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U-Net: Convolutional Networks for BiomedicalImage SegmentationOlaf Ronneberger, Philipp Fischer, and Thomas BroxComputer Science Department and BIOSS Centre for Biological Signalling Studies,University of Freiburg, home page: is large consent that successful training of deep net-works requires many thousand annotated training samples. In this pa-per, we present a network and training strategy that relies on the stronguse of data augmentation to use the available annotated samples moreefficiently. The architecture consists of a contracting path to capturecontext and a symmetric expanding path that enables precise localiza-tion.
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger, Philipp Fischer, and Thomas Brox Computer Science Department and BIOSS Centre for Biological Signalling Studies,
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