Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier Is All You Need
Weakly supervised whole slide image classification is usually formulated as a multiple instance learning (MIL) problem, where each slide is treated as a bag, and the patches cut out of it are treated as instances. Existing methods either train an instance classifier through pseudo-labeling or aggreg...
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Veröffentlicht in: | IEEE transactions on circuits and systems for video technology 2024-10, Vol.34 (10), p.9732-9744 |
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