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Robust Myelin Quantitative Imaging from Multi-echo T2 MRI Using Edge Preserving Spatial Priors
Xiaobo Shen1, Thanh D. Nguyen2, Susan A. Gauthier2, and Ashish Raj2
1Department of Computer Science, Cornell University, Ithaca, NY, USA
xs83@cornell.edu
2Department of Radiology, Weill Cornell Medical College, New York, NY, USA
tdn2001@med.cornell.edu
sag2015@med.cornell.edu
asr2004@med.cornell.edu
Abstract. Demyelinating diseases such as multiple sclerosis cause changes in the brain white matter microstructure. Multi-exponential T2 relaxometry is a powerful technology for detecting these changes by generating a myelin water fraction (MWF) map. However, conventional approaches are subject to noise and spatial in-consistence. We proposed a novel approach by imposing spatial consistency and smoothness constraints. We first introduce a two-Gaussian model to approximate the T2 distribution. Then an expectation-maximization framework is introduced with an edge-preserving prior incorporated. Three-dimensional multi-echo MRI data sets were collected from three patients and three healthy volunteers. MWF maps ob-tained using the conventional, Spatially Regularized Non-negative Least Squares (srNNLS) algorithm as well as the proposed algorithm are compared. The proposed method provides MWF maps with improved depiction of brain structures and significantly lower coefficients of variance in various brain regions.
Keywords: T2 relaxometry, myelin water fraction, edge-preserving priors
LNCS 8149, p. 622 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2013