Meeting Banner
Abstract #3538

Multichannel Diffusion MR Image Reconstruction: How to Reduce Elevated Noise Floor and Improve Fiber Orientation Estimation

Christophe Lenglet1, Stamatios Sotiropoulos2, Steen Moeller1, Junqian Xu1, Edward J. Auerbach1, Essa Yacoub1, David Feinberg3, Kawin Setsompop4, Lawrence Walds

1Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States; 2Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom; 3Advanced MRI Technologies, Sebastopol, CA, United States; 4Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States

Signal intensity in magnitude MR images follows a Rician distribution when single-channel receiver coils are employed. For multi-channel coil acquisitions, noise properties change, and the observed noise levels depend on the image reconstruction method used to combine information from different coils. This is problematic for diffusion-weighted MRI, where any artificial elevation of the noise floor limits the ability to properly quantify the signal attenuation and, ultimately, estimate fiber orientation for tractography. We propose to use a multi-channel SENSE1 reconstruction of GRAPPA un-aliased data, which exhibits Rician noise properties, and demonstrate its advantage over the RSoS reconstruction for fiber orientation estimation.