Meeting Banner
Abstract #3149

Robust Fiber Response Function Estimation for Deconvolution Based Diffusion MRI Methods

Chantal M.W. Tax1, Ben Jeurissen2, Max A. Viergever1, Alexander Leemans1

1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands; 2Department of Physics, University of Antwerp, iMinds-Vision Lab, Antwerp, Belgium

Spherical deconvolution techniques characterize complex fiber configurations within a voxel. Currently, the response function (RF) needed for deconvolution is derived from voxels with the highest fractional anisotropy (FA). Poor accuracy of FA in the high b-value and low SNR regime and the ad-hoc nature of selecting these voxels complicate RF estimation, which may lead to the detection of false positive peaks and altered peak magnitudes. In this work, the computation of the RF is optimized by excluding "crossing fibers" voxels in a recursive framework, which does not rely on FA. Feasibility is demonstrated on simulated and real diffusion MRI data.

Abstract PDF Presentation Video

Keywords

absent according accumulating acquisition added akin angular anymore appealing approaches automated axially bundle calibration characterize collected colored complex computation configurations consisting constrain constrained constraints contains corrected created crossing currently deconvolution defined defining dependence despite detail deviations differently diffusion displays distinctly distribution distributions dominant eddy either estimation evidence excluding exist false fatter feasible fiber fibers findings fractional fractions framework free function glyphs gradient graph great hand hardware heterogeneity human influences instance inter intra investigating iteration largest last lead magnitude majority mask measures medical model motion need newton noise optimization optimized orientation orientations oriented parker particular peak peaks performance physics population populations positive positives press processing profile qualitative real recent recursive referring rely reorient reoriented represents required resolution resolutions response robust sampling sciences select selected sensitivity settings severely similarities simulated simulation simulations smaller sphere step steps straight subject sufficiently suggest symmetric tensor termed threshold trade true uniformly vast versus vision volume white yields