基于人工智能的膝关节自动建模研究  

Automatic modeling of the knee joint based on artificial intelligence

作　　者：汤小勇 李晓虎 谷雪莲[1] 赵宇轩 刘洝辰 刘宇甜 陶玉蓉 TANG Xiaoyong;LI Xiaohu;GU Xuelian;ZHAO Yuxuan;LIU Anchen;LIU Yutian;TAO Yurong(School of Health Sciences and Engineering,University of Shanghai for Science and Technology,Shanghai,200093,P.R.China)

机构地区：[1]上海理工大学健康科学与工程学院,上海200093

出　　处：《中国修复重建外科杂志》2023年第3期348-352,共5页Chinese Journal of Reparative and Reconstructive Surgery

基　　金：上海介入医疗器械工程技术研究中心建设项目(18DZ2250900);国家自然科学基金资助项目(82172441)。

摘　　要：目的研究基于Mimics软件的人工智能(artificial intelligence,AI)自动分割膝关节CT图像建模方法,旨在提高膝关节建模效率。方法选择3名志愿者膝关节CT影像,在Mimics软件中分别进行AI自动分割和手动分割图像并建模,记录自动建模时间。参考既往文献选择股骨远端和胫骨近端解剖标志点,计算与手术设计相关的参考指标,用Pearson相关系数(r)判断两种方法建模结果相关性,以DICE系数分析两种方法建模结果一致性。结果经自动及手动分割图像均成功构建膝关节三维模型。3个膝关节自动分割建模所需时间分别为10.45、9.50、10.20 min,较既往文献中手动分割建模(64.73±17.07)min缩短。相关性分析示手动和自动分割生成的模型之间存在强相关性(r=0.999,P<0.001)。3个膝关节股骨DICE系数分别为0.990、0.996和0.944,胫骨分别为0.943、0.978和0.981,提示手动与自动分割建模一致性程度高。结论在Mimics软件中可采用AI分割图像方法快速建立有效的膝关节三维模型。Objective To investigate an artificial intelligence(AI)automatic segmentation and modeling method for knee joints,aiming to improve the efficiency of knee joint modeling.Methods Knee CT images of 3 volunteers were randomly selected.AI automatic segmentation and manual segmentation of images and modeling were performed in Mimics software.The AI-automated modeling time was recorded.The anatomical landmarks of the distal femur and proximal tibia were selected with reference to previous literature,and the indexes related to the surgical design were calculated.Pearson correlation coefficient(r)was used to judge the correlation of the modeling results of the two methods;the consistency of the modeling results of the two methods were analyzed by DICE coefficient.Results The threedimensional model of the knee joint was successfully constructed by both automatic modeling and manual modeling.The time required for AI to reconstruct each knee model was 10.45,9.50,and 10.20 minutes,respectively,which was shorter than the manual modeling[(64.73±17.07)minutes]in the previous literature.Pearson correlation analysis showed that there was a strong correlation between the models generated by manual and automatic segmentation(r=0.999,P<0.001).The DICE coefficients of the 3 knee models were 0.990,0.996,and 0.944 for the femur and 0.943,0.978,and 0.981 for the tibia,respectively,verifying a high degree of consistency between automatic modeling and manual modeling.Conclusion The AI segmentation method in Mimics software can be used to quickly reconstruct a valid knee model.

关 键 词：自动分割 膝关节 Pearson相关系数 DICE系数 人工智能 

分 类 号：R687.4[医药卫生—骨科学]