json @@ -0,0 +1,99 @@ +{ + "1_TextBox_1": "This tutorial is an introduction to the basics of loading and viewing DICOM images and 3D models in 3D Slicer.", + "3_TextBox_0": "Tutorial materials", + "4_TextBox_0": "Tutorial dataset", + "33_TextBox_0": "Tutorial dataset", + "5_TextBox_0": "Disclaimer", + "6_TextBox_0": "Tutorial Outline", + "8_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "9_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "8_TextBox_1": "The patient1 study contains a CT Thorax Abdomen dataset", + "11_ArrowText_2": "Select the module \nVolumes", + "10_VisualizingDICOMimages_title": "Visualizing DICOM images", + "11_VisualizingDICOMimages_title": "Visualizing DICOM images", + "12_VisualizingDICOMimages_title": "Visualizing DICOM images", + "13_VisualizingDICOMimages_title": "Visualizing DICOM images", + "14_VisualizingDICOMimages_title": "Visualizing DICOM images", + "15_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_VisualizingDICOMimages_title": "Visualizing DICOM images", + "17_VisualizingDICOMimages_title": "Visualizing DICOM images", + "18_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_TextBox_0": "Slicer switches the layout \nto Conventional \nWidescreen layout", + "17_TextBox_0": "Use the right mouse button in the \n3D Viewer to zoom in and out", + "19_3DViewerController_title": "3D Viewer Controller", + "20_3DViewerController_title": "3D Viewer Controller", + "22_TextBox_0": "Volume Rendering", + "23_VolumeRendering_title": "Volume Rendering", + "24_VolumeRendering_title": "Volume Rendering", + "25_VolumeRendering_title": "Volume Rendering", + "26_VolumeRendering_title": "Volume Rendering", + "27_VolumeRendering_title": "Volume Rendering", + "28_VolumeRendering_title": "Volume Rendering", + "29_VolumeRendering_title": "Volume Rendering", + "30_VolumeRendering_title": "Volume Rendering", + "31_VolumeRendering_title": "Volume Rendering", + "24_TextBox_2": "Select VTK GPU Ray Casting Rendering\nClick on the eye icon in the Volume tab to display \nthe volume rendered image in the 3D viewer", + "26_ArrowText_0": "Click on Display ROI to \ndisplay a region of interest \n(ROI) in the 3D viewer and \ncheck the option Enable", + "28_ArrowText_0": "Click on the eye icon to \ndisplay the volume rendered \nimage", + "29_TextBox_0": "Slicer displays the \nvolume rendered \nimage of the left kidney ", + "30_TextBox_0": "Extend the ROI to generate \na volume rendered image of \nthe right kidney", + "34_TextBox_0": "Slicer Scene", + "35_LoadingaScene_title": "Loading a Scene", + "35_TextBox_0": "Slicer displays a 3D \nsurface model of the \nhead and 2D MRI slices", + "36_Viewing3Dmodels_title": "Viewing 3D models", + "37_Viewing3Dmodels_title": "Viewing 3D models", + "38_Viewing3Dmodels_title": "Viewing 3D models", + "39_Viewing3Dmodels_title": "Viewing 3D models", + "40_Viewing3Dmodels_title": "Viewing 3D models", + "36_ArrowText_0": "Position the cursor over \nthe pin icon to reveal the \nslice menu and click on \nthe eye icon to display the \naxial slice in the 3D viewer", + "41_Interactingwith3Dmodels_title": "Interacting with 3D models", + "42_Interactingwith3Dmodels_title": "Interacting with 3D models", + "43_Interactingwith3Dmodels_title": "Interacting with 3D models", + "44_Interactingwith3Dmodels_title": "Interacting with 3D models", + "38_ArrowText_0": "Lower the opacity of \nthe Skin model using \nthe visibility slider", + "38_TextBox_1": "The skull bone and \neyeballs models appear \nthrough the skin", + "40_TextBox_2": "The white matter and \noptic nerve models \nappear through the skin", + "40_ArrowText_1": "Select the skull bone \nmodel and click on the \neye icon to turn off its \nvisibility", + "0_TextBox_0": "Basics of Data Loading and 3D Visualization in 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Overall Goal", + "2_TextBox_0": "Learning Objectives", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_TextBox_0": "Slicer displays the axial, coronal \nand sagittal images of the CT \nThorax Abdomen dataset ", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_ArrowText_0": "Click on Preset in the Display tab \nand select the preset CT-Cardiac3 ", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "41_ArrowText_0": "Click on the eye icon to \ndisplay the coronal slice \nin the 3D viewer", + "42_ArrowText_2": "Select the hemispheric \nwhite matter model and \nselect the option Clipping", + "43_TextBox_0": "Move the coronal slice \nposteriorily to display the \noptic chiasm", + "44_TextBox_0": "Slicer displays a 3D view of \nthe optic chiasm", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Acknowledgements", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)", + "45_TextBox_0": "Conclusion" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en-US.