膝关节骨关节炎成像和全膝关节整形术中的人工智能:进步,挑战和细分方法 - - 综述
Ahsan Humayun1, Mustafain Rehman2, Muhammad Zainulabideen2
1Department of Software Engineering, Faculty of Information Technology and Computer Science, University of Central Punjab, Lahore 54000, Pakistan; DUT School of Software Technology & DUT-RU International School of Information Science and Engineering, Dalian University of Technology, China.
The Knee
|January 21, 2026
概括
使用人工智能 (AI) 的自动细分可以改善膝盖成像,用于全膝关节整形术 (TKA) 规划. 人工智能方法比经典技术提供了更高的准确性,解决了更精确的患者特异性膝关节置换的局限性.
科学领域:
- 整形外科 整形外科 整形外科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 膝关节关节炎 (KOA) 是导致残疾的主要原因.
- 膝关节整形术 (TKA) 是高级KOA的标准,需要精确的成像和规划.
- 目前的成像方法 (X射线图,CT,MRI,超声波) 有诸如人造物和软组织对比度差等局限性.
研究的目的:
- 审查TKA中膝盖成像的自动细分和分析方法.
- 为了比较传统和人工智能驱动的TKA规划和评估方法.
主要方法:
- 对经典细分技术的调查 (基于区域,边界,地图,模型).
- 审查人工智能驱动的方法,专注于深度学习模型.
- 讨论这些方法的功能,局限性和临床相关性.
主要成果:
- 经典方法提供了基础工具,但缺乏概括性.
- 人工智能,特别是深度学习,提高了细分精度和结果预测.
- 人工智能解决了传统的局限性,但需要大量的数据集和标准化的协议.
结论:
- 将人工智能集成到TKA工作流程中,有望实现更精确,更可靠,更针对患者的膝关节关节置换术.
- 基于人工智能的细分比传统的TKA规划方法具有显著的优势.
- 解决人工智能实施中的挑战是临床采用的关键.
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