When multiple instance learning meets foundation models: Advancing histological whole slide image analysis

Deep multiple instance learning (MIL) pipelines are the mainstream weakly supervised learning methodologies for whole slide image (WSI) classification. However, it remains unclear how these widely used approaches compare to each other, given the recent proliferation of foundation models (FMs) for pa...

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Bibliographic Details
Published in:	Medical image analysis Vol. 101; p. 103456
Main Authors:	Xu, Hongming, Wang, Mingkang, Shi, Duanbo, Qin, Huamin, Zhang, Yunpeng, Liu, Zaiyi, Madabhushi, Anant, Gao, Peng, Cong, Fengyu, Lu, Cheng
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.04.2025
Subjects:	Cancer diagnosis Computational pathology Deep Learning Foundation models Histological classification Humans Image Interpretation, Computer-Assisted - methods Image Processing, Computer-Assisted - methods Multiple instance learning Multiple-Instance Learning Algorithms Neoplasm Grading Neoplasms - diagnostic imaging Neoplasms - pathology Foundation models Cancer diagnosis Multiple instance learning Computational pathology Histological classification
ISSN:	1361-8415, 1361-8423, 1361-8423
Online Access:	Get full text
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