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使用先进光流算法对三维正电子发射断层扫描(PET)数据进行呼吸运动校正。

Respiratory motion correction in 3-D PET data with advanced optical flow algorithms.

作者信息

Dawood Mohammad, Buther Florian, Jiang Xiaoyi, Schafers Klaus P

机构信息

Department of Mathematics and Computer Science, University of Münster, 48149 Münster, Germany.

出版信息

IEEE Trans Med Imaging. 2008 Aug;27(8):1164-75. doi: 10.1109/TMI.2008.918321.

Abstract

The problem of motion is well known in positron emission tomography (PET) studies. The PET images are formed over an elongated period of time. As the patients cannot hold breath during the PET acquisition, spatial blurring and motion artifacts are the natural result. These may lead to wrong quantification of the radioactive uptake. We present a solution to this problem by respiratory-gating the PET data and correcting the PET images for motion with optical flow algorithms. The algorithm is based on the combined local and global optical flow algorithm with modifications to allow for discontinuity preservation across organ boundaries and for application to 3-D volume sets. The superiority of the algorithm over previous work is demonstrated on software phantom and real patient data.

摘要

在正电子发射断层扫描(PET)研究中,运动问题是众所周知的。PET图像是在一段较长的时间内形成的。由于患者在PET采集过程中无法屏住呼吸,空间模糊和运动伪影是自然产生的结果。这些可能会导致放射性摄取的错误量化。我们通过对PET数据进行呼吸门控并使用光流算法校正PET图像运动来解决这个问题。该算法基于局部和全局光流算法的组合,并进行了修改,以允许在器官边界处保持不连续性,并应用于三维体积数据集。在软件模拟体模和真实患者数据上证明了该算法相对于先前工作的优越性。

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