Suppr超能文献

基于数据一致性的扇束CT平移运动伪影减少

Data consistency based translational motion artifact reduction in fan-beam CT.

作者信息

Yu Hengyong, Wei Yuchuan, Hsieh Jiang, Wang Ge

机构信息

CT/Micro-CT Lab, Department of Radiology, University of Iowa, Iowa City 52242, USA.

出版信息

IEEE Trans Med Imaging. 2006 Jun;25(6):792-803. doi: 10.1109/tmi.2006.875424.

Abstract

A basic assumption in the classic computed tomography (CT) theory is that an object remains stationary in an entire scan. In biomedical CT/micro-CT, this assumption is often violated. To produce high-resolution images, such as for our recently proposed clinical micro-CT (CMCT) prototype, it is desirable to develop a precise motion estimation and image reconstruction scheme. In this paper, we first extend the Helgason-Ludwig consistency condition (HLCC) from parallel-beam to fan-beam geometry when an object is subject to a translation. Then, we propose a novel method to estimate the motion parameters only from sinograms based on the HLCC. To reconstruct the moving object, we formulate two generalized fan-beam reconstruction methods, which are in filtered backprojection and backprojection filtering formats, respectively. Furthermore, we present numerical simulation results to show that our approach is accurate and robust.

摘要

经典计算机断层扫描(CT)理论中的一个基本假设是,在整个扫描过程中物体保持静止。在生物医学CT/微型CT中,这一假设常常不成立。为了生成高分辨率图像,比如用于我们最近提出的临床微型CT(CMCT)原型,开发一种精确的运动估计和图像重建方案是很有必要的。在本文中,当物体发生平移时,我们首先将Helgason-Ludwig一致性条件(HLCC)从平行束几何扩展到扇形束几何。然后,我们提出了一种仅基于HLCC从正弦图估计运动参数的新方法。为了重建运动物体,我们制定了两种广义扇形束重建方法,分别为滤波反投影和反投影滤波格式。此外,我们给出了数值模拟结果,以表明我们的方法准确且稳健。

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