Correction for human head motion in helical x-ray CT

Abstract

Correction for rigid object motion in helical CT can be achieved by reconstructing from a modified source-detector orbit, determined by the object motion during the scan. This ensures that all projections are consistent, but it does not guarantee that the projections are complete in the sense of being sufficient for exact reconstruction. We have previously shown with phantom measurements that motion-corrected helical CT scans can suffer from data-insufficiency, in particular for severe motions and at high pitch. To study whether such data-insufficiency artefacts could also affect the motion-corrected CT images of patients undergoing head CT scans, we used an optical motion tracking system to record the head movements of 10 healthy volunteers while they executed each of the 4 different types of motion ('no', slight, moderate and severe) for 60 s. From these data we simulated 354 motion-affected CT scans of a voxelized human head phantom and reconstructed them with and without motion correction. For each simulation, motion-corrected (MC) images were compared with the motion-free reference, by visual inspection and with quantitative similarity metrics. Motion correction improved similarity metrics in all simulations. Of the 270 simulations performed with moderate or less motion, only 2 resulted in visible residual artefacts in the MC images. The maximum range of motion in these simulations would encompass that encountered in the vast majority of clinical scans. With severe motion, residual artefacts were observed in about 60% of the simulations. We also evaluated a new method of mapping local data sufficiency based on the degree to which Tuy's condition is locally satisfied, and observed that areas with high Tuy values corresponded to the locations of residual artefacts in the MC images. We conclude that our method can provide accurate and artefact-free MC images with most types of head motion likely to be encountered in CT imaging, provided that the motion can be accurately determined.

An iterative projection‐based motion estimation and compensation scheme for head x‐ray CT

“…We have shown previously that optical motion tracking methods are effective, even for very severe motion. 5,6 As shown in Sec. 3.C, the proposed method can refine the tracker based motion estimation.…”

“…Details about measuring these motions are given in Ref. 6. The phantom was a 3D voxelized phantom from the Visible Human Project.…”

“…10. Box plots of improvement over reconstructed planes of each individual study -simulation studies (1)(2)(3)(4)(5)(6), phantom scan (7). Left: RMSE improvement.…”

“…2 In practice, it is difficult to completely eliminate motion, and compensating motion artifacts is of considerable general interest in tomography. A variety of methods for assessing motion in CT exist, including directly estimating motion using a camera system with visual markers [3][4][5][6] or without markers. 7 Artificial or anatomical landmarks can be also tracked in the image or projection domains.…”

“…Relatively few studies have been done for clinical helical CT, and some of those require additional measurement to acquire the motion. [3][4][5][6] In this study, we propose an approach to reduce or eliminate motion artifacts in helical CT reconstruction. The proposed motion estimation and compensation method only needs the measured raw data.…”