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en-US.json new file mode 100644 index 00000000..fafa50dc --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en-US.json @@ -0,0 +1,99 @@ +{ + "1_TextBox_1": "This tutorial is an introduction to the basics of loading and viewing DICOM images and 3D models in 3D Slicer.", + "3_TextBox_0": "Tutorial materials", + "4_TextBox_0": "Tutorial dataset", + "33_TextBox_0": "Tutorial dataset", + "5_TextBox_0": "Disclaimer", + "6_TextBox_0": "Tutorial Outline", + "8_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "9_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "8_TextBox_1": "The patient1 study contains a CT Thorax Abdomen dataset", + "11_ArrowText_2": "Select the module \nVolumes", + "10_VisualizingDICOMimages_title": "Visualizing DICOM images", + "11_VisualizingDICOMimages_title": "Visualizing DICOM images", + "12_VisualizingDICOMimages_title": "Visualizing DICOM images", + "13_VisualizingDICOMimages_title": "Visualizing DICOM images", + "14_VisualizingDICOMimages_title": "Visualizing DICOM images", + "15_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_VisualizingDICOMimages_title": "Visualizing DICOM images", + "17_VisualizingDICOMimages_title": "Visualizing DICOM images", + "18_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_TextBox_0": "Slicer switches the layout \nto Conventional \nWidescreen layout", + "17_TextBox_0": "Use the right mouse button in the \n3D Viewer to zoom in and out", + "19_3DViewerController_title": "3D Viewer Controller", + "20_3DViewerController_title": "3D Viewer Controller", + "22_TextBox_0": "Volume Rendering", + "23_VolumeRendering_title": "Volume Rendering", + "24_VolumeRendering_title": "Volume Rendering", + "25_VolumeRendering_title": "Volume Rendering", + "26_VolumeRendering_title": "Volume Rendering", + "27_VolumeRendering_title": "Volume Rendering", + "28_VolumeRendering_title": "Volume Rendering", + "29_VolumeRendering_title": "Volume Rendering", + "30_VolumeRendering_title": "Volume Rendering", + "31_VolumeRendering_title": "Volume Rendering", + "24_TextBox_2": "Select VTK GPU Ray Casting Rendering\nClick on the eye icon in the Volume tab to display \nthe volume rendered image in the 3D viewer", + "26_ArrowText_0": "Click on Display ROI to \ndisplay a region of interest \n(ROI) in the 3D viewer and \ncheck the option Enable", + "28_ArrowText_0": "Click on the eye icon to \ndisplay the volume rendered \nimage", + "29_TextBox_0": "Slicer displays the \nvolume rendered \nimage of the left kidney ", + "30_TextBox_0": "Extend the ROI to generate \na volume rendered image of \nthe right kidney", + "34_TextBox_0": "Slicer Scene", + "35_LoadingaScene_title": "Loading a Scene", + "35_TextBox_0": "Slicer displays a 3D \nsurface model of the \nhead and 2D MRI slices", + "36_Viewing3Dmodels_title": "Viewing 3D models", + "37_Viewing3Dmodels_title": "Viewing 3D models", + "38_Viewing3Dmodels_title": "Viewing 3D models", + "39_Viewing3Dmodels_title": "Viewing 3D models", + "40_Viewing3Dmodels_title": "Viewing 3D models", + "36_ArrowText_0": "Position the cursor over \nthe pin icon to reveal the \nslice menu and click on \nthe eye icon to display the \naxial slice in the 3D viewer", + "41_Interactingwith3Dmodels_title": "Interacting with 3D models", + "42_Interactingwith3Dmodels_title": "Interacting with 3D models", + "43_Interactingwith3Dmodels_title": "Interacting with 3D models", + "44_Interactingwith3Dmodels_title": "Interacting with 3D models", + "38_ArrowText_0": "Lower the opacity of \nthe Skin model using \nthe visibility slider", + "38_TextBox_1": "The skull bone and \neyeballs models appear \nthrough the skin", + "40_TextBox_2": "The white matter and \noptic nerve models \nappear through the skin", + "40_ArrowText_1": "Select the skull bone \nmodel and click on the \neye icon to turn off its \nvisibility", + "0_TextBox_0": "Basics of Data Loading and 3D Visualization in 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Overall Goal", + "2_TextBox_0": "Learning Objectives", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_TextBox_0": "Slicer displays the axial, coronal \nand sagittal images of the CT \nThorax Abdomen dataset ", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_ArrowText_0": "Click on Preset in the Display tab \nand select the preset CT-Cardiac3 ", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "41_ArrowText_0": "Click on the eye icon to \ndisplay the coronal slice \nin the 3D viewer", + "42_ArrowText_2": "Select the hemispheric \nwhite matter model and \nselect the option Clipping", + "43_TextBox_0": "Move the coronal slice \nposteriorily to display the \noptic chiasm", + "44_TextBox_0": "Slicer displays a 3D view of \nthe optic chiasm", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Acknowledgements", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)", + "45_TextBox_0": "Conclusion" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json new file mode 100644 index 00000000..8019fbb8 --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json @@ -0,0 +1,121 @@ +{ + "0_TextBox_0": "Basics of Data Loading and 3D Visualization in 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Overall Goal", + "2_TextBox_0": "Learning Objectives", + "1_TextBox_1": "Este tutorial es una introducción a los conceptos básicos de carga y visualización de imágenes DICOM y modelos 3D en 3D Slicer.", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_0": "Materiales tutoriales", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_0": "Conjunto de datos del tutorial", + "33_TextBox_0": "Pulse en el Archivo ", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_0": "Descargo de responsabilidad", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_0": "Esquema del