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CT心肌灌注测量中的束硬化校正

Beam hardening correction in CT myocardial perfusion measurement.

作者信息

So Aaron, Hsieh Jiang, Li Jian-Ying, Lee Ting-Yim

机构信息

Imaging Program, Lawson Health Research Institute, London, Ontario, Canada.

出版信息

Phys Med Biol. 2009 May 21;54(10):3031-50. doi: 10.1088/0031-9155/54/10/005. Epub 2009 Apr 27.

Abstract

This paper presents a method for correcting beam hardening (BH) in cardiac CT perfusion imaging. The proposed algorithm works with reconstructed images instead of projection data. It applies thresholds to separate low (soft tissue) and high (bone and contrast) attenuating material in a CT image. The BH error in each projection is estimated by a polynomial function of the forward projection of the segmented image. The error image is reconstructed by back-projection of the estimated errors. A BH-corrected image is then obtained by subtracting a scaled error image from the original image. Phantoms were designed to simulate the BH artifacts encountered in cardiac CT perfusion studies of humans and animals that are most commonly used in cardiac research. These phantoms were used to investigate whether BH artifacts can be reduced with our approach and to determine the optimal settings, which depend upon the anatomy of the scanned subject, of the correction algorithm for patient and animal studies. The correction algorithm was also applied to correct BH in a clinical study to further demonstrate the effectiveness of our technique.

摘要

本文提出了一种用于校正心脏CT灌注成像中束硬化(BH)的方法。所提出的算法处理重建图像而非投影数据。它应用阈值来分离CT图像中低衰减(软组织)和高衰减(骨骼和造影剂)物质。每个投影中的BH误差通过分割图像的前向投影的多项式函数来估计。误差图像通过对估计误差的反投影进行重建。然后通过从原始图像中减去缩放后的误差图像来获得BH校正图像。设计了体模来模拟在心脏研究中最常用的人类和动物心脏CT灌注研究中遇到的BH伪影。这些体模用于研究我们的方法是否可以减少BH伪影,并确定针对患者和动物研究的校正算法的最佳设置,这些设置取决于扫描对象的解剖结构。校正算法还应用于临床研究中校正BH,以进一步证明我们技术的有效性。

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