Multi-scale multi-instance contrastive learning for whole slide image classification

Author:

Zhang Jianan,Hao Fang,Liu Xueyu,Yao Shupei,Wu YongfeiORCID,Li Ming,Zheng Wen

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanxi Province

Publisher

Elsevier BV

Reference52 articles.

1. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images;Campanella;Nat. Med.,2019

2. Chen, T., Kornblith, S., Norouzi, M., Hinton, G., 2020. A simple framework for contrastive learning of visual representations. In: 2020 International Conference on Machine Learning. ICML, pp. 1597–1607.

3. Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis;Cheplygina;Med. Image Anal.,2019

4. Explicit metric-based multiconcept multi-instance learning with triplet and superbag;Chi;IEEE Trans. Neural Netw. Learn. Syst.,2022

5. Self supervised contrastive learning for digital histopathology;Ciga;Mach. Learn. Appl.,2022

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