PC-MIL shows that anchoring supervision at a 2 mm scale and progressively mixing slide- and region-level labels improves cross-context accuracy in WSI cancer detection without reducing global performance.
Advances in neural information processing systems34, 2136–2147 (2021)
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PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning
PC-MIL shows that anchoring supervision at a 2 mm scale and progressively mixing slide- and region-level labels improves cross-context accuracy in WSI cancer detection without reducing global performance.