Mitigating motion artifacts in FDK based 3D Cone-beam Brain Imaging System using markers

Abstract

Head motion during Computed Tomographic (CT) brain imaging studies can adversely affect the reconstructed image through distortion, loss of resolution and other related artifacts. In this paper, we propose a marker based innovative approach to detect and mitigate motion artifacts in three dimensional cone-beam brain CT systems without using any external motion tracking sensor. Motion is detected using correlations between the adjacent projections. Once motion is detected, motion parameters (i.e. six degrees-of-freedom of motions) are estimated using a numerical optimization technique. Artifacts, caused by motions, are mitigated by using a modified form Feldkemp-Davis-Kress (FDK) algorithm which uses the estimated motion parameters in back-projection stage. The proposed approach has been evaluated on a modified three-dimensional Shepp-Logan phantom with a range of simulated motions. Simulation results demonstrate a quantitative and qualitative validation of motion detection and artifacts mitigation technique.