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Abstract #1584

New analysis and visualization tools AFNI-FATCAT (and implementing other software)

Paul Taylor1, Justin Rajendra1, Amritha Nayak2,3, M. Okan Irfanoglu2, Daniel R Glen1, and Richard C Reynolds1

1NIMH, NIH, Bethesda, MD, United States, 2NIBIB, NIH, Bethesda, MD, United States, 3Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States

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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