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连接组可视化工具：用于人类脑网络可视化的软件。

The Connectome Visualization Utility: software for visualization of human brain networks.

作者信息

LaPlante Roan A, Douw Linda, Tang Wei, Stufflebeam Steven M

机构信息

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America.

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America; VU University Medical Center, Department of Anatomy & Clinical Neurosciences, Amsterdam, The Netherlands.

出版信息

PLoS One. 2014 Dec 1;9(12):e113838. doi: 10.1371/journal.pone.0113838. eCollection 2014.

DOI:10.1371/journal.pone.0113838
PMID:25437873
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4250035/
Abstract

In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats.

摘要

在人类连接组分析中，人类大脑的连接性是通过多种成像方式收集的，并使用图论技术进行分析。人类连接性数据的维度很高，理解连接组学中的复杂网络需要复杂的可视化和分析软件。目前可用于分析人类连接组的软件包有限。连接组可视化工具（CVU）是一个新的软件包，专为人类脑网络的可视化和网络分析而设计。CVU通过提供扩展的交互式分析和高级可视化功能来补充现有软件包，包括以三种不同的互补样式自动可视化网络，并具有标量图论属性和模块化结构的特殊可视化功能。通过将网络创建过程与网络可视化和分析解耦，我们确保CVU可以可视化来自任何成像方式的网络。CVU提供图形用户界面、交互式脚本，并表示数据使用透明的神经成像和基于矩阵的文件类型，而不是不透明的特定于应用程序的文件格式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/82904391fb7a/pone.0113838.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/d8eb8b4a90dc/pone.0113838.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/f819b33289fb/pone.0113838.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/5547e632ad59/pone.0113838.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/93e30fc4b709/pone.0113838.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/82904391fb7a/pone.0113838.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/d8eb8b4a90dc/pone.0113838.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/f819b33289fb/pone.0113838.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/5547e632ad59/pone.0113838.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/93e30fc4b709/pone.0113838.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe2/4250035/82904391fb7a/pone.0113838.g005.jpg

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