Advances in AI-Enabled Total Hip Arthroplasty
10.16156/j.1004-7220.2024.06.030
- VernacularTitle:人工智能赋能的全髋关节置换术进展
- Author:
Yinshu HUANG
1
;
Haojie SHAN
;
Xiaowei YU
Author Information
1. 上海海洋大学 工程学院,上海 201306
- Publication Type:Journal Article
- Keywords:
artificial intelligence(AI);
total hip arthroplasty;
preoperative planning;
medical image segmentation;
medical image registration
- From:
Journal of Medical Biomechanics
2024;39(6):1228-1234
- CountryChina
- Language:Chinese
-
Abstract:
Preoperative planning,intraoperative navigation,and postoperative rehabilitation of total hip arthroplasty(THA)have been significantly enhanced by the integration of artificial intelligence(AI)technology.This review summarizes the latest advancements in AI technology for medical image segmentation and registration,with a particular focus on its application in THA.The notable differences between medical and natural images present challenges for the design of AI algorithms.Deep learning techniques,especially CNN,U-Net,and Transformer models,have demonstrated an outstanding performance in various medical image segmentation and registration tasks.The AI technology,through deep learning analysis of CT images,has significantly improved the accuracy of identifying hip pathologies.In terms of intraoperative guidance,AI systems provide real-time navigation and precise positioning for surgeries by utilizing intelligent segmentation and motion state simulation,effectively enhancing surgical efficiency.AI technology also encompasses surgical cost prediction and postoperative recovery,offering robust data support for medical decision-making through method such as Markov models.As deep learning technology continues to advance,the analysis of medical images is progressively achieving automation and intelligence,which has significant clinical implications for improving patients'overall surgical experiences and outcomes,suggesting potential new breakthroughs in the field of medical imaging in the future.
