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螺旋 CT 扫描中采用普通螺距的心脏运动校正。

Cardiac Motion Correction for Helical CT Scan With an Ordinary Pitch.

出版信息

IEEE Trans Med Imaging. 2018 Jul;37(7):1587-1596. doi: 10.1109/TMI.2018.2817594.

Abstract

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.

摘要

心脏 X 射线计算机断层扫描(CT)成像仍然具有挑战性,因为在 CT 扫描期间心脏会运动,这会导致重建图像中出现运动伪影。为此,已经提出了许多心脏 X 射线 CT 成像算法,这些算法基于运动估计(ME)和运动补偿(MC),通过减轻重建图像中的运动伪影来提高图像质量。然而,这些 ME/MC 算法主要基于轴向扫描或低螺距螺旋扫描。在本文中,我们提出了一种基于 ME/MC 的心脏成像算法,用于从普通螺距约为 1.0 的螺旋扫描中获取数据集,以便在没有心电图门控的情况下,在单次短时间扫描中获得整个心脏图像。在提出的算法中,通过使用正弦图的连续部分生成一系列部分角度重建(PAR)图像,每个部分具有小的角度跨度。随后,使用多对共轭 PAR 图像获得初始的 4D 运动矢量场(MVF)。然后,根据图像质量度量对 4D MVF 进行细化,以提高运动补偿图像的质量。最后,通过使用细化的 4D MVF 进行运动补偿图像重建来获得时分辨的心脏图像。使用数字 XCAT 体模数据集和通常通过螺距为 1.0 的螺旋扫描获得的人体数据集,我们证明了该算法通过减轻运动伪影显著提高了图像质量。

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