Motion-compensated reconstruction of tomographic image sequences

Abstract

In this paper, we study a motion-compensated approach for simultaneous reconstruction of image frames in a time sequence. We treat the frames in a sequence collectively as a single function of both space and time, and define a temporal prior to account for the temporal correlations in a sequence. This temporal prior is defined in a form of motion-compensation, aimed to follow the curved trajectories of the object motion through space-time. The image frames are then obtained through estimation using the expectation-maximization (EM) algorithm. The proposed algorithm was evaluated using the four-dimensional (4-D) gated mathematical cardiac-torso (gMCAT) D1.01 phantom to simulate gated single photon emission computed tomography (SPECT) perfusion imaging with Tc-99m-sestamibi. Our experimental results demonstrate that the use of motion compensation for reconstruction can lead to significant improvement in image quality and reconstruction accuracy.