The typical size of MRI data sets being processed for a study is rapidly increasing, particularly with the growth of publicly available data sets and “big data” strategies for approaching problems. This produces a dual need in analysis: having scriptable and reproducible pipelines for analysis, as well as having a method for visualizing data both during intermediate steps and for final results presentation. Here, we describe new AFNI-FATCAT tools that provides a succinct set of processing steps for a full DTI analysis pipeline, from DICOM conversion to tractography and statistical anlyses; these tools create QC images and quantitative checks at each step for pipeline evaluation.
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