Multiplex-detection Based Multiple Instance Learning Network for Whole Slide Image Classification. (arXiv:2208.03526v3 [cs.CV] UPDATED)

Multiple instance learning (MIL) is a powerful approach to classify whole
slide images (WSIs) for diagnostic pathology. A fundamental challenge of MIL on
WSI classification is to discover the \textit{critical instances} that trigger
the bag label. However, previous methods are primarily designed under the
independent and identical distribution hypothesis (\textit{i.i.d}), ignoring
either the correlations between instances or heterogeneity of tumours. In this
paper, we propose a novel multiplex-detection-based multiple instance learning
(MDMIL) to tackle the issues above. Specifically, MDMIL is …

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