摘要： 胃肠道间质瘤是常见的胃肠道上皮下肿瘤，具有一定的恶性潜能。早期诊断及恶性潜能的预测对于胃肠道间质瘤治疗方案的制定及预后十分重要。深度学习技术已在消化道疾病诊断领域取得重大进展，可有效辅助诊断胃肠道间质瘤，并在术前预测其恶性潜能。深度学习技术在胃肠道间质瘤诊断中的应用包括CT、常规内镜和超声内镜3个方面。本文就深度学习技术在胃肠道间质瘤诊断及恶性潜能预测中的应用进行综述。

深度学习技术在胃肠道间质瘤诊断中的应用

陈婷婷¹, 杨帆¹, 李泽阳², 徐士雪¹, 杨飞¹, 刘香¹

1. 中国医科大学附属盛京医院消化内科, 沈阳 110004;
2. 中国医科大学附属盛京医院普通外科, 沈阳 110004

收稿日期:2022-10-31出版日期:2024-02-28发布日期:2024-01-12
通讯作者:刘香E-mail:liux@sj-hospital.org
作者简介:陈婷婷(1998-),女,医师,硕士研究生.
基金资助:国家自然科学基金（82100700）


关键词: 深度学习技术, 胃肠道间质瘤, 诊断
Abstract: Gastrointestinal stromal tumor (GIST), with a certain malignant potential, are currently the most common subepithelial tumors of the gastrointestinal tract. Early diagnosis and prediction of malignant potential are very important for the formulation of a treatment plan and determining the prognosis of GIST. Deep learning technology has made significant progress in the diagnosis of digestive tract diseases, and it can also effectively assist physicians in diagnosing GIST and predicting their malignant potential, preoperatively. The application of deep learning technology in the diagnosis of GIST includes CT, gastrointestinal endoscopy and endoscopic ultrasound. This paper aims to review the application of deep learning technology in the diagnosis and prediction of malignant potential of GIST.
Key words: deep learning technology, gastrointestinal stromal tumor, diagnosis
PDF全文下载地址:

https://journal.cmu.edu.cn/CN/article/downloadArticleFile.do?attachType=PDF&id=3371