Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks

4 Apr 2019Richard McKinleyMichael RebsamenRaphael MeierMauricio ReyesChristian RummelRoland Wiest

In applications of supervised learning applied to medical image segmentation, the need for large amounts of labeled data typically goes unquestioned. In particular, in the case of brain anatomy segmentation, hundreds or thousands of weakly-labeled volumes are often used as training data... (read more)

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