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Learning To Focus: Anatomy-Guided Attention Regularization for Medical Image Classification
Medical image classification models are ideally expected to identify diagnostically relevant regions while making predictions, yet standard classification losses rarely provide spatial supervision. Explicit supervision via anatomical shape information, such as segmentation masks of task-relevant ana
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