文献类型：期刊文献

中文题名：深度学习用于影像学研究膝骨关节炎进展

英文题名：Progresses of deep learning in imaging research of knee osteoarthritis

作者：何雪[1];乔翠[1];项家宝[1];吴亮[1];周晟[2]

第一作者：何雪

机构：[1]甘肃中医药大学第一临床学院,甘肃兰州730000;[2]甘肃省人民医院放射科,甘肃兰州730000

第一机构：甘肃中医药大学中医临床学院

年份：2026

卷号：42

期号：1

起止页码：144

中文期刊名：中国医学影像技术

外文期刊名：Chinese Journal of Medical Imaging Technology

收录：;北大核心:【北大核心2023】；

语种：中文

中文关键词：骨关节炎;膝;深度学习;诊断显像

外文关键词：osteoarthritis,knee;deep learning;diagnostic imaging

摘要：膝骨关节炎(KOA)是常见退行性关节疾病,早期诊断和精确诊疗对改善患者生活质量至关重要。传统影像学诊断和评估KOA存在主观性强、诊断标准不统一等问题。深度学习(DL)为自动化诊断和评估KOA提供了新的可能。本文围绕DL用于X线、MRI诊断与评估KOA,以及影像学评估以全膝关节置换术治疗KOA研究进展展开综述。
Knee osteoarthritis(KOA)is a common degenerative joint disease,for which early diagnosis and accurate assessment are crucial to improve patients'life quality.Traditional imaging examinations for diagnosing and evaluating KOA faced challenges such as strong subjectivity and lack of unified diagnostic criteria.Deep learning(DL)has possibilities for automated diagnosis and assessment of KOA.The progresses in DL for X-ray and MRI research of diagnosis and evaluation of KOA,as well as in imaging assessment of total knee replacement for treating KOA were reviewed in this article.