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Explainable Semantic Medical Image Segmentation with Style
The discriminator is generalised to small domain shifts as much as permissible by the training data, and the generator automatically diversifies the training samples using a manifold of input features learnt during segmentation.
CAN3D: Fast 3D Medical Image Segmentation via Compact Context Aggregation
Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large volume under investigation.
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