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CONVOLUITIONAL NEURAL NETWORKS FOR MS LESION SEGMENTATION , METHOD DESCRIPTION OF DIAG TEAM

Recently deep neural networks have shown many successful applications in different domains. For this lesion segmentation task, we utilize a deep convolutional neural network with 5 layers in a sliding window fashion to create a voxel-based classifier. We evaluate our system with Dice similarity, misclassification rate and area under the ROC curve. Based on experimental results our proposed CAD system reaches average Dice similarity, misclassification rate and area under the ROC curve of 0.976, 0.565, 0.073 respectively.