Construction of An Automated Segmentation Visual Foundation Model for Pathological Images of Hemorrhoids and Its Application in Traditional Chinese Medicine Clinical Syndrome Analysis
10.13288/j.11-2166/r.2026.07.011
- VernacularTitle:痔病理图像自动化分割视觉大模型的构建及其在中医临床证型分析中的应用
- Author:
Shijie ZHANG
1
;
Ao ZHANG
1
;
Kang WANG
1
;
Bin KANG
2
;
Xiaofan YU
2
;
Xujing FENG
1
;
Jinyu CAO
1
;
Wenzhen HUANG
1
;
Kang DING
1
Author Information
1. Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine，Nanjing，210001
2. School of Internet of Things，Nanjing University of Posts and Telecommunications
- Publication Type:Journal Article
- Keywords:
hemorrhoids;
pathological diagnosis;
visual foundation models;
segment anything model;
traditional Chinese medicine syndrome
- From:
Journal of Traditional Chinese Medicine
2026;67(7):764-769
- CountryChina
- Language:Chinese
-
Abstract:
This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.
