Xu Jiayi, Thevenon Gaspard, Chabat Timothee, McCormick Matthew, Li Forrest, Birdsong Tom, Martin Ken, Lee Yueh, Aylward Stephen
Kitware, Inc.
The University of North Carolina at Chapel Hill.
Comput Methods Biomech Biomed Eng Imaging Vis. 2023;11(4):1019-1026. doi: 10.1080/21681163.2022.2145239. Epub 2022 Nov 18.
The diversity and utility of cinematic volume rendering (CVR) for medical image visualization have grown rapidly in recent years. At the same time, volume rendering on augmented and virtual reality systems is attracting greater interest with the advance of the WebXR standard. This paper introduces CVR extensions to the open-source visualization toolkit (vtk.js) that supports WebXR. This paper also summarizes two studies that were conducted to evaluate the speed and quality of various CVR techniques on a variety of medical data. This work is intended to provide the first open-source solution for CVR that can be used for in-browser rendering as well as for WebXR research and applications. This paper aims to help medical imaging researchers and developers make more informed decision when selecting CVR algorithms for their applications. Our software and this paper also provide a foundation for new research and product development at the intersection of medical imaging, web visualization, XR, and CVR.
近年来,用于医学图像可视化的电影体绘制(CVR)的多样性和实用性迅速增长。与此同时,随着WebXR标准的推进,增强现实和虚拟现实系统上的体绘制正吸引着越来越多的关注。本文介绍了对支持WebXR的开源可视化工具包(vtk.js)的CVR扩展。本文还总结了两项研究,这些研究旨在评估各种CVR技术在各种医学数据上的速度和质量。这项工作旨在为CVR提供首个开源解决方案,该方案可用于浏览器内渲染以及WebXR研究和应用。本文旨在帮助医学成像研究人员和开发人员在为其应用选择CVR算法时做出更明智的决策。我们的软件和本文还为医学成像、网络可视化、扩展现实和CVR交叉领域的新研究和产品开发奠定了基础。