Development and Pre-Clinical Analysis of Spatiotemporal-Aware Augmented Reality in Orthopedic Interventions.

IF 8.9 1区 医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS IEEE Transactions on Medical Imaging Pub Date : 2021-02-01 DOI:10.1109/TMI.2020.3037013
Javad Fotouhi, Arian Mehrfard, Tianyu Song, Alex Johnson, Greg Osgood, Mathias Unberath, Mehran Armand, Nassir Navab
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引用次数: 10

Abstract

Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only been considered as a visualization device improving traditional workflows. As a consequence, the technology is gaining minimum maturity that it requires to redefine new procedures, user interfaces, and interactions. The main contribution of this paper is to reveal how exemplary workflows are redefined by taking full advantage of head-mounted displays when entirely co-registered with the imaging system at all times. The awareness of the system from the geometric and physical characteristics of X-ray imaging allows the exploration of different human-machine interfaces. Our system achieved an error of 4.76 ± 2.91mm for placing K-wire in a fracture management procedure, and yielded errors of 1.57 ± 1.16° and 1.46 ± 1.00° in the abduction and anteversion angles, respectively, for total hip arthroplasty (THA). We compared the results with the outcomes from baseline standard operative and non-immersive AR procedures, which had yielded errors of [4.61mm, 4.76°, 4.77°] and [5.13mm, 1.78°, 1.43°], respectively, for wire placement, and abduction and anteversion during THA. We hope that our holistic approach towards improving the interface of surgery not only augments the surgeon's capabilities but also augments the surgical team's experience in carrying out an effective intervention with reduced complications and provide novel approaches of documenting procedures for training purposes.

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时空感知增强现实在骨科干预中的发展和临床前分析。
与患者数据的次优交互以及掌握基于病态2D介入图像的3D解剖的挑战是图像引导治疗中必不可少的问题。在过去的十年里,增强现实(AR)已经被引入手术室;然而,在图像引导干预中,它通常只被认为是一种改进传统工作流程的可视化设备。因此,该技术正在获得最小的成熟度,它需要重新定义新的过程、用户界面和交互。本文的主要贡献是揭示了如何通过充分利用头戴式显示器在任何时候完全与成像系统共同注册时重新定义示例工作流程。系统从x射线成像的几何和物理特征的意识允许探索不同的人机界面。我们的系统在骨折处理过程中放置k -钢丝的误差为4.76±2.91mm,在全髋关节置换术(THA)中,外展角和前倾角的误差分别为1.57±1.16°和1.46±1.00°。我们将结果与基线标准手术和非沉浸式AR手术的结果进行了比较,后者在THA期间放置导线、外展和前倾的误差分别为[4.61mm, 4.76°,4.77°]和[5.13mm, 1.78°,1.43°]。我们希望我们改善手术界面的整体方法不仅可以提高外科医生的能力,还可以增加手术团队在减少并发症的情况下进行有效干预的经验,并为培训目的提供记录手术过程的新方法。
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
IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging 医学-成像科学与照相技术
CiteScore
21.80
自引率
5.70%
发文量
637
审稿时长
5.6 months
期刊介绍: The IEEE Transactions on Medical Imaging (T-MI) is a journal that welcomes the submission of manuscripts focusing on various aspects of medical imaging. The journal encourages the exploration of body structure, morphology, and function through different imaging techniques, including ultrasound, X-rays, magnetic resonance, radionuclides, microwaves, and optical methods. It also promotes contributions related to cell and molecular imaging, as well as all forms of microscopy. T-MI publishes original research papers that cover a wide range of topics, including but not limited to novel acquisition techniques, medical image processing and analysis, visualization and performance, pattern recognition, machine learning, and other related methods. The journal particularly encourages highly technical studies that offer new perspectives. By emphasizing the unification of medicine, biology, and imaging, T-MI seeks to bridge the gap between instrumentation, hardware, software, mathematics, physics, biology, and medicine by introducing new analysis methods. While the journal welcomes strong application papers that describe novel methods, it directs papers that focus solely on important applications using medically adopted or well-established methods without significant innovation in methodology to other journals. T-MI is indexed in Pubmed® and Medline®, which are products of the United States National Library of Medicine.
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