Non-rigid Groupwise Image Registration for Motion Compensation in Quantitative MRI
Quantitative magnetic resonance imaging (qMRI) aims to extract quantitative parameters representing tissue properties from a series of images by modeling the image acquisition process. This requires the images to be spatially aligned but, due to patient motion, anatomical structures in the consecutive images may be misaligned. In this work, we propose a groupwise non-rigid image registration method for motion compensation in qMRI. The method minimizes a dissimilarity measure based on principal component analysis (PCA), exploiting the fact that intensity changes can be described by a low-dimensional acquisition model. Using an unbiased groupwise formulation of the registration problem, there is no need to choose a reference image as in conventional pairwise approaches. The method was evaluated on three applications: modified Look-Locker inversion recovery T 1 mapping in a porcine myocardium, black-blood variable flip-angle T 1 mapping in the carotid artery region, and apparent diffusion coefficient (ADC) mapping in the abdomen. The method was compared to a conventional pairwise alignment that uses a mutual information similarity measure. Registration accuracy was evaluated by computing precision of the estimated parameters of the qMRI model. The results show that the proposed method performs equally well or better than an optimized pairwise approach and is therefore a suitable motion compensation method for a wide variety of qMRI applications.
Keywordsgroupwise image registration quantitative MRI motion compensation T1 mapping ADC mapping principal component analysis
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