Automatic Landmark Detection for Preoperative Planning of High Tibial Osteotomy Using Traditional Feature Extraction and Deep Learning Methods

IF 2.3 3区医学 Q2 SURGERY

International Journal of Medical Robotics and Computer Assisted Surgery Pub Date : 2024-11-04 DOI:10.1002/rcs.70006

Jiaqi Han, Xinlong Ma, Yiou Lyu, Haohao Bai

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引用次数: 0

Abstract

Background

Automatic High Tibial Osteotomy (HTO) landmark detection methods promise to improve the effectiveness and standardisation of HTO preoperative planning. Unfortunately, due to the limited number of HTO datasets, existing methods are less robust when dealing with patients with varied deformities than traditional manual planning, severely limiting their clinical viability and application in practical surgical settings.

Methods

Here, we present a new HTO landmark detection framework using an integration of optimised heatmap-offset aggregation method and traditional feature extraction. Subjective and objective approaches were employed to reflect the final clinical acceptance of our model.

Results

Average Mean Absolute Error of prediction results compared to the surgeon's gold standard was 0.35° for the hip-knee-ankle angle. The objective score rated by surgeons reached 4.4 on a scale of 5.

Conclusion

The study demonstrated that the automatic detection method has great potential serving as an alternative to manual radiological analysis in practical surgical pre-operative planning.

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利用传统特征提取和深度学习方法为高胫骨截骨术的术前规划进行自动地标检测

背景：自动高胫骨截骨术（HTO）地标检测方法有望提高HTO术前规划的有效性和标准化。不幸的是，由于 HTO 数据集数量有限，现有方法在处理畸形各异的患者时不如传统人工规划方法稳健，严重限制了其在实际手术环境中的临床可行性和应用。我们采用了主观和客观的方法来反映我们模型的最终临床接受度：结果：与外科医生黄金标准相比，髋关节-膝关节-踝关节角度预测结果的平均绝对误差为 0.35°。外科医生的客观评分达到了 4.4 分（5 分制）：研究表明，自动检测方法在实际手术术前规划中替代人工放射学分析的潜力巨大。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Medical Robotics and Computer Assisted Surgery 医学-外科

CiteScore

4.50

自引率

12.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.