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Abstract #3574

MicroQIT - A Computational Framework for Population Microstructure Imaging

Ryan P Cabeen1 and Arthur W Toga1

1Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States

Microstructure imaging provides a quantitative tool for characterizing neural tissue with diffusion MRI and expanding our understanding of how the brain changes in health and disease. However, robust computational tools are needed for population imaging studies, so we developed a computational framework (MicroQIT) using the Quantitative Imaging Toolkit to meet this need by providing regional summaries and spatially normalized microstructure parameter maps. It supports a variety of ways to extract microstructure information from multi-shell diffusion MRI, leverages grid computing environments, and is available for use by the research community for future studies.

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