tutorial", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_LoadingaDICOMvolume_title": "Cargar un volumen DICOM", + "9_LoadingaDICOMvolume_title": "Cargar un volumen DICOM", + "8_ArrowText_0": "Arrastre y suelte el directorio\ndataset1_Thorax_Abdomen\nen Slicer", + "9_TextBox_0": "Haga clic en Aceptar para\ncargar el directorio en la\nbase de datos DICOM", + "10_TextBox_0": "Slicer displays the axial, coronal \nand sagittal images of the CT \nThorax Abdomen dataset ", + "8_TextBox_1": "El estudio patient1 contiene un conjunto de datos de TC de Tórax y Abdomen", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_TextBox_0": "Slicer muestra las imágenes axiales,\ncoronales y sagitales del conjunto de\ndatos de TC de tórax y abdomen \n", + "11_ArrowText_2": "Seleccione el módulo\nVolúmenes", + "13_TextBox_2": "Pulse al izquierdo en DICOM para\nmostrar la lista de módulos de Slicer. ", + "14_ArrowText_0": "Pulse en el CT-abdomen\npreseleccione a ajuste automático\nla ventana/nivel exhibido del\nconjunto de datos CT ", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "15_ArrowText_1": "Pulsa en el icono de Enlaces \npara vincular los controles de \ncorte en todos los Visores de Cortes. ", + "15_ArrowText_2": "Pulse en el icono del ojo para\nvisualizar los tres cortes anatómicos\nen el visor 3D", + "16_TextBox_0": "Slicer cambia el distribución a\nPantalla Ancha Convencional", + "10_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "11_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "12_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "13_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "14_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "15_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "16_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "17_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "18_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "17_ArrowText_1": "Pulse en el icono del menú de diseño\nde la segmentación de datos y seleccione\nel diseño de pantalla ancha convencional ", + "19_VisualizingDICOMimage_title": "Visualizando imagen DICOM", + "20_VisualizingDICOMimage_title": "Visualizando imagen DICOM", + "17_TextBox_0": "Utilice el botón rojo del ratón en\nel Visor 3D para ampliar y reducir", + "20_TextBox_0": "Utilice al botón izquierdo del ratón\nen el Visor 3D para rotar las imágenes ", + "19_3DViewerController_title": "Controlador del Visor 3D", + "20_3DViewerController_title": "Controlador del Visor 3D", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_0": "Representación de Volumen", + "23_TextBox_0": "Parte 2\nRepresentar Volumen", + "23_VolumeRendering_title": "Representación de Volumen", + "24_VolumeRendering_title": "Representación de Volumen", + "25_VolumeRendering_title": "Representación de Volumen", + "26_VolumeRendering_title": "Representación de Volumen", + "27_VolumeRendering_title": "Representación de Volumen", + "28_VolumeRendering_title": "Representación de Volumen", + "29_VolumeRendering_title": "Representación de Volumen", + "30_VolumeRendering_title": "Representación de Volumen", + "31_VolumeRendering_title": "Representación de Volumen", + "24_TextBox_1": "-Técnicas de representar\nel volumen habilita \nvisualización en 3D del\nconjunto de datos\n-El módulo de \nRepresentación de Volumen\nen Slice habilita la visualización\ninteractiva de visualización en 3D\nde imágenes DICOM ", + "25_TextBox_0": "Pulse en Preajuste en la pestaña Pantalla y\nseleccione el preajuste CT-Cardiac3", + "24_TextBox_2": "Seleccione Representación de Ray Casting por GPU VTK.\nPulse en el icono del ojo en la pestaña Volumen para exhibir\nla imagen representada del volumen en el visor 3D", + "27_ArrowText_0": "Utilice el control deslizante de\ndesplazamiento para cambiar la\nfunción de transferencia y exhibir\nla aorta", + "26_ArrowText_0": "Pulse en Mostrar ROI para\nmostrar una región de interés\n(ROI) en el visor 3D y marque\nla opción Habilitar", + "29_ArrowText_0": "Apaga la visibilidad de los\ncortes axial, sagital y coronal\nen el visor 2D. Coloque la ROI\nalrededor del riñón izquierdo\nusando los controles de color", + "28_ArrowText_0": "Pulse en el icono del ojo\npara mostrar la imagen del\nvolumen representado", + "29_TextBox_0": "Slicer exhibe la imagen\nrepresentada por volumen\ndel riñón izquierdo ", + "30_TextBox_0": "Ampliar la ROI para generar\nuna imagen representada en\nvolumen del riñón derecho", + "34_TextBox_0": "Escena Slicer", + "35_TextBox_1": "*Slicer almacena todos los datos cargados en un repositorio llamado escena\n\n*Cada conjunto de datos, como un volumen de imagen, un modelo de superficie o un conjunto de puntos, se representa como un nodo en una escena de Slicer.