DBP:HD Data Collaborators

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Requester Institution Description of Project
Ramesh Sridharan & Adrian Dalca Polina Gollard's Group, CSAIL, MIT Learn image manifolds and the underlying structure of brain images by incorporating external constraints such as longitudinal data.
Archana Venkataraman Polina Gollard's Group, CSAIL, MIT Model the structural-functional relationship in the brain and how it breaks down in clinical populations.
Manasi Datar & Ross Whitaker SCI Institue, School of Computing, University of Utah Include longitudinal shape regression into the ShapeWorks framework.
Martin Styner University of North Carolina novel longitudinal shape analysis methodology and apply those to the longitudinal changes of the nucleus caudate in patients suffering from Huntington’s disease, as well as novel longitudinal DTI assessment methods and apply those to several white matter fiber tracts of interest, such as the cerebro spinal tract and anterior thalamic radiations, in patients suffering from Huntigton’s disease.
Yi Gao Georgia Tech Segmentation and registration research.
Guido Gerig University of Utah Develop analysis methodologies for 4D MR images, specifically quantifying longitudinal anatomical changes and comparing such changes between different populations.
Carl-Fredrik Westin Brigham and Women's Hospital / Harvard Medical School Develop novel analysis methods.
Thomas Shultz Max Plank Institute Develop reliable and reproducible methods for in vivo segmentation of thalamic subnuclei.
William Wells Brigham and Women's Hospital / Harvard Medical School Evaluate quantitative susceptibility mapping.
Hans Johnson University of Iowa Developing new and refined existing tools to achieve the specific aims of the NA-MIC HD-DBP.
Casey Goodlett Kitware Develop registration algorithms for distribution in Slicer 3D.
Dan Marcus Washington University in St. Louis School of Medicine Improve data distribution and modeling methods for the xnat imaging informatics platform.
Anuj Srivastava and Sentibaleng Ncube Florida State University Development of novel Riemannian metrics for HARDI data analysis.
Stefan Klöppel & Volkmar Glauche UNIVERSITÄTS FREIBURG Study white matter changes in different stages of HD and compare data variability between diffusion directions for sequences with many direction but a single repetition.
Jessica Turner University of California, Irvine Develop the use of automated reasoning systems to represent the connectivity of white matter tracts.
Xiaodong Tao GE Global Research Center Improve the DicomToNrrd diffusion tensor conversion tool, and improve 3D Slicer (www.slicer.org) DTI analysis processing
Zhexing Liu The University of North Carolina at Chapel Hill Improve the DTIPrep diffusion tensor quality control tool.