CAMEL enriches image-level histopathology labels into approximate pixel labels via MIL-based instance selection, and achieves segmentation performance near fully supervised baselines.
Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation
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CAMEL: A Weakly Supervised Learning Framework for Histopathology Image Segmentation
CAMEL enriches image-level histopathology labels into approximate pixel labels via MIL-based instance selection, and achieves segmentation performance near fully supervised baselines.