[논문]Cardiac Motion Correction for Helical CT Scan With an Ordinary Pitch

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

doi:10.1109/TMI.2018.2817594

[해외논문] Cardiac Motion Correction for Helical CT Scan With an Ordinary Pitch

IEEE transactions on medical imaging, v.37 no.7, 2018년, pp.1587 - 1596

Kim, Seungeon (School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea) , Chang, Yongjin (School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea) , Ra, Jong Beom (School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea)

Abstract ▼ AI-Helper

Cardiac X-ray computed tomography (CT) imaging is still challenging due to the cardiac motion during CT scanning, which leads to the presence of motion artifacts in the reconstructed image. In response, many cardiac X-ray CT imaging algorithms have been proposed, based on motion estimation (ME) and motion compensation (MC), to improve the image quality by alleviating the motion artifacts in the reconstructed image. However, these ME/MC algorithms are mainly based on an axial scan or a low-pitch helical scan. In this paper, we propose a ME/MC-based cardiac imaging algorithm for the data set acquired from a helical scan with an ordinary pitch of around 1.0 so as to obtain the whole cardiac image within a single scan of short time without ECG gating. In the proposed algorithm, a sequence of partial angle reconstructed (PAR) images is generated by using consecutive parts of the sinogram, each of which has a small angular span. Subsequently, an initial 4-D motion vector field (MVF) is obtained using multiple pairs of conjugate PAR images. The 4-D MVF is then refined based on an image quality metric so as to improve the quality of the motion-compensated image. Finally, a time-resolved cardiac image is obtained by performing motion-compensated image reconstruction by using the refined 4-D MVF. Using digital XCAT phantom data sets and a human data set commonly obtained via a helical scan with a pitch of 1.0, we demonstrate that the proposed algorithm significantly improves the image quality by alleviating motion artifacts.

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