A Probabilistic U-Net for Segmentation of Ambiguous Images

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), pp. 6965-6975, 2018.

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a setct scanhigh impactas wellvision problems

Abstract:

Many real-world vision problems suffer from inherent ambiguities. In clinical applications for example, it might not be clear from a CT scan alone which particular region is cancer tissue. Therefore a group of graders typically produces a set of diverse but plausible segmentations. We consider the task of learning a distribution over segm...More

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