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Found 2 papers, 1 papers with code
Marginal loss and exclusion loss for partially supervised multi-organ segmentation
Annotating multiple organs in medical images is both costly and time-consuming; therefore, existing multi-organ datasets with labels are often low in sample size and mostly partially labeled, that is, a dataset has a few organs labeled but not all organs.
Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition
We hereby propose a decomposition generative adversarial network (DecGAN) to anatomically decompose a CXR image but with unpaired data.
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