MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology

arXiv:2403.06800v1 Announce Type: new
Abstract: Multiple Instance Learning (MIL) has emerged as a dominant paradigm to extract discriminative feature representations within Whole Slide Images (WSIs) in computational pathology. Despite driving notable progress, existing MIL approaches suffer from limitations in facilitating comprehensive and efficient interactions among instances, as well as challenges related to time-consuming computations and overfitting. In this paper, we incorporate the Selective Scan Space State Sequential Model (Mamba) in Multiple Instance Learning (MIL) for long sequence modeling with linear …

arxiv computational cs.cv modeling pathology type