Feature Re-calibration based MIL for Whole Slide Image Classification. (arXiv:2206.10878v1 [cs.CV])

Whole slide image (WSI) classification is a fundamental task for the
diagnosis and treatment of diseases; but, curation of accurate labels is
time-consuming and limits the application of fully-supervised methods. To
address this, multiple instance learning (MIL) is a popular method that poses
classification as a weakly supervised learning task with slide-level labels
only. While current MIL methods apply variants of the attention mechanism to
re-weight instance features with stronger models, scant attention is paid to
the properties of the …

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