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The Liver Tumor Segmentation Benchmark (LiTS)., , , , , , , , , and 49 other author(s). CoRR, (2019)Diabetes60 - Inferring Bread Units From Food Images Using Fully Convolutional Neural Networks., , , , , , , , and . ICCV Workshops, page 1526-1535. IEEE Computer Society, (2017)A large annotated medical image dataset for the development and evaluation of segmentation algorithms., , , , , , , , , and 14 other author(s). CoRR, (2019)Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields., , , , , , , , , and 3 other author(s). MICCAI (2), volume 9901 of Lecture Notes in Computer Science, page 415-423. (2016)The Medical Segmentation Decathlon., , , , , , , , , and 48 other author(s). CoRR, (2021)Automated Unsupervised Segmentation of Liver Lesions in CT scans via Cahn-Hilliard Phase Separation., , , , and . CoRR, (2017)Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks., , , , , , , , , and 10 other author(s). CoRR, (2017)MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision., , , , , , , , , and 39 other author(s). CoRR, (2023)Convolutional Neural Networks for Classification and Segmentation of Medical Images (Convolutional Neural Networks zur Klassifizierung und Segmentierung von medizinischen Bilddaten). Technical University of Munich, Germany, (2017)SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D Convolutional Neural Networks., , , , , , , , , and . ISBI, page 839-843. IEEE, (2017)