A fully convolutional neural network modified from the U-Net architecture was used to segment WMH on the FLAIR images. Next, another network was trained to segment the white matter from T1 images, and the segmented white matter mask is applied to remove false positives from the WMH segmentation results. The original U-Net architecture was trimmed to keep only three pooling layers.

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An updated submission is available: nih_cidi 2.