\n\n*Todos los módulos de Slicer operan con los datos almacenados en una escena de Slicer", + "36_TextBox_1": "*El directorio dataset2_Head contiene\nla escena de Slicer llamada\nHead_scene.mrb\n\n*Esta escena contiene modelos 3D\ndel atlas cerebral SPL desarrollado\npor el Departamento de Radiología\ndel Hospital Brigham and Women’s\nde la Facultad de Medicina de Harvard\n(NIH P41 RR013218, NIH R01 MH05074)", + "35_LoadingaScene_title": "Cargando una Escena", + "37_ArrowText_0": "Arrastre y suelte el archivo\nHead_Scene.mrb, ubicado en\nel directorio dataset2_Head,\nen Slicer", + "35_TextBox_0": "Slicer exhibe un modelo de\nsuperficie 3D de la cabeza y cortes\nde resonancia magnética 2D", + "36_Viewing3Dmodels_title": "Viendo modelos 3D", + "37_Viewing3Dmodels_title": "Viendo modelos 3D", + "38_Viewing3Dmodels_title": "Viendo modelos 3D", + "39_Viewing3Dmodels_title": "Viendo modelos 3D", + "40_Viewing3Dmodels_title": "Viendo modelos 3D", + "36_ArrowText_0": "Coloque el cursor sobre el\nicono del alfiler para abrir el\nmenú de cortes y pulse sobre\nel icono del ojo para ver el\ncorte axial en el visor 3D", + "40_ArrowText_0": "Selecciona los Modelos del \nmódulo en el listado de modelos ", + "41_ArrowText_0": "Pulse en el icono del ojo\npara visualizar el corte\ncoronal en el visor 3D", + "41_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "42_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "43_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "44_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "38_ArrowText_0": "Disminuya la opacidad\ndel modelo de piel con\nel control deslizante de\nvisibilidad", + "38_TextBox_1": "Los modelos de huesos\ndel cráneo y globos oculares\naparecen a través de la piel", + "40_TextBox_2": "Los modelos de sustancia\nblanca y nervio óptico\naparecen a través de la piel", + "40_ArrowText_1": "Seleccione el modelo del\nhueso del cráneo y pulse\nen el icono del ojo para\ndesactivar su visibilidad", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_ArrowText_0": "Click on Preset in the Display tab \nand select the preset CT-Cardiac3 ", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "42_ArrowText_2": "Seleccione el modelo de\nmateria blanca hemisférico y\nseleccione la opción Recorte", + "43_TextBox_0": "Mueva el corte coronal\nposteriormente para visualizar\nel quiasma óptico", + "44_TextBox_0": "Slicer exhibe una vista 3D\ndel quiasma óptico", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Agradecimientos", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)", + "48_TextBox_1": "Dentro de Análisis\nNeuroimage \n(NIBIB P41 EB015902)", + "45_TextBox_0": "Conclusión", + "49_TextBox_1": "*3D Slicer ofrece funciones avanzadas para cargar y\nvisualizar datos de imágenes médicas en 3D.\n\n*El tutorial muestra cómo usar la representación\nvolumétrica y el modelado de superficies en 3D\npara la visualización interactiva de datos de TC y RM.\n\nContacto: spujol@bwh.harvard.edu" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json new file mode 100644 index 00000000..50cc9fbe --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json @@ -0,0 +1,117 @@ +{ + "0_TextBox_0": "Notions de base sur le chargement de données et la visualisation 3D dans 3D Slicer", + "0_TextBox_1": "Auteur : Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Professeur adjoint en radiologie\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Objectif global", + "2_TextBox_0": "Objectifs d’apprentissage", + "1_TextBox_1": "Ce tutoriel est une introduction aux notions de base du chargement et de l’affichage des images DICOM et des modèles 3D dans 3D Slicer.", + "2_TextBox_1": " • À la suite de ce tutoriel, vous serez capable :\n\n• de charger et visualiser des images DICOM dans Slicer\n\n• de réaliser un rendu volumique des données CT\n\n• de charger et visualiser des modèles 3D reconstruits à partir de données IRM", + "3_TextBox_0": "Matériels du tutoriel", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_0": "Jeu de données du tutoriel", + "33_TextBox_0": "Cliquez sur File ", + "4_TextBox_1": "Le fichier 3DVisualizationDataset.zip contient deux répertoires :\n\n- dataset1_Thorax_Abdomen\n- dataset2_Head\n\nDécompressez le fichier 3DVisualizationDataset.zip sur votre ordinateur pour accéder aux jeux de données", + "5_TextBox_0": "Avertissement", + "5_TextBox_1": "• 3D Slicer est un logiciel libre et open source, distribué sous une licence de type BSD.\n\n\n• Le logiciel n’est pas approuvé par la FDA ni marqué CE, et est destiné uniquement à un usage de recherche.\nPlan du tutoriel", + "6_TextBox_0": "Plan du tutoriel", + "6_TextBox_1": "• Partie 1 : Chargement et visualisation des données DICOM\n\n• Partie 2 : Rendu volumique\n\n\n• Partie 3 : Chargement et visualisation des modèles 3D", + "7_TextBox_0": "Partie 1 : Chargement des données DICOM", + "8_LoadingaDICOMvolume_title": "Chargement d’un volume DICOM", + "9_LoadingaDICOMvolume_title": "Chargement d’un volume DICOM", + "8_ArrowText_0": "Glissez-déposez le répertoire \ndataset1_Thorax_Abdomen \ndans Slicer", + "9_TextBox_0": "Cliquez sur OK pour charger \nle répertoire dans \nla base de données DICOM", + "8_TextBox_0": "Slicer affiche l’interface utilisateur du module DICOM", + "8_TextBox_1": "L’étude patient1 contient un jeu de données CT Thorax Abdomen", + "11_ArrowText_1": "Cliquez avec le bouton gauche sur DICOM pour afficher la liste des modules de Slicer", + "12_TextBox_0": "Slicer affiche les images axiale, coronale \net sagittale du jeu de données \nCT Thorax Abdomen. \n", + "11_ArrowText_2": "Sélectionnez le module Volumes", + "13_TextBox_2": "Clic gauche sur DICOM pour afficher la liste des modules de Slicer. ", + "12_ArrowText_0": "Cliquez sur le preset CT-abdomen pour ajuster automatiquement la fenêtre et le niveau d’affichage du jeu de données CT", + "15_ArrowText_0": "Cliquez sur l’icône du menu de disposition de Slicer, puis