基于深度学习和虚拟实配准的支架体外开窗增强现实导航研究。

IF 1.5 4区医学 Q3 SURGERY Computer Assisted Surgery Pub Date : 2023-12-01 Epub Date: 2023-12-07 DOI:10.1080/24699322.2023.2289339

Fengfeng He, Xiaoyu Qi, Qingmin Feng, Qiang Zhang, Ning Pan, Chao Yang, Shenglin Liu

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引用次数: 0

摘要

目的:体外支架移植(IVFS)开窗需要高精度的导航方法以达到最佳的手术效果。本研究旨在提出一种用于IVFS的增强现实(AR)导航方法，该方法可以提供原位覆盖显示来定位开窗位置。方法:我们提出了一种AR导航方法来辅助医生进行体外受精。采用基于深度学习的主动脉分割算法，实现了主动脉的自动快速分割。基于vuforia的虚拟实配准和标记识别算法相结合，确保了原位AR图像的准确性。结果:该方法可提供三维原位AR图像，虚实配准后的基准配准误差为2.070 mm。主动脉分割实验得到骰子相似系数为91.12%，豪斯多夫距离为2.59，优于改进前的常规算法。结论:该方法能直观、准确地定位开窗位置，可辅助医生进行体外受精。

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Research on augmented reality navigation of in vitro fenestration of stent-graft based on deep learning and virtual-real registration.

Objectives: In vitro fenestration of stent-graft (IVFS) demands high-precision navigation methods to achieve optimal surgical outcomes. This study aims to propose an augmented reality (AR) navigation method for IVFS, which can provide in situ overlay display to locate fenestration positions.

Methods: We propose an AR navigation method to assist doctors in performing IVFS. A deep learning-based aorta segmentation algorithm is used to achieve automatic and rapid aorta segmentation. The Vuforia-based virtual-real registration and marker recognition algorithm are integrated to ensure accurate in situ AR image.

Results: The proposed method can provide three-dimensional in situ AR image, and the fiducial registration error after virtual-real registration is 2.070 mm. The aorta segmentation experiment obtains dice similarity coefficient of 91.12% and Hausdorff distance of 2.59, better than conventional algorithms before improvement.

Conclusions: The proposed method can intuitively and accurately locate fenestration positions, and therefore can assist doctors in performing IVFS.

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来源期刊

Computer Assisted Surgery Medicine-Surgery

CiteScore

2.30

自引率

0.00%

发文量

审稿时长

10 weeks

期刊介绍： omputer Assisted Surgery aims to improve patient care by advancing the utilization of computers during treatment; to evaluate the benefits and risks associated with the integration of advanced digital technologies into surgical practice; to disseminate clinical and basic research relevant to stereotactic surgery, minimal access surgery, endoscopy, and surgical robotics; to encourage interdisciplinary collaboration between engineers and physicians in developing new concepts and applications; to educate clinicians about the principles and techniques of computer assisted surgery and therapeutics; and to serve the international scientific community as a medium for the transfer of new information relating to theory, research, and practice in biomedical imaging and the surgical specialties. The scope of Computer Assisted Surgery encompasses all fields within surgery, as well as biomedical imaging and instrumentation, and digital technology employed as an adjunct to imaging in diagnosis, therapeutics, and surgery. Topics featured include frameless as well as conventional stereotactic procedures, surgery guided by intraoperative ultrasound or magnetic resonance imaging, image guided focused irradiation, robotic surgery, and any therapeutic interventions performed with the use of digital imaging technology.