부산대학교 도서관

Even for short protocols (<1 min), head movement can compromise accurate haemodynamic modelling of cerebral CT perfusion (CTP) imaging in acute stroke. Frame-to-frame registration is the most common form of retrospective correction but neglects the fact that motion is continuous, not discrete. By contrast, external tracking devices provide continuous motion monitoring and thereby the opportunity to fully correct the acquired data for motion. The aim of this study was to characterise the Intel D415 stereo depth camera, a compact low-cost markerless tracking device, in terms of its suitability for retrospective CTP motion correction. The results showed that jitter was stable, and thermally-induced pose drift was {\le} 1.5 mm and {\le} 0.5{\deg} during the first 10-20 min, after which it also became stable. For static poses, the mean difference between the Intel D415 motion estimates and ground-truth poses for a head phantom was {\le} 1.24 \pm 0.01 mm and {\le} 0.68 \pm 0.01{\deg} for position and orientation, respectively. For dynamic poses measured while a head phantom travelled smooth continuous trajectories with median speed 0.031 ms^(-1) (speed range 0-0.500 ms^(-1)), the root-mean-square-error (RMSE) was {\le} 1.40 \pm 0.12 mm and {\le} 0.24 \pm 0.02{\deg}. When tracking a simulated patient head trajectory derived from a clinical CTP scan, the average RMSE was {\le} 0.86 \pm 0.03 mm and {\le} 0.16 \pm 0.03{\deg}. Tracking the head motion of a human volunteer inside a clinical CT scanner, the average RMSE was {\le} 2.72 \pm 0.24 mm and {\le} 0.55 \pm 0.07{\deg}. Overall, our results suggest that a single D415 tracking system can achieve promising pose estimation accuracy, though still worse than typical brain CT resolution, including CTP. The error is likely to be reduced to a practical level by combining multiple devices and this should be investigated in future work.