Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada.
Montréal Neurological Institute & Hospital (MNI/H), Montréal, Canada.
Comput Assist Surg (Abingdon). 2024 Dec;29(1):2355897. doi: 10.1080/24699322.2024.2355897. Epub 2024 May 24.
Advancements in mixed reality (MR) have led to innovative approaches in image-guided surgery (IGS). In this paper, we provide a comprehensive analysis of the current state of MR in image-guided procedures across various surgical domains. Using the Data Visualization View (DVV) Taxonomy, we analyze the progress made since a 2013 literature review paper on MR IGS systems. In addition to examining the current surgical domains using MR systems, we explore trends in types of MR hardware used, type of data visualized, visualizations of virtual elements, and interaction methods in use. Our analysis also covers the metrics used to evaluate these systems in the operating room (OR), both qualitative and quantitative assessments, and clinical studies that have demonstrated the potential of MR technologies to enhance surgical workflows and outcomes. We also address current challenges and future directions that would further establish the use of MR in IGS.
混合现实 (MR) 的进步带来了图像引导手术 (IGS) 的创新方法。本文全面分析了当前各种外科领域中基于图像的 MR 引导手术的现状。我们使用数据可视化视图 (DVV) 分类法,分析了自 2013 年关于 MR IGS 系统的文献综述以来取得的进展。除了检查当前使用 MR 系统的外科领域外,我们还探讨了用于手术的 MR 硬件类型、可视化数据类型、虚拟元素的可视化以及使用中的交互方法的趋势。我们的分析还涵盖了在手术室 (OR) 中评估这些系统的指标,包括定性和定量评估以及已经证明 MR 技术有潜力增强手术流程和结果的临床研究。我们还讨论了当前的挑战和未来的方向,这将进一步确立 MR 在 IGS 中的应用。
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