Pathology report generation from whole slide images with knowledge retrieval and multi-level regional feature selection-Reference-Cited by-同舟云学术

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Pathology report generation from whole slide images with knowledge retrieval and multi-level regional feature selection

Published:2025-05 Issue: Volume:263 Page:108677
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Hu Dingyi,Jiang Zhiguo,Shi Jun,Xie Fengying,Wu Kun,Tang Kunming,Cao Ming,Huai Jianguo,Zheng Yushan^ORCID

Funder

Fundamental Research Funds for the Central Universities

Beijing Natural Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference43 articles.

1. A visual–language foundation model for pathology image analysis using medical twitter;Huang;Nature Med.,2023

2. A novel dataset and efficient deep learning framework for automated grading of renal cell carcinoma from kidney histopathology images;Chanchal;Sci. Rep.,2023

3. Positional encoding-guided transformer-based multiple instance learning for histopathology whole slide images classification;Shi;Comput. Methods Programs Biomed.,2025

4. Deep learning–based segmentation and quantification in experimental kidney histopathology;Bouteldja;J. Am. Soc. Nephrol.,2021

5. Restaining-based annotation for cancer histology segmentation to overcome annotation-related limitations among pathologists;Komura;Patterns,2023

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