Joint Reconstruction of 2-D Left Ventricular Displacement and Contours from Tagged Magnetic Resonance Images Using Markov Random Field Edge Prior

and Contours from Tagged Magnetic Resonance Images Using Markov Random Field Edge Prior Litao Yan and Thomas S. Denney, Jr. Department of Electrical Engineering Auburn University Auburn University, Alabama 36849, USA [email protected], [email protected] Abstract Magnetic Resonance (MR) tagging has been shown to be a useful method for non-invasively measuring the deformation of the left ventricle (LV), during the cardiac cycle. By reconstructing a displacement eld based on the movement of the tag lines, one can compute myocardial contraction measures such as strain. Existing methods depend on user-de ned LV contours, which require human intervention and are therefore the biggest bottleneck in the reconstruction process. In this paper we present a method for reconstructing 2-D LV deformation without user-de ned contours. We use a compound Gauss-Markov random eld to model the 2-D vector displacement eld, which is parameterized by two closed and smooth contours. By iteratively optimizing the contours, the displacement eld, and the parameters, we obtain an estimate of the displacement eld and the contours. Experimental results on in vivo human data are presented that demonstrate the accuracy of our algorithm.