sélectionnez la disposition Conventional Widescreen", + "15_ArrowText_1": "Cliquez sur l’icône Links pour relier les contrôles des coupes entre toutes les Visionneuses de Coupes. ", + "15_ArrowText_2": "Cliquez sur l’icône Eye pour afficher les trois coupes anatomiques dans la Visionneuse 3D", + "14_TextBox_0": "Les trois coupes anatomiques apparaissent dans le visionneur 3D.", + "10_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "11_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "12_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "13_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "14_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "15_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "16_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "17_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "18_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "17_ArrowText_1": "Cliquez sur l’icône du menu de mise en page de Slicer et sélectionnez la mise en page Conventional Widescreen. ", + "16_TextBox_0": "Slicer passe à la mise en page Conventional Widescreen", + "19_VisualizingDICOMimage_title": "Visualisation d’une image DICOM", + "20_VisualizingDICOMimage_title": "Visualisation d’une image DICOM", + "17_TextBox_0": "Utilisez le bouton droit de la souris dans la Visionneuse 3D pour zoomer avant et arrière", + "18_TextBox_0": "Utilisez le bouton gauche de la souris dans le visionneur 3D pour faire pivoter les images", + "19_3DViewerController_title": "Contrôleur de la Visionneuse 3D", + "20_3DViewerController_title": "Contrôleur de la Visionneuse 3D", + "19_TextBox_0": "Placez le curseur de la souris sur l’icône en forme d’épingle dans la bande bleue de la fenêtre de la visionneuse 3D pour afficher le contrôleur 3DView.\nCliquez sur la deuxième icône de la première rangée du contrôleur 3DView pour centrer la vue 3D sur la scène.", + "22_TextBox_0": "Rendu Volumique", + "23_TextBox_0": "Partie 2 Rendu Volumique", + "23_VolumeRendering_title": "Rendu Volumique", + "24_VolumeRendering_title": "Rendu Volumique", + "25_VolumeRendering_title": "Rendu Volumique", + "26_VolumeRendering_title": "Rendu Volumique", + "27_VolumeRendering_title": "Rendu Volumique", + "28_VolumeRendering_title": "Rendu Volumique", + "29_VolumeRendering_title": "Rendu Volumique", + "30_VolumeRendering_title": "Rendu Volumique", + "31_VolumeRendering_title": "Rendu Volumique", + "24_TextBox_1": "- Les techniques de rendu volumique permettent la visualisation 3D des jeux de données 3D\n- Le module Volume Rendering de Slicer permet la visualisation 3D interactive des images DICOM. ", + "25_TextBox_0": "Cliquez sur Preset dans l’onglet Display et sélectionnez le préréglage CT-Cardiac3", + "24_TextBox_2": "Sélectionnez VTK GPU Ray Casting Rendering\nCliquez sur l’icône Eye dans l’onglet Volume pour afficher l’image en rendu volumique dans la visionneuse 3D", + "25_ArrowText_0": "Utilisez le curseur **Shift** pour modifier la fonction de transfert et afficher l’aorte", + "26_ArrowText_0": "Cliquez sur Display ROI pour afficher une région d’intérêt (ROI) dans la visionneuse 3D et cochez l’option Enable", + "27_ArrowText_0": "Désactivez la visibilité des coupes axiale, sagittale et coronale dans la visionneuse 2D.\nPositionnez la ROI autour du rein gauche en utilisant les poignées colorées.", + "28_ArrowText_0": "Cliquez sur l’icône Eye pour afficher l’image en rendu volumique", + "29_TextBox_0": "Slicer affiche l’image en rendu volumique du rein gauche. ", + "30_TextBox_0": "Étendez la ROI pour générer une image en rendu volumique du rein droit", + "34_TextBox_0": "Scène Slicer", + "35_TextBox_1": "*Slicer stocke toutes les données chargées dans un dépôt appelé scène\n\n*Chaque jeu de données, comme un volume d’image, un modèle de surface ou un ensemble de points, est représenté par un nœud dans une scène Slicer\n\n*Tous les modules de Slicer opèrent sur les données stockées dans une scène Slicer", + "36_TextBox_1": "*Le répertoire dataset2_Head contient la scène Slicer appelée Head_scene.mrb\n\n*La scène contient des modèles 3D de l’atlas cérébral SPL développé par le département de radiologie du Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "35_LoadingaScene_title": "Chargement d’une scène", + "37_ArrowText_0": "Sélectionnez le module Models dans la liste des modules. ", + "35_TextBox_0": "Slicer affiche un modèle de surface 3D de la tête ainsi que des coupes IRM 2D", + "36_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "37_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "38_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "39_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "40_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "36_ArrowText_0": "Placez le curseur sur l’icône en forme d’épingle pour afficher le menu des coupes, puis cliquez sur l’icône en forme d’œil pour afficher la coupe axiale dans la visionneuse 3D", + "38_ArrowText_0": "Réduisez l’opacité du modèle Skin en utilisant le curseur de visibilité", + "41_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "42_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "43_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "44_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "13_TextBox_1": "Placez le curseur de la souris sur la bande rouge du visionneur rouge pour afficher le menu des coupes.