Feb. 7, 2024, 5:47 a.m. | Ali Khajegili Mirabadi Graham Archibald Amirali Darbandsari Alberto Contreras-Sanz Ramin Ebrahim Nakhli Maryam

cs.CV updates on arXiv.org arxiv.org

Cancer subtyping is one of the most challenging tasks in digital pathology, where Multiple Instance Learning (MIL) by processing gigapixel whole slide images (WSIs) has been in the spotlight of recent research. However, MIL approaches do not take advantage of inter- and intra-magnification information contained in WSIs. In this work, we present GRASP, a novel graph-structured multi-magnification framework for processing WSIs in digital pathology. Our approach is designed to dynamically emulate the pathologist's behavior in handling WSIs and benefits from …

cancer cs.cv digital graph image images information instance in the spotlight mil multiple pathology processing representation research spotlight tasks work

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