bioRxiv (Cold Spring Harbor Laboratory) · 2022 · 626 citations · 57 references
MedicineAnatomyNeuroscienceComputational NeuroscienceHuman AnatomyNeuroanatomyBrain ImagingComputational NeuroanatomyGross Brain AnatomyMagnetic Resonance ImagingMedical Image AnalysisMedical ImagingComputational AnatomyGraphical User InterfacesMorphometric VisualizationPipelinesStructural Brain ImagingSurface-based Morphometric AnalysisSurface-based MorphometryVolumetric Brain Analysis
Abstract 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, as well as 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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A fast diffeomorphic image registration algorithm
John Ashburner · NeuroImage · 2007 · 8.3K citations
John Ashburner, Karl Friston · NeuroImage · 2005 · 7.5K citations