CAT: a computational anatomy toolbox for the analysis of structural MRI data.
Alzheimer’s disease
CAT12
MRI
ROI
SPM12
VBM
brain
computational anatomy
cortical folding
cortical surface
cortical thickness
longitudinal
morphometry
Journal
GigaScience
ISSN: 2047-217X
Titre abrégé: Gigascience
Pays: United States
ID NLM: 101596872
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
received:
05
03
2024
revised:
17
05
2024
accepted:
27
06
2024
medline:
5
8
2024
pubmed:
5
8
2024
entrez:
5
8
2024
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 39102518
pii: 7727520
doi: 10.1093/gigascience/giae049
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIH HHS
ID : R01HD081720
Pays : United States
Organisme : University of Auckland
Informations de copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of GigaScience.