Simultaneous reconstruction and three-dimensional motion estimation for gated myocardial emission tomography

A new method for simultaneous image reconstruction and wall-motion estimation in gated myocardial emission tomography (ET) is presented. We implemented the method using simulated phantoms and evaluated the performance of the method.; To reduce the blur in the images induced by the heart motion, gated ET uses the patient's electrocardiogram (ECG) to trigger and acquire a time sequence of image frames, each capturing a particular stage of the cardiac cycle. However, the individual gated image frames reconstructed by conventional image-reconstruction algorithms are very noisy due to the reduced counts of detected gamma rays.; Non-rigid deformation of myocardium can be characterized by means of a vector field called the motion field, which describes the relative displacement of each voxel, and thus establishes a voxel-intensity correspondence between two image frames. Previous research incorporated a deformable elastic material model into a motion-estimation algorithm to more accurately describe the deformation of the myocardium. The estimated motion field was used to warp each frame to a common reference volume. All warped frames were then recombined to generate an improved composite image.; Instead of using the motion to warp and recombine frames, our simultaneous estimation method uses the motion field to regularize the individual reconstructed image frames, whereas the projection data are also a constraint for motion estimation. Thus, the simultaneous method is expected to improve the motion-estimation accuracy and the image quality of individual frames, relative to the independent motion-estimation and image-reconstruction methods.; We presented the mathematical formulation of the simultaneous estimation method, followed by an optimization algorithm. The algorithm was implemented on a simulated geometric phantom and a realistic non-uniform-rational-B-splines-based cardiac torso (MCAT) phantom. We evaluated the simultaneous method in terms of the motion accuracy and the image quality. A numerical observer model was used to assess the detectability provided by the simultaneous method for the defect detection task. Results showed that the simultaneous method produces better motion accuracy and image quality, relative to the independent motion estimation and an alternative image-reconstruction algorithm.