\n\n\nCliquez sur l’icône Liens pour lier les commandes des coupes dans tous les visionneurs de coupes.\n\n\nCliquez sur l’icône Yeux pour afficher les trois coupes anatomiques dans le visionneur 3D", + "19_TextBox_1": "Placez le curseur de la souris sur l’icône en forme d’épingle dans la bande bleue de la fenêtre du visionneur 3D pour afficher le contrôleur 3DView\n\nCliquez sur la deuxième icône de la première ligne du contrôleur 3DView pour centrer la vue 3D sur la scène", + "21_TextBox_0": "Partie 2 : Rendu volumique", + "22_TextBox_1": "• Les techniques de rendu volumique permettent la visualisation 3D de jeux de données tridimensionnels\n\n• Le module Rendu volumique de Slicer permet la visualisation 3D interactive des images DICOM", + "27_TextBox_0": "Désactivez la visibilité des coupes axiale, sagittale et coronale dans le visionneur 2D\n\n\nPositionnez le ROI autour du rein gauche en utilisant les poignées de couleur", + "31_ArrowText_1": "Cliquez sur Fichier, puis sur Fermez la scène dans le menu principal", + "32_TextBox_0": "Partie 3 : Chargement et visualisation des modèles 3D\n", + "33_TextBox_1": "• Le répertoire dataset2_Head contient la scène Slicer appelée Head_scene.mrb\n\n• La scène contient des modèles 3D issus de l’atlas cérébral SPL développé par le département de radiologie du Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stocke toutes les données chargées dans un dépôt appelé scène.\n\n\nChaque jeu de données, comme un volume d’image, un modèle de surface ou un ensemble de points, est représenté par un nœud dans une scène Slicer.\n\n\nTous les modules de Slicer fonctionnent sur les données stockées dans une scène Slicer.", + "37_ArrowText_1": "Sélectionnez le module Modèles dans la liste des modèles", + "38_TextBox_1": "Les modèles du crâne et des yeux apparaissent à travers la peau", + "39_ArrowText_0": "Slicer affiche la liste des modèles 3D chargés dans la scène.\n\nSélectionnez le modèle Skin.vtk", + "40_TextBox_2": "Les modèles de la matière blanche et du nerf optique apparaissent à travers la peau", + "45_TextBox_1": "• 3D Slicer offre des fonctionnalités avancées pour le chargement et la visualisation de données d’imagerie médicale 3D.\n\n• Le tutoriel montre comment utiliser le rendu volumique et la modélisation de surface 3D pour la visualisation interactive des données CT et IRM.\n\n\nContact : spujol@bwh.harvard.edu", + "46_TextBox_1": "Neuroimage Analysis \nCenter \n(NIBIB P41 EB015902)", + "40_ArrowText_1": "Sélectionnez le modèle skull bone et cliquez sur l’icône Eye pour désactiver sa visibilité", + "9_ArrowText_1": "Sélectionnez patient1 et cliquez sur Chargez pour charger le jeu de données dans Slicer", + "10_TextBox_0": "Slicer affiche les images axiale, coronale et sagittale du jeu de données CT Thorax Abdomen. ", + "20_ArrowText_1": "Sélectionnez le module Rendu volumique dans la liste des modules. ", + "23_ArrowText_0": "Cliquez sur Préréglage dans l’onglet Display et sélectionnez le préréglage CT-Cardiac3 ", + "41_ArrowText_0": "Cliquez sur l’icône Eye pour afficher la coupe coronale dans la visionneuse 3D", + "42_ArrowText_2": "Sélectionnez le modèle hemispheric white matter et activez l’option Clipping", + "43_TextBox_0": "Déplacez la coupe coronale vers l’arrière pour afficher le chiasma optique", + "44_TextBox_0": "Slicer affiche une vue 3D du chiasma optique", + "46_TextBox_0": "Remerciements", + "45_TextBox_0": "Conclusion", + "49_TextBox_1": "*3D Slicer offre des fonctionnalités avancées pour le chargement et la visualisation des données d’imagerie médicale 3D\n\n*Le tutoriel montre comment utiliser le rendu volumique et la modélisation de surfaces 3D pour la visualisation interactive des données CT et IRM\n\nContact : spujol@bwh.harvard.edu" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..d17023df --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json @@ -0,0 +1,99 @@ +{ + "0_TextBox_0": "Noções básicas de carregamento de dados e visualização 3D no 3D Slicer", + "0_TextBox_1": "Autor: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Professora Assistente de Radiologia Brigham e Escola Médica de Harvard do Hospital das Mulheres", + "1_TextBox_0": "Objetivo geral", + "1_TextBox_1": "Este tutorial é uma introdução aos conceitos básicos de carregamento e visualização de imagens DICOM e modelos 3D no 3D Slicer.", + "2_TextBox_0": "Objectivos de aprendizagem", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_0": "Materiais do tutorial", + "3_TextBox_1": "-3D Slicer versão 5.10\n\n-3D VisualizationDataSet.zip", + "4_TextBox_0": "Tutorial dataset", + "4_TextBox_1": "O arquivo 3DVisualizationDataset.zip contém\ndois diretórios:\n-dataset1_Thorax_Abdomen\n-dataset2_Head\n\nDescompactar o arquivo 3DVisualizationDataset.zip em\nseu computador para acessar os conjuntos de dados", + "5_TextBox_0": "Isenção de responsabilidade", + "5_TextBox_1": "• O 3D Slicer é um software de código aberto gratuito distribuído sob uma licença no estilo BSD.