Perelman School of Medicine at the University of Pennsylvania

Section for Biomedical Image Analysis (SBIA)

participating with CBICA

Diffusion measures: HARDI Invariants


We have designed rotationally invariant features of High Angular Resolution Diffusion Imaging (HARDI) data. These measures quantify the complexity of the angular diffusion profile modeled using a higher order model, thereby giving more information than classical diffusion tensor-derived parameters. The method is based on the spherical harmonic (SH) representation of the angular diffusion information, and is generalizable to a range of HARDI reconstruction models. We have compute a set of 12 or 25 rotationally invariant measures representative of the underlying white matter for the rank-4 or rank-6 SH representation of the apparent diffusion coefficient profile, respectively. These measures are currently being applied to datasets in autism demonstrate their ability to characterize white matter, especially complex white matter found in regions of fiber crossings and derive new biomarkers for HARDI and can be used for HARDI-based population analysis.

Collaborators
Publications
  1. Emmanuel Caruyer, Ragini Verma, On facilitating the use of HARDI in population studies by creating rotation-invariant markers. Medical Image Analysis, 20(1), 87-96, February 2015, DOI: 10.1016/j.media.2014.10.009
  2. Emmanuel Caruyer, Ragini Verma. Rotation-invariant measures for population study in HARDI. ISMRM, May 2014, Milan, Italy. 2014. <hal-00944646>