Leveraging commonality across multiple tissue slices for enhanced whole slide image classification using graph convolutional networks

Leveraging commonality across multiple tissue slices for enhanced whole slide image classification using graph convolutional networks

Abstract Background Accurate classification of histopathological whole slide images (WSIs) is essential for cancer diagnosis and treatment planning. Conventional WSI creation involves slicing a biopsy tissue into multiple slices, placing them on a single glass slide, and digitally scanning them. Whi...

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Bibliographic Details
Main Authors: Sakonporn Noree, Willmer Rafell Quinones Robles, Young Sin Ko, Mun Yong Yi
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Imaging
Subjects:
Whole slide image classification
Graph-based classification
Commonality
Deep learning
Histopathology
Online Access:https://doi.org/10.1186/s12880-025-01760-8
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