Review on Applications of Deep Learning in Digital Pathological Images.
10.12455/j.issn.1671-7104.240499
- Author:
Chaoyi LYU
1
;
Yuan XIE
1
;
Lu QIU
1
;
Lu ZHAO
1
;
Jun ZHAO
1
Author Information
1. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai,
- Publication Type:English Abstract
- Keywords:
cancer diagnosis;
cancer prognostic prediction;
deep learning;
histopathology;
pathological image segmentation
- MeSH:
Deep Learning;
Humans;
Image Processing, Computer-Assisted/methods*;
Artificial Intelligence;
Neoplasms
- From:
Chinese Journal of Medical Instrumentation
2025;49(3):237-243
- CountryChina
- Language:Chinese
-
Abstract:
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.
