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Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning. (arXiv:2107.03602v3 [cs.CV] UPDATED)
Sept. 23, 2022, 1:15 a.m. | Noriaki Hashimoto, Yusuke Takagi, Hiroki Masuda, Hiroaki Miyoshi, Kei Kohno, Miharu Nagaishi, Kensaku Sato, Mai Takeuchi, Takuya Furuta, Keisuke Kawam
cs.CV updates on arXiv.org arxiv.org
In the present study, we propose a novel case-based similar image retrieval
(SIR) method for hematoxylin and eosin (H&E)-stained histopathological images
of malignant lymphoma. When a whole slide image (WSI) is used as an input
query, it is desirable to be able to retrieve similar cases by focusing on
image patches in pathologically important regions such as tumor cells. To
address this problem, we employ attention-based multiple instance learning,
which enables us to focus on tumor-specific regions when the similarity …
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