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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