A cluster attention-based multiple instance learning network for enhancing histopathological image interpretation

Histopathological diagnosis involves examining abnormal architectural patterns and cellular-level changes. Whole slide images (WSIs) provide comprehensive digital representations of tissue samples, enabling detailed analysis and interpretation. Annotating the giga-pixel images remains labor-intensiv...

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Veröffentlicht in:	Computers in biology and medicine Jg. 193; S. 110353
Hauptverfasser:	Ko, Seokhwan, Ando, Yu, Kim, Moonsik, Park, Nora Jee-Young, Han, Hyungsoo, Park, Ji Young, Cho, Junghwan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.07.2025
Schlagworte:	Cluster Analysis Clustering Deep learning Histopathology Humans Image Interpretation, Computer-Assisted - methods Internal Medicine Machine Learning Multiple instance learning Multiple-Instance Learning Algorithms Neoplasms - diagnostic imaging Neoplasms - pathology Other Weakly-supervised learning Deep learning Histopathology Weakly-supervised learning Clustering Multiple instance learning
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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