时珍国医国药2026，Vol.37Issue(5)：987-992,6.DOI:10.70976/j.1008-0805.SZGYGY-2026-0528
基于Vision Transformer的肠镜图像识别模型在结肠疾病中的诊断作用研究
The diagnostic role of a vision transformer-based model in colonoscopic image recognition for colonic diseases
摘要
Abstract
Objective To investigate the diagnostic role of a Vision Transformer(ViT)-based artificial intelligence(AI)system in colonic diseases by analyzing clinical endoscopic imaging data.Methods A total of 3000 standard white-light colonoscopy images from 1082 patients with histologically confirmed colonic diseases(including colon polyps,colitis,and colon cancer)were retrospectively col-lected from the Endoscopy Center database of Hebei Provincial Hospital of Traditional Chinese Medicine.The processed datasets of these three disease types were divided in a ratio of 7:2:1.For each disease type,70%of the images were randomly selected as the train-ing set,20%as the test set,and 10%as the validation set.Finally,the ViT model was used to identify and classify the images.Results In the test set,the classification accuracy for colonoscopy images was 99.61%for colon polyps,99.67%for colitis,and 100.00%for colon cancer.Conclusion ViT demonstrated high diagnostic accuracy in detecting colonic diseases.This model can assist primary hospi-tals in enhancing the diagnostic accuracy of colonic diseases and help primary endoscopists enhance their ability to identify colonic dis-eases,thus demonstrating relatively reliable clinical application value.关键词
结肠疾病/Vision Transformer/分类识别/临床应用Key words
Colonic diseases/Vision transformer/Classification and recognition/Clinical application分类
医药卫生引用本文复制引用
张婷,徐伟超,许亚培,王子康,夏悦桐,刘秋华,杜姚,才艳茹,杨倩..基于Vision Transformer的肠镜图像识别模型在结肠疾病中的诊断作用研究[J].时珍国医国药,2026,37(5):987-992,6.基金项目
国家自然科学基金(82205314) （82205314）
国家科技重大专项(2024ZD0521004) （2024ZD0521004）
国家中医药管理局科技项目(GZY-KJS-2023-025) （GZY-KJS-2023-025）
河北省中央引导地方科技专项项目(246Z7708G) （246Z7708G）
河北省自然科学基金项目(H2023423001) （H2023423001）
河北省中医药定量化研究创新专项(252W7712D) （252W7712D）
