A 10-layer 3D convolutional neural network architecture previously used to segment multiple sclerosis lesions. A cascaded training procedure was employed, training two separate networks to first identify candidate lesion voxels and next to reduce false positive detections. A third network re-trains the last fully connected layer to perform WMH segmentation.Presentation of this method.
Full description of this method.
Docker container of this method.