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Kinetic Parameter Reconstruction for Motion Compensation in Transmission Tomography

机译:传输层析成像中运动补偿的动力学参数重建

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摘要

Model based iterative reconstruction (MBIR) algorithms have recently been applied to computed tomography and demonstrated superior image quality. This algorithmic framework also provides us the flexibility to incorporate more sophisticated models of the data acquisition process. In this paper, we present the kinetic parameter iterative reconstruction (KPIR) algorithm which estimates voxel values as a function of time in the MBIR framework. We introduce a parametric kinetic model for each voxel, and estimate the kinetic parameters directly from the data. Results on phantom study and clinical data show that the proposed method can significantly reduce motion artifacts in the reconstruction.
机译:基于模型的迭代重建(MBIR)算法最近已应用于计算机断层扫描,并显示出卓越的图像质量。该算法框架还为我们提供了灵活性,使其可以合并更复杂的数据采集过程模型。在本文中,我们提出了动力学参数迭代重建(KPIR)算法,该算法在MBIR框架中估算作为时间函数的体素值。我们为每个体素引入参数动力学模型,并直接从数据中估算动力学参数。幻像研究和临床数据的结果表明,该方法可以显着减少重建过程中的运动伪影。

著录项

  • 来源
    《Computational imaging IX》|2011年|p.78730T.1-78730T.7|共7页
  • 会议地点 San Francisco CA(US)
  • 作者单位

    GE Healthcare Technologies, W-1180, 3000 N Grandview Blvd, Waukesha, WI 53188;

    GE Healthcare Technologies, W-1180, 3000 N Grandview Blvd, Waukesha, WI 53188;

    Department of Electrical Engineering, 275 Fitzpatrick, University of Notre Dame, Notre Dame, IN 46556-5637;

    School of Electrical Engineering, Purdue University, West Lafayette, IN 47907-0501;

    Department of Electrical Engineering, 275 Fitzpatrick, University of Notre Dame, Notre Dame, IN 46556-5637;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 信息处理(信息加工);
  • 关键词

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