A study of criteria for grading follicular lymphoma using a cell type classifier from pathology images based on complementary-label learning

We propose a criterion for grading follicular lymphoma that is consistent with the intuitive evaluation, which is conducted by experienced pathologists. A criterion for grading follicular lymphoma is defined by the World Health Organization (WHO) based on the number of centroblasts and centrocytes w...

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Veröffentlicht in:	Micron (Oxford, England : 1993) England : 1993), 2024-09, Vol.184, p.103663, Article 103663
Hauptverfasser:	Koga, Ryoichi, Koide, Shingo, Tanaka, Hiromu, Taguchi, Kei, Kugler, Mauricio, Yokota, Tatsuya, Ohshima, Koichi, Miyoshi, Hiroaki, Nagaishi, Miharu, Hashimoto, Noriaki, Takeuchi, Ichiro, Hontani, Hidekata
Format:	Artikel
Sprache:	eng
Schlagworte:	Cancer Cancer grading Classification Complementary-label learning Computer Science Digital pathology Humans Image Processing, Computer-Assisted - methods Life Sciences Lymphoma, Follicular - classification Lymphoma, Follicular - pathology Machine Learning Malignant lymphoma Medical Imaging Neoplasm Grading - methods
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