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Abstract #2854

Quantitative Imaging Toolkit: Software for Interactive 3D Visualization, Data Exploration, and Computational Analysis of Neuroimaging Datasets

Ryan P Cabeen1, David H Laidlaw2, and Arthur W Toga1

1Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States, 2Department of Computer Science, Brown University, Providence, RI, United States

Computational tools are increasingly important to MR imaging research, as they can make experiments more reproducible, improve our ability to share our findings and methods, and facilitate hypothesis generation. We aim to contribute a software package to the research community named the Quantitative Imaging Toolkit (QIT). QIT was developed to provide tools for 3D visualization, data exploration, and computational analysis of neuroimaging datasets. While meant to be generally useful for neuroimaging, the tools have extensively developed features for analyzing diffusion MRI data, running large population imaging analyses, and developing new algorithms.

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