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Abstract #4489

SlicerDMRI: a suite of clinician-accessible tools for neurosurgical planning research using diffusion MRI and tractography

Fan Zhang1, Thomas Noh1, Parikshit Juvekar1, Sarah F Frisken1, Laura Rigolo1, Isaiah Norton1, Tina Kapur1, Sonia Pujol1, William Wells III1,2, Alex Yarmarkovich3, Gordon Kindlmann4, Demian Wassermann5, Raul San Jose Estepar1, Yogesh Rathi1, Ron Kikinis1,6, Hans J Johnson7, Carl-Fredrik Westin1, Steve Pieper3, Alexandra J Golby1, and Lauren J O'Donnell1
1Harvard Medical School, Boston, MA, United States, 2Massachusetts Institute of Technology, Boston, MA, United States, 3Isomics, Inc., Cambridge, MA, United States, 4University of Chicago, Chicago, IL, United States, 5Université Paris-Saclay, Palaiseau, France, 6University of Bremen and Fraunhofer MEVIS, Bremen, Germany, 7University of Iowa, Iowa City, IA, United States

We present an open-source software suite, SlicerDMRI (dmri.slicer.org), that enables neurosurgical planning research using diffusion magnetic resonance imaging (dMRI). SlicerDMRI is built upon and deeply integrated with 3D Slicer, an NIH-supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. In this work, we give a demonstration of SlicerDMRI to enable end-to-end dMRI analyses in two retrospective imaging datasets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor imaging (DTI) analysis, advanced multi-fiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI.

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