We propose a semi-supervised training scheme for white matter hyperintensity (WMHs) segmentation using V-Net on FLAIR images. The training procedure does not require manual labeling data but only a few domain knowledge of WMHs. The segmentation result obtained by the V-Net with the proposed scheme outperformed that obtained by the supervised loss with manual labels, showing great potential and generalizability in medical image applications.
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