The primary goal of this work has been to develop a processing method for gated cardiac emission computed tomography (ECT) that simultaneously reconstructs the pixel intensities of the gated images and estimates the motion of the cardiac wall. The simultaneous reconstruction and motion estimation is achieved using conjugate gradient optimization with an objective function that is dependent on the gated reconstructed images at two time frames and the estimated motion of the object between the two frames. The method was evaluated on simulated phantom data both with and without Poisson noise. With noise-free data, the accuracy of the motion estimate and the quality of the reconstructed images were found to be dependent on the hyperparameter selection. With noisy data, the simultaneous method produced reconstructed images with smaller squared error compared with images reconstructed without motion estimation. In a patient gated myocardial perfusion study, the estimated motion between two frames agreed with subjective assessment of wall motion.
In this paper, we propose and test a new iterative algorithm to simultaneously estimate the nonrigid motion vector fields and the emission images for a complete cardiac cycle in gated cardiac emission tomography. We model the myocardium as an elastic material whose motion does not generate large amounts of strain. As a result, our method is based on minimizing an objective function consisting of the negative logarithm of a maximum likelihood image reconstruction term, the standard biomechanical model of strain energy, and an image matching term that ensures a measure of agreement of intensities between frames. Simulations are obtained using data for the four-dimensional (4-D) NCAT phantom. The data models realistic noise levels in a typical gated myocardial perfusion SPECT study. We show that our simultaneous algorithm produces images with improved spatial resolution characteristics and noise properties compared with those obtained from postsmoothed 4-D maximum likelihood methods. The simulations also demonstrate improved motion estimates over motion estimation using independently reconstructed images.
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