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Multiuser collaborative illustration and visualization for volumetric scientific data
Software: Practice and Experience ( IF 3.5 ) Pub Date : 2020-11-22 , DOI: 10.1002/spe.2935
Richen Liu 1 , Xiaodong Wen 1 , Meng Jiang 1 , Guang Yang 1 , Chuyu Zhang 1 , Xiaojian Chen 1
Affiliation  

Multiuser can collaboratively complete complex visualization tasks that cannot be completed by a single user. Although multiuser collaboration system has made great progress, there are many challenges in the collaborative visualization of 3D volumetric scientific data due to the difficulties in multiuser collaboration, and collaborative slice analysis. This article proposes a client‐server based collaborative visualization system, which consists of a 3D volume explorer and a 2D slice analyzer, to help domain experts to fully utilize their background domain knowledge to illustrate different parts of the data. For example, the brain surgeon expert, pulmonologist, and cardiologist can visualize and analyze the different subsets of the volumetric scientific data, that is, the corresponding subvolumes of the brain, heart, lungs, and blood vessels. It also allows taking full advantage of the hardware resources, because all the computation intensive tasks especially for the whole data rendering can be allocated to the powerful server while the light‐weight tasks can be allocated to the portable clients. Besides, we design a seed point tracing algorithm based on flood fill algorithm to illustrate the slice more efficiently. We evaluate the system by collecting the feedback from domain experts and the people who are unfamiliar with data computation or visualization. The evaluation shows that the 3D volume explorer and the 2D slice analyzer are capable of supporting peer‐expert discussion and medical case teaching, respectively.

中文翻译:

体积科学数据的多用户协作插图和可视化

多用户可以协同完成单个用户无法完成的复杂可视化任务。尽管多用户协作系统已经取得了长足的进步,但是由于多用户协作和协作切片分析的困难,在3D体积科学数据的协作可视化方面仍然存在许多挑战。本文提出了一种基于客户端-服务器的协作可视化系统,该系统由3D体积浏览器和2D切片分析器组成,以帮助领域专家充分利用其背景领域知识来说明数据的不同部分。例如,脑外科专家,肺病学家和心脏病学家可以可视化并分析体积科学数据的不同子集,即大脑,心脏,肺和血管的相应子体积。它还可以充分利用硬件资源,因为可以将所有计算密集型任务(尤其是整个数据渲染任务)分配给功能强大的服务器,而将轻量级任务分配给便携式客户端。此外,我们设计了一种基于泛洪填充算法的种子点跟踪算法,以更有效地说明切片。我们通过收集领域专家和不熟悉数据计算或可视化的人员的反馈来评估系统。评估显示,3D体积浏览器和2D切片分析器分别能够支持同行专家讨论和医学案例教学。因为所有的计算密集型任务(尤其是整个数据渲染)都可以分配给功能强大的服务器,而轻量级的任务可以分配给便携式客户端。此外,我们设计了一种基于泛洪填充算法的种子点跟踪算法,以更有效地说明切片。我们通过收集领域专家和不熟悉数据计算或可视化的人员的反馈来评估系统。评估显示,3D体积浏览器和2D切片分析器分别能够支持同行专家讨论和医学案例教学。因为所有的计算密集型任务(尤其是整个数据渲染)都可以分配给功能强大的服务器,而轻量级的任务可以分配给便携式客户端。此外,我们设计了一种基于泛洪填充算法的种子点跟踪算法,以更有效地说明切片。我们通过收集领域专家和不熟悉数据计算或可视化的人员的反馈来评估系统。评估显示,3D体积浏览器和2D切片分析器分别能够支持同行专家讨论和医学案例教学。我们通过收集领域专家和不熟悉数据计算或可视化的人员的反馈来评估系统。评估显示,3D体积浏览器和2D切片分析器分别能够支持同行专家讨论和医学案例教学。我们通过收集领域专家和不熟悉数据计算或可视化的人员的反馈来评估系统。评估显示,3D体积浏览器和2D切片分析器分别能够支持同行专家讨论和医学案例教学。
更新日期:2020-11-22
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