Joint Estimation of Image and Deformation Parameters in Tomographic Image Reconstruction

Abstract

We consider an emission tomography reconstruction problem in which projection measurements from several successive time frames are available. Two strategies for doing motion-corrected image reconstruction are compared. In the first strategy, separate images are reconstructed from the measurements at each time frame. They are then consolidated by post-registration and averaging procedures. In the second strategy, parameters to describe the effects of motion are added to the statistical model of the projections. Joint maximum likelihood estimation of image and motion parameters is then carried out.