Stack transition artifact removal (STAR) for cardiac CT.

Abstract

In cardiac computed tomography (CT), irregular motion may lead to unique artifacts for scanners with a longitudinal collimation that does not cover the entire heart. Given partial coverage, subvolumes, or stacks, may be reconstructed and used to assemble a final CT volume. Irregular motion, for example, due to cardiac arrhythmia or breathing, may cause mismatch between neighboring stacks and therefore discontinuities within the final CT volume. The aim of this work is the removal of the discontinuities that are hereafter referred to as stack transition artifacts. A stack transition artifact removal (STAR) is achieved using a symmetric deformable image registration. A symmetric Demons algorithm was implemented and applied to stacks to remove mismatch and therefore the stack transition artifacts. The registration can be controlled with one parameter that affects the smoothness of the deformation vector field (DVF). The latter is crucial for realistically transforming the stacks. Different smoothness settings as well as an entirely automatic parameter selection that considers the required deformation magnitude for each registration were tested with patient data. Thirteen datasets were evaluated. Simulations were performed on two additional datasets. STAR considerably improved image quality while computing realistic DVFs. Discontinuities, for example, appearing as breaks or cuts in coronary arteries or cardiac valves, were removed or considerably reduced. A constant smoothing parameter that ensured satisfactory results for all datasets was found. The automatic parameter selection was able to find a proper setting for each individual dataset. Consequently, no over regularization of the DVF occurred that would unnecessarily limit the registration accuracy for cases with small deformations. The automatic parameter selection yielded the best overall results and provided a registration method for cardiac data that does not require user input.