\n• O software não possui aprovação da FDA nem marcação CE, e é apenas para uso em pesquisa.", + "6_TextBox_0": "Resumo do tutorial", + "6_TextBox_1": "Parte 1: Carregando e visualizando dados DICOM\n\nParte 2: Renderização de volume\n\nParte 3: Carregando e visualizando modelos 3D", + "7_TextBox_0": "Parte 1: Carregamento de Dados DICOM", + "8_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "8_TextBox_1": "O estudo do paciente 1 contém um conjunto de dados de tomografia computadorizada de tórax e abdome", + "9_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_VisualizingDICOMimages_title": "Visualizing DICOM images", + "10_TextBox_0": "Slicer exibe o axial, coronal\ne imagens sagitais da TC\nConjunto de dados Thorax Abdomen ", + "11_VisualizingDICOMimages_title": "Visualizing DICOM images", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "11_ArrowText_2": "Select the module \nVolumes", + "12_VisualizingDICOMimages_title": "Visualizing DICOM images", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_VisualizingDICOMimages_title": "Visualizing DICOM images", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_VisualizingDICOMimages_title": "Visualizing DICOM images", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "15_VisualizingDICOMimages_title": "Visualizing DICOM images", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "16_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_TextBox_0": "O fatiador alterna o layout\npara Convencional\nLayout de tela ampla", + "17_VisualizingDICOMimages_title": "Visualizing DICOM images", + "17_TextBox_0": "Use o botão direito do mouse no\nVisualizador 3D para aumentar e diminuir o zoom", + "18_VisualizingDICOMimages_title": "Visualizing DICOM images", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_3DViewerController_title": "3D Viewer Controller", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_3DViewerController_title": "3D Viewer Controller", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_0": "Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_VolumeRendering_title": "Volume Rendering", + "23_ArrowText_0": "Clique em Predefinição na guia Exibir\ne selecione a predefinição CT-Cardiac3 ", + "24_VolumeRendering_title": "Volume Rendering", + "24_TextBox_2": "Select VTK GPU Ray Casting Rendering\nClick on the eye icon in the Volume tab to display \nthe volume rendered image in the 3D viewer", + "25_VolumeRendering_title": "Volume Rendering", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "26_VolumeRendering_title": "Volume Rendering", + "26_ArrowText_0": "Clique em Exibir ROI para\nmostrar uma região de interesse\n(ROI) no visualizador 3D e\nverificar a opção Habilitar", + "27_VolumeRendering_title": "Volume Rendering", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "28_VolumeRendering_title": "Volume Rendering", + "28_ArrowText_0": "Clique no ícone do olho para\nexibir o volume renderizado\nimagem", + "29_VolumeRendering_title": "Volume Rendering", + "29_TextBox_0": "Slicer displays the \nvolume rendered \nimage of the left kidney ", + "30_VolumeRendering_title": "Volume Rendering", + "30_TextBox_0": "Amplie a ROI para gerar\numa imagem renderizada em volume do\nrim direito", + "31_VolumeRendering_title": "Volume Rendering", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_0": "Conjunto de dados do tutorial", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_0": "Cena do Slicer", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "35_LoadingaScene_title": "Carregando uma cena", + "35_TextBox_0": "O Slicer exibe um modelo de \nsuperfície 3D da cabeça e cortes \nde ressonância magnética 2D", + "36_Viewing3Dmodels_title": "Viewing 3D models", + "36_ArrowText_0": "Posicione o cursor sobre\no ícone do pino para revelar o\nmenu de fatias e clique em\no ícone do olho para exibir\nfatia axial no espectador 3D", + "37_Viewing3Dmodels_title": "Viewing 3D models", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "38_Viewing3Dmodels_title": "Viewing 3D models", + "38_ArrowText_0": "Lower the opacity of \nthe Skin model using \nthe visibility slider", + "38_TextBox_1": "The skull bone and \neyeballs models appear \nthrough the skin", + "39_Viewing3Dmodels_title": "Viewing 3D models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "40_Viewing3Dmodels_title": "Viewing 3D models", + "40_ArrowText_1": "Select the skull bone \nmodel and click on the \neye icon to turn off its \nvisibility", + "40_TextBox_2": "The white matter and \noptic nerve models \nappear through the skin", + "41_Interactingwith3Dmodels_title": "Interacting with 3D models", + "41_ArrowText_0": "Clique no ícone do olho para\nexibir o corte coronal\nno visualizador 3D", + "42_Interactingwith3Dmodels_title": "Interacting with 3D models", + "42_ArrowText_2": "Select the hemispheric \nwhite matter model and \nselect the option Clipping", + "43_Interactingwith3Dmodels_title": "Interacting with 3D models", + "43_TextBox_0": "Mova a fatia coronal\nposteriormente para exibir o\nquiasma óptico", + "44_Interactingwith3Dmodels_title": "Interacting with 3D models", + "44_TextBox_0": "O Slicer exibe uma visualização 3D do\nquiasma óptico", + "45_TextBox_0": "Conclusão", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Agradecimentos", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt_PT.