工具箱
计算机科学
数据科学
人工智能
解剖
计算生物学
生物
程序设计语言
作者
Christian Gaser,Robert Dahnke,Paul M. Thompson,Florian Kurth,Eileen Luders A,The Alzheimer’s Disease Neuroimaging Initiative
出处
期刊:GigaScience
[University of Oxford]
日期:2024-01-01
卷期号:13
被引量:1398
标识
DOI:10.1093/gigascience/giae049
摘要
A large range of sophisticated brain image analysis tools have been developed by the neuroscience community, greatly advancing the field of human brain mapping. Here we introduce the Computational Anatomy Toolbox (CAT)-a powerful suite of tools for brain morphometric analyses with an intuitive graphical user interface but also usable as a shell script. CAT is suitable for beginners, casual users, experts, and developers alike, providing a comprehensive set of analysis options, workflows, and integrated pipelines. The available analysis streams-illustrated on an example dataset-allow for voxel-based, surface-based, and region-based morphometric analyses. Notably, CAT incorporates multiple quality control options and covers the entire analysis workflow, including the preprocessing of cross-sectional and longitudinal data, statistical analysis, and the visualization of results. The overarching aim of this article is to provide a complete description and evaluation of CAT while offering a citable standard for the neuroscience community.
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