Tikhonov regularization and related methods are widely used in recovering relaxation time
distributions in magnetic resonance relaxometry. Regularization optimization methods such
as the L-curve and generalized cross-validation (GCV) identify a single optimized solution
as the best approximation to the underlying distribution. In contrast, we propose a new
reconstruction method, Multi-Reg, incorporating a range of regularized solutions. Multi-Reg
is based on a dictionary of noise-corrupted regularized reconstructions of distribution basis …

J35. 00004: Multi-Regularization Reconstruction of One-Dimensional T 2 Distributions in
Magnetic Resonance Relaxometry* Abstract Presenter: Richard Spencer (National Institutes
of Health-NIH) Authors: Chuan Bi (National Institutes of Health-NIH) Yvonne M. Ou
(Mathematical Sciences, University of Delaware) Wenshu Qian (National Institutes of Health-
NIH) You Zhuo (National Institutes of Health-NIH) Richard Spencer (National Institutes of
Health-NIH) Measurements of T 2 relaxation time distributions in magnetic resonance …