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Abstract #3140

A framework for getting the correct T 2 distribution from multiple echo magnitude MRI signal

Ruiliang Bai 1,2 , Cheng Guan Koay 3 , and Peter J Basser 1

1 Section on Tissue Biophysics and Biomimetics, PPITS, NICHD, National Institutes of Health, Bethesda, MD, United States, 2 Biophysics Program, Institute for Physical Science and Technology, University of Maryland, College Park, MD, United States, 3 Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States

The noise-induced bias in the magnitude multi-echo MRI signals causes artifacts in T 2 distributions calculated by conventional inverse Laplace transform (ILT) algorithms, that implicitly assume the noisy signal is always Gaussian distributed. Here we propose a signal transformational framework to map the noisy Rician-distributed magnitude signal back to a Gaussian distribution and then perform an ILT algorithm on the corrected data to obtain an accurate T 2 distribution. Both simulations and experiments validate the efficiency of this approach in correcting these artifacts.

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