Review on Applications of Deep Learning in Digital Pathological Images

Computer-assisted methods for pathological image analysis can improve doctor's efficiency of image reading and diagnostic accuracy, effectively addressing the shortage of pathology diagnostic manpower. With the rapid development of artificial intelligence and digital pathology, deep learning te...

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Bibliographic Details
Main Authors: Chaoyi LYU, Yuan XIE, Lu QIU, Lu ZHAO, Jun ZHAO
Format: Article
Language:zho
Published: Editorial Office of Chinese Journal of Medical Instrumentation 2025-05-01
Series:Zhongguo yiliao qixie zazhi
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Online Access:https://zgylqxzz.xml-journal.net/article/doi/10.12455/j.issn.1671-7104.240499
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Summary:Computer-assisted methods for pathological image analysis can improve doctor's efficiency of image reading and diagnostic accuracy, effectively addressing the shortage of pathology diagnostic manpower. With the rapid development of artificial intelligence and digital pathology, deep learning technology has spurred a wealth of research in the field of histopathology. This article reviews the various applications of deep learning in digital pathological image analysis, such as pathological image segmentation, cancer auxiliary diagnosis, and cancer prognosis prediction, and discusses the challenges and solutions in its application. Furthermore, it predicts future trends in deep learning for pathological image analysis and proposes potential research directions.
ISSN:1671-7104