CIVET is an image processing pipeline for fully automated volumetric, corticometric, and morphometric analysis of human brain imaging data (MRI). CIVET performs transformation into stereotaxic space, grey and white matter tissue classification, reconstruction of left and right hemisphere cortical surfaces, surface registration in order to perform group comparisons and cortical thickness analysis. Regional maps are produced based on the lobar parcellation of surfaces. A number of other measurements are also performed, such as mean curvature, gyrification index and total cortical area.
Conversion tools to make comparison between CIVET and other image processing tools are available on demand.
Large-Scale data analysis
The CIVET pipeline can take advantage of distributed compute clusters to expedite preprocessing of large-scale anatomical MRI data through parallel-processing. Features such as automatically-generates quality-control spreadsheets, preprocessing logs, and composite images to provide a visual summary of the pipeline output, facilitate detection of errors and outlying data.
Currently, different versions of CIVET are installed on CBRAIN.
Technical Features of CIVET
CIVET is implemented with high-level scripts, primarily using the common scripting language Perl, that runs computationally efficient image processing tools mainly implemented in C/C++. CIVET extends the previous in-house pipelines by the addition of corticometry analysis tools.
CIVET analysis includes our in-house morphometric analysis tools for:
More Information and Documentation
Documentation about CIVET at McGill University website