Automated registration of dynamic MR images for the quantification of myocardial perfusion

Bidaut, Luc M. and Valee, Jean-Paul (2001) Automated registration of dynamic MR images for the quantification of myocardial perfusion. Journal of Magnetic Resonance Imaging, 13 (4). pp. 648-655. ISSN 1053-1807

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Item Type:Article
Item Status:Live Archive

Abstract

Cardiac dynamic magnetic resonance imaging (MRI) after contrast media injection suffers from motion induced by free breathing during acquisition. This work presents an automated approach for motion correction of the heart. The registration is based on the multipass/ multiresolution iterative minimizing of intrinsic differences between each image and a reference image coupled to a two-dimensional/3 parameters rigid body correction. The efficiency of this correction method was evaluated with anatomical landmarks, various cost functions, and for a compartment model fit of the data with 2 parameters: K1, the blood to myocardium transfer coefficient; and Vd, the distribution volume of the contrast media. The variability of K1 and Vd, derived from the fit of the registered images (using the manual correction as a gold standard), was significantly reduced by comparison with the variability obtained from the uncorrected images (P < 0.04). This motion correction method also clearly improves the analysis of dynamic cardiac MRI after contrast media injection in comparison to manual correction. © 2001 Wiley-Liss, Inc.

Keywords:contrast medium, gadolinium pentetate, article, breathing, contrast enhancement, data analysis, device, drug effect, first pass effect, heart muscle perfusion, human, human tissue, image analysis, image quality, nuclear magnetic resonance imaging, priority journal, quantitative diagnosis, Contrast Media, Coronary Circulation, Coronary Disease, Humans, Image Processing, Computer-Assisted, Least-Squares Analysis, Magnetic Resonance Imaging, Movement, Perfusion, Respiratory Physiology
Subjects:F Physical Sciences > F350 Medical Physics
Divisions:College of Science > School of Computer Science
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ID Code:24156
Deposited On:19 Oct 2016 10:12

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