A novel technique for mitigating motion artifacts in 3D brain imaging systems

Over the past several years,there have been substantial improvements in the area ofthree-dimensional (3d) cone-beam computed tomography (ct) imaging systems. nevertheless, moreimprovement is needed to detect and mitigate motion artifacts in the clinical follow-up of neurologicalpatients with multiple sclerosis, tumors, and stroke, etc., in which failure to detect motion artifacts oftenleads to misdiagnosis of disease. in this paper, we propose a marker-based innovative approach to detectand mitigate motion artifacts in 3d cone-beam brain ct systems without using any external motiontracking sensors. motion is detected by comparing the motion-free ideal marker projections and thecorresponding measured marker projections. once motion is detected, motion parameters (six degrees-offreedomof motion) are estimated using a numerical optimization technique. artifacts, caused by motions,are mitigated in the back projection stage of the 3d reconstruction process by correcting the position ofevery reconstruction voxel according to the estimated motion parameters. we refer to this algorithmas the mb_fdk (marker-based feldkempdaviskress) algorithm. mb_fdk has been evaluated on amodified 3d shepplogan phantom with a range of simulated motion. simulation results demonstratea quantitative and qualitative validation of motion detection and artifact mitigation techniques.