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt_PT.json new file mode 100644 index 00000000..0cf90953 --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt_PT.json @@ -0,0 +1,99 @@ +{ + "1_TextBox_1": "Este tutorial é uma introdução aos conceitos básicos de carregamento e visualização de imagens DICOM e modelos 3D no 3D Slicer.", + "3_TextBox_0": "Materiais do tutorial", + "4_TextBox_0": "Conjunto de dados do tutorial", + "33_TextBox_0": "Conjunto de dados do tutorial", + "5_TextBox_0": "Isenção de responsabilidade", + "6_TextBox_0": "Resumo do tutorial", + "8_LoadingaDICOMvolume_title": "A carregar um volume DICOM", + "9_LoadingaDICOMvolume_title": "A carregar um volume DICOM", + "8_TextBox_1": "O estudo do utente 1 contém um conjunto de dados de tomografia computadorizada de tórax e abdome", + "11_ArrowText_2": "Selecione o módulo\nVolumes", + "10_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "11_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "12_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "13_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "14_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "15_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "16_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "17_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "18_VisualizingDICOMimages_title": "A visualizar imagens DICOM", + "16_TextBox_0": "O fatiador alterna o layout\npara Convencional\nLayout de ecrã amplo", + "17_TextBox_0": "Use o botão direito do rato no\nVisualizador 3D para aumentar e diminuir o zoom", + "19_3DViewerController_title": "Controlador de visualização 3D", + "20_3DViewerController_title": "Controlador de visualização 3D", + "22_TextBox_0": "Renderização de volume", + "23_VolumeRendering_title": "Renderização de volume", + "24_VolumeRendering_title": "Renderização de volume", + "25_VolumeRendering_title": "Renderização de volume", + "26_VolumeRendering_title": "Renderização de volume", + "27_VolumeRendering_title": "Renderização de volume", + "28_VolumeRendering_title": "Renderização de volume", + "29_VolumeRendering_title": "Renderização de volume", + "30_VolumeRendering_title": "Renderização de volume", + "31_VolumeRendering_title": "Renderização de volume", + "24_TextBox_2": "Select VTK GPU Ray Casting Rendering\nClick on the eye icon in the Volume tab to display \nthe volume rendered image in the 3D viewer", + "26_ArrowText_0": "Clique em Exibir ROI para\nmostrar uma região de interesse\n(ROI) no visualizador 3D e\nverificar a opção Ativar", + "28_ArrowText_0": "Clique no ícone do olho para\nexibir o volume renderizado\nimagem", + "29_TextBox_0": "Slicer displays the \nvolume rendered \nimage of the left kidney ", + "30_TextBox_0": "Amplie a ROI para gerar\numa imagem renderizada em volume do\nrim direito", + "34_TextBox_0": "Cena do Slicer", + "35_LoadingaScene_title": "A carregar uma cena", + "35_TextBox_0": "O Slicer exibe um modelo de \nsuperfície 3D da cabeça e cortes \nde ressonância magnética 2D", + "36_Viewing3Dmodels_title": "A visualizar modelos 3D", + "37_Viewing3Dmodels_title": "A visualizar modelos 3D", + "38_Viewing3Dmodels_title": "A visualizar modelos 3D", + "39_Viewing3Dmodels_title": "A visualizar modelos 3D", + "40_Viewing3Dmodels_title": "A visualizar modelos 3D", + "36_ArrowText_0": "Posicione o cursor sobre\no ícone do pino para revelar o\nmenu de fatias e clique em\no ícone do olho para exibir\nfatia axial no espectador 3D", + "41_Interactingwith3Dmodels_title": "Interagir com modelos 3D", + "42_Interactingwith3Dmodels_title": "Interagir com modelos 3D", + "43_Interactingwith3Dmodels_title": "Interagir com modelos 3D", + "44_Interactingwith3Dmodels_title": "Interagir com modelos 3D", + "38_ArrowText_0": "Lower the opacity of \nthe Skin model using \nthe visibility slider", + "38_TextBox_1": "The skull bone and \neyeballs models appear \nthrough the skin", + "40_TextBox_2": "The white matter and \noptic nerve models \nappear through the skin", + "40_ArrowText_1": "Select the skull bone \nmodel and click on the \neye icon to turn off its \nvisibility", + "0_TextBox_0": "Noções básicas de carregamento de dados e visualização 3D no 3D Slicer", + "0_TextBox_1": "Autor: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Professora Assistente de Radiologia Brigham e Escola Médica de Harvard do Hospital das Mulheres", + "1_TextBox_0": "Objetivo geral", + "2_TextBox_0": "Objetivos de aprendizagem", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_1": "-3D Slicer versão 5.10\n\n-3D VisualizationDataSet.zip", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Parte 1: Carregar Dados DICOM", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_TextBox_0": "Slicer exibe o axial, coronal\ne imagens sagitais da TC\nConjunto de dados Thorax Abdomen ", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_ArrowText_0": "Clique em Predefinição na guia Exibir\ne selecione a predefinição CT-Cardiac3 ", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "41_ArrowText_0": "Clique no ícone do olho para\nexibir o corte coronal\nno visualizador 3D", + "42_ArrowText_2": "Select the hemispheric \nwhite matter model and \nselect the option Clipping", + "43_TextBox_0": "Mova a fatia coronal\nposteriormente para exibir o\nquiasma ótico", + "44_TextBox_0": "O Slicer exibe uma visualização 3D do\nquiasma ótico", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Agradecimentos", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)", + "45_TextBox_0": "Conclusão" +} \ No newline at end of file