CT理论与应用研究2022，Vol.31Issue(5)：531-542,12.DOI:10.15953/j.ctta.2022.091
膝关节三维磁共振影像语义分割的可行性研究
A Feasibility Study of Knee Joint Semantic Segmentation on 3D MR Images
摘要
Abstract
The segmentation of knee joint is of great significance for diagnosis, guidance and treatment of knee osteoarthritis. However, manual delineation is time-consuming and labor-intensive since various anatomical structures are involved in the 3D MRI volume. Automatic segmentation of the whole knee joint requires no human effort, additionally can improve the quality of arthritis diagnosis and treatment by describing the details more accurately. Existing knee joint segmentation methods in the literature focus on only one or few structures out of many. In this paper, we study the feasibility of knee joint segmentation on MR images based on neural networks and deal with the following challenges: (1) end-to-end segmentation of 15 anatomical structures, including bone and soft tissue, of the whole knee on MR images; (2) robust segmentation of small structures such as the anterior cruciate ligament, accounting for about 0.036％ of the volume data. Experiments on the knee joint MR images demonstrate that the average segmentation accuracy of our method achieves 92.92％. The Dice similarity coefficients of 9 structures were above 94％, five structures were between 87％ and 90％, and the remaining one was about 76％.关键词
深度学习/语义分割/神经网络/磁共振影像/膝骨关节炎Key words
deep learning/semantic segmentation/neural networks/MRI/knee osteoarthritis分类
数理科学引用本文复制引用
沈乐,蔡谞,卢倩,唐虎,吴厦,易懿,孙运达,邱倩,张丽,郑卓肇..膝关节三维磁共振影像语义分割的可行性研究[J].CT理论与应用研究,2022,31(5):531-542,12.基金项目
国家自然科学基金(融合动态频谱与个性化建模的冠状动脉容积成像方法与关键技术(62031020)) （融合动态频谱与个性化建模的冠状动脉容积成像方法与关键技术(62031020）
2019年人工智能关键技术源头创新专项(立体图像智能安全计算及软硬件协同优化). （立体图像智能安全计算及软硬件协同优化）
