DBP:HD Data Collaborators

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.