Segment3DBrainTumorUsingDeepLearningExample/unet_2d.m at master · ImageGuidedTherapyLab/Segment3DBrainTumorUsingDeepLearningExample · GitHub

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%define n as number of channels
n = 1;
lgraph = layerGraph();
%% Add Layer Branches
% Add the branches of the network to the layer graph. Each branch is a linear
% array of layers.

tempLayers = [
    imageInputLayer([64 64 n],"Name","input","Normalization","none")
    batchNormalizationLayer("Name","BN_Module1_Level1")
    convolution2dLayer([3 3],32,"Name","conv_Module1_Level1","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module1_Level1")
    batchNormalizationLayer("Name","BN_Module1_Level2")
    convolution2dLayer([3 3],64,"Name","conv_Module1_Level2","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module1_Level2")];
lgraph = addLayers(lgraph,tempLayers);

tempLayers = [
    maxPooling2dLayer([2 2],"Name","maxpool_Module1","Padding","same","Stride",[2 2])
    batchNormalizationLayer("Name","BN_Module2_Level1")
    convolution2dLayer([3 3],64,"Name","conv_Module2_Level1","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module2_Level1")
    batchNormalizationLayer("Name","BN_Module2_Level2")
    convolution2dLayer([3 3],128,"Name","conv_Module2_Level2","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module2_Level2")];
lgraph = addLayers(lgraph,tempLayers);

tempLayers = [
    maxPooling2dLayer([2 2],"Name","maxpool_Module2","Padding","same","Stride",[2 2])
    batchNormalizationLayer("Name","BN_Module3_Level1")
    convolution2dLayer([3 3],128,"Name","conv_Module3_Level1","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module3_Level1")
    batchNormalizationLayer("Name","BN_Module3_Level2")
    convolution2dLayer([3 3],256,"Name","conv_Module3_Level2","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module3_Level2")];
lgraph = addLayers(lgraph,tempLayers);

tempLayers = [
    maxPooling2dLayer([2 2],"Name","maxpool_Module3","Padding","same","Stride",[2 2])
    batchNormalizationLayer("Name","BN_Module4_Level1")
    convolution2dLayer([3 3],256,"Name","conv_Module4_Level1","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module4_Level1")
    batchNormalizationLayer("Name","BN_Module4_Level2")
    convolution2dLayer([3 3],512,"Name","conv_Module4_Level2","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module4_Level2")
    upsample2dLayer([2 2],512,"Name","upsample_Module4","Stride",[2 2])];
lgraph = addLayers(lgraph,tempLayers);

tempLayers = [
    concatenationLayer(3,2,"Name","concat3")
    batchNormalizationLayer("Name","BN_Module5_Level1")
    convolution2dLayer([3 3],256,"Name","conv_Module5_Level1","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module5_Level1")
    batchNormalizationLayer("Name","BN_Module5_Level2")
    convolution2dLayer([3 3],256,"Name","conv_Module5_Level2","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module5_Level2")
    upsample2dLayer([2 2],256,"Name","upsample_Module5","Stride",[2 2])];
lgraph = addLayers(lgraph,tempLayers);

tempLayers = [
    concatenationLayer(3,2,"Name","concat2")
    batchNormalizationLayer("Name","BN_Module6_Level1")
    convolution2dLayer([3 3],128,"Name","conv_Module6_Level1","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module6_Level1")
    batchNormalizationLayer("Name","BN_Module6_Level2")
    convolution2dLayer([3 3],128,"Name","conv_Module6_Level2","Padding","same","WeightsInitializer","narrow-normal")
    reluLayer("Name","relu_Module6_Level2")
    upsample2dLayer([2 2],128,"Name","upsample_Module6","Stride",[2 2])];
lgraph = addLayers(lgraph,tempLayers);

tempLayers = [
    concatenationLayer(3,2,"Name","concat1")
    batchNormalizationLayer("Name","BN_Module7_Level1")
    convolution2dLayer([3 3],64,"Name","conv_Module7_Level1","Padding","same")
    reluLayer("Name","relu_Module7_Level1")
    batchNormalizationLayer("Name","BN_Module7_Level2")
    convolution2dLayer([3 3],64,"Name","conv_Module7_Level2","Padding","same")
    reluLayer("Name","relu_Module7_Level2")
    batchNormalizationLayer("Name","BN_Module7_Level3")
    convolution2dLayer([1 1],2,"Name","ConvLast_Module7")
    softmaxLayer("Name","softmax")
    dicePixelClassificationLayer("Name","output")];
lgraph = addLayers(lgraph,tempLayers);

% clean up helper variable
clear tempLayers;
%% Connect Layer Branches
% Connect all the branches of the network to create the network graph.

lgraph = connectLayers(lgraph,"relu_Module1_Level2","maxpool_Module1");
lgraph = connectLayers(lgraph,"relu_Module1_Level2","concat1/in2");
lgraph = connectLayers(lgraph,"relu_Module2_Level2","maxpool_Module2");
lgraph = connectLayers(lgraph,"relu_Module2_Level2","concat2/in2");
lgraph = connectLayers(lgraph,"relu_Module3_Level2","maxpool_Module3");
lgraph = connectLayers(lgraph,"relu_Module3_Level2","concat3/in2");
lgraph = connectLayers(lgraph,"upsample_Module4","concat3/in1");
lgraph = connectLayers(lgraph,"upsample_Module5","concat2/in1");
lgraph = connectLayers(lgraph,"upsample_Module6","concat1/in1");
%% Plot Layers

plot(lgraph);