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18 changes: 11 additions & 7 deletions README.md
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Expand Up @@ -113,7 +113,7 @@ These are examples of how DeepTrack2 can be used on real datasets:

Training a fully connected neural network to identify handwritten digits using MNIST dataset.

- DTEx212 **Single Particle Tracking** <!-- **[Single Particle Tracking](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx212 **[Single Particle Tracking](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Tracks experimental videos of a single particle.

Expand All @@ -134,7 +134,7 @@ These are examples of how DeepTrack2 can be used on real datasets:
</p>
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- DTEx213 **Multi-Particle Tracking** <!-- **[Multi-Particle Tracking](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx213_multi_particle_tracking.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx213_multi_particle_tracking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx213 **[Multi-Particle Tracking](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx213_multi_particle_tracking.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx213_multi_particle_tracking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Detecting quantum dots in a low SNR image.

Expand All @@ -150,7 +150,7 @@ These are examples of how DeepTrack2 can be used on real datasets:

Extracting the radius and refractive index of particles.

- DTEx215 **Cell Counting** <!-- **[Cell Counting](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx215_cell_counting.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx215_cell_counting.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx215 **[Cell Counting](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx215_cell_counting.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx215_cell_counting.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Counting the number of cells in fluorescence images.

Expand All @@ -164,7 +164,7 @@ These are examples of how DeepTrack2 can be used on real datasets:

Specific examples for label-free particle tracking using **LodeSTAR**:

- DTEx231A **LodeSTAR to Detect Particles** <!-- **[LodeSTAR to Detect Particles](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231A_LodeSTAR_template.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231A_LodeSTAR_template.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx231A **[LodeSTAR to Detect Particles](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231A_LodeSTAR_template.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231A_LodeSTAR_template.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

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Expand All @@ -183,11 +183,11 @@ Specific examples for label-free particle tracking using **LodeSTAR**:

- DTEx231C **LodeSTAR to Measure the Mass of Particles in Holography**

- DTEx231D **LodeSTAR to Detect the Cells in the BF-C2DT-HSC Dataset** <!-- **[LodeSTAR to Detect the Cells in the BF-C2DT-HSC Dataset](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231D_LodeSTAR_track_BF-C2DL-HSC.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231D_LodeSTAR_track_BF-C2DL-HSC.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx231D **[LodeSTAR to Detect the Cells in the BF-C2DT-HSC Dataset](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231D_LodeSTAR_track_BF-C2DL-HSC.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231D_LodeSTAR_track_BF-C2DL-HSC.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTEx231E **LodeSTAR to Detect the Cells in the Fluo-C2DT-Huh7 Dataset** <!-- **[LodeSTAR to Detect the Cells in the Fluo-C2DT-Huh7 Dataset](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231E_LodeSTAR_track_Fluo-C2DL-Huh7.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231E_LodeSTAR_track_Fluo-C2DL-Huh7.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx231E **[LodeSTAR to Detect the Cells in the Fluo-C2DT-Huh7 Dataset](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231E_LodeSTAR_track_Fluo-C2DL-Huh7.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231E_LodeSTAR_track_Fluo-C2DL-Huh7.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTEx231F **LodeSTAR to Detect the Cells in the PhC-C2DT-PSC Dataset** <!-- **[LodeSTAR to Detect the Cells in the PhC-C2DT-PSC Dataset](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231F_LodeSTAR_track_PhC-C2DL-PSC.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231F_LodeSTAR_track_PhC-C2DL-PSC.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->
- DTEx231F **[LodeSTAR to Detect the Cells in the PhC-C2DT-PSC Dataset](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231F_LodeSTAR_track_PhC-C2DL-PSC.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231F_LodeSTAR_track_PhC-C2DL-PSC.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTEx231G **LodeSTAR to Detect Plankton** <!-- **[LodeSTAR to Detect Plankton](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231G_LodeSTAR_track_plankton.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231G_LodeSTAR_track_plankton.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a> -->

Expand Down Expand Up @@ -216,6 +216,10 @@ Specific examples for graph-neural-network-based particle linking and trace char

- DTEx241B **MAGIK to Track HeLa Cells**

- DTEx251 **[Neural tissue segmentation](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx251_neural_tissue_segmentation.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx251_neural_tissue_segmentation.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTEx252 **[Phase mask optimization](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx252_phase_mask_optimization.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx252_phase_mask_optimization.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

# Advanced Tutorials

This section provides a list of advanced tutorials. The primary focus of these tutorials is to demonstrate the functionalities of individual modules and how they work in relative isolation, helping to provide a better understanding of them and their roles in DeepTrack2.
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