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Tomographic image reconstruction from reduced projection data.

机译:从减少的投影数据中重建断层图像。

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摘要

X-ray computed tomography (CT) is a dominant imaging tool in medical diagnosis, monitoring, and assessment. In many of the medical applications of CT, one is only interested in information about certain regions and/or organs within the imaged subject. Therefore, it is desirable to have scanning configurations, including x-ray source trajectories and illumination coverages, and reconstruction algorithms that yield images only in targeted regions of interest (ROIs) within the subject from reduced projection data. Most currently available CT imaging techniques accommodate a limited set of scanning configurations and, more importantly, require complete x-ray-illumination coverage of the subject cross sections, they are not applicable to ROI imaging. In this thesis, we have developed and investigated innovative scanning configurations and novel reconstruction algorithms for obtaining ROI images from reduced projection data in CT, which can reduce the scanning time, lower the radiation dose and scatter, and improve. Based upon the concept of chord, we have developed and evaluated algorithms for image reconstruction from reduced data acquired in circular fan-beam and helical cone-beam scans, which can exactly reconstruct an image within an ROI from reduced data. Moreover, the chord-based algorithms have been extended to the scans with some pratically useful trajectories and detector shapes. We have also studied the noise properties of chord-based image reconstructions from fan- and cone-beam projection data, and a rebinned algorithm has been proposed for improving the noise properties of our proposed algorithms. We have tailored these algorithms to the clinical data acquired from an advanced CT scanner with state-of-the-art technologies. We have tailored these algorithms to the clinical data acquired from an advanced CT scanner with state-of-the-art technologies. Finally, we have proposed a chordless algorithm for reconstructing images within an ROI from a reduced-scan circular sinusoidal scan.
机译:X射线计算机断层扫描(CT)是医学诊断,监视和评估中的主要成像工具。在CT的许多医学应用中,人们仅对有关成像对象内某些区域和/或器官的信息感兴趣。因此,期望具有包括X射线源轨迹和照明范围在内的扫描配置,以及重构算法,该重构算法仅根据缩小的投影数据在对象内的目标感兴趣区域(ROI)中产生图像。目前,大多数可用的CT成像技术只能容纳有限的一组扫描配置,更重要的是,需要对对象横截面进行完整的X射线照射覆盖,它们不适用于ROI成像。在本文中,我们开发并研究了新颖的扫描配置和新颖的重建算法,以从CT中减少的投影数据中获取ROI图像,从而可以减少扫描时间,降低辐射剂量和散射并改善图像。基于和弦的概念,我们已经开发并评估了从圆形扇形束和螺旋锥束扫描中获取的缩小数据中重建图像的算法,这些算法可以从缩小数据中准确地在ROI中重建图像。此外,基于和弦的算法已扩展到具有一些实用的轨迹和检测器形状的扫描。我们还研究了从扇形和锥形束投影数据中基于弦的图像重建的噪声特性,并提出了一种重新组合算法来改善我们提出的算法的噪声特性。我们针对这些算法进行了调整,以适应使用先进技术从高级CT扫描仪获取的临床数据。我们针对这些算法进行了调整,以适应使用先进技术从高级CT扫描仪获取的临床数据。最后,我们提出了一种无弦算法,用于通过减少扫描的圆形正弦扫描在ROI内重建图像。

著录项

  • 作者

    Xia, Dan.;

  • 作者单位

    The University of Chicago.;

  • 授予单位 The University of Chicago.;
  • 学科 Health Sciences Radiology.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 260 p.
  • 总页数 260
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 宗教;
  • 关键词

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