Constrained Maximum Likelihood Estimation of the Diffusion Kurtosis Tensor Using a Rician Noise Model

被引:96
作者
Veraart, Jelle [1 ]
Van Hecke, Wim [1 ,2 ,3 ]
Sijbers, Jan [1 ]
机构
[1] Univ Antwerp, Dept Phys, Vis Lab, B-2020 Antwerp, Belgium
[2] Univ Antwerp, Univ Antwerp Hosp, Dept Radiol, B-2020 Antwerp, Belgium
[3] Catholic Univ Louvain, Univ Hosp, Dept Radiol, B-3000 Louvain, Belgium
关键词
DKI; maximum likelihood; Rician noise; parameter estimation; constraint; GAUSSIAN WATER DIFFUSION; BRAIN; MRI; OPTIMIZATION; REGISTRATION; MOTION; ROBUST;
D O I
10.1002/mrm.22835
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
A computational framework to obtain an accurate quantification of the Gaussian and non-Gaussian component of water molecules' diffusion through brain tissues with diffusion kurtosis imaging, is presented. The diffusion kurtosis imaging model quantifies the kurtosis, the degree of non-Gaussianity, on a direction dependent basis, constituting a higher order diffusion kurtosis tensor, which is estimated in addition to the well-known diffusion tensor. To reconcile with the physical phenomenon of molecular diffusion, both tensor estimates should lie within a physically acceptable range. Otherwise, clinically and artificially significant changes in diffusion (kurtosis) parameters might be confounded. To guarantee physical relevance, we here suggest to estimate both diffusional tensors by maximizing the joint likelihood function of all Rician distributed diffusion weighted images given the diffusion kurtosis imaging model while imposing a set of nonlinear constraints. As shown in this study, correctly accounting for the Rician noise structure is necessary to avoid significant overestimation of the kurtosis values. The performance of the constrained estimator was evaluated and compared to more commonly used strategies during simulations. Human brain data were used to emphasize the need for constrained estimators as not imposing the constraints give rise to constraint violations in about 70% of the brain voxels. Magn Reson Med 66:678-686,2011. (C)2011 Wiley-Liss, Inc.
引用
收藏
页码:678 / 686
页数:9
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