Suppr超能文献

比较分析与代数方法在运动补偿的胸部锥形束 CT 重建中的应用。

Comparison of analytic and algebraic methods for motion-compensated cone-beam CT reconstruction of the thorax.

机构信息

Department of Radiation Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, 1066 CX Amsterdam, The Netherlands.

出版信息

IEEE Trans Med Imaging. 2009 Oct;28(10):1513-25. doi: 10.1109/TMI.2008.2008962. Epub 2009 Feb 10.

Abstract

Respiratory motion is a major concern in cone-beam (CB) computed tomography (CT) of the thorax. It causes artifacts such as blur, streaks, and bands, in particular when using slow-rotating scanners mounted on the gantry of linear accelerators. In this paper, we compare two approaches for motion-compensated CBCT reconstruction of the thorax. The first one is analytic; it is heuristically adapted from the method of Feldkamp, Davis, and Kress (FDK). The second one is algebraic: the system of linear equations is generated using a new algorithm for the projection of deformable volumes and solved using the Simultaneous Algebraic Reconstruction Technique (SART). For both methods, we propose to estimate the motion on patient data using a previously acquired 4-D CT image. The methods were tested on two digital and one mechanical motion-controlled phantoms and on a patient dataset. Our results indicate that the two methods correct most motion artifacts. However, the analytic method does not fully correct streaks and bands even if the motion is perfectly estimated due to the underlying approximation. In contrast, the algebraic method allows us full correction of respiratory-induced artifacts.

摘要

胸部锥形束(CB)计算机断层扫描(CT)中,呼吸运动是一个主要关注点。当使用安装在直线加速器龙门架上的慢速旋转扫描仪时,它会导致模糊、条纹和条带等伪影。在本文中,我们比较了两种用于胸部运动补偿 CBCT 重建的方法。第一种是解析方法;它是从 Feldkamp、Davis 和 Kress(FDK)方法中启发式地改编而来的。第二种是代数方法:使用用于变形体积投影的新算法生成线性方程组,并使用同时代数重建技术(SART)进行求解。对于这两种方法,我们建议使用先前获取的 4D CT 图像来估计患者数据上的运动。该方法在两个数字和一个机械运动控制的体模以及一个患者数据集上进行了测试。我们的结果表明,两种方法都可以纠正大多数运动伪影。然而,由于基础近似,即使运动得到完美估计,解析方法也不能完全纠正条纹和条带。相比之下,代数方法允许我们完全纠正呼吸引起的伪影。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验