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用于冠状动脉介入治疗的X射线图像的前瞻性运动校正。

Prospective motion correction of X-ray images for coronary interventions.

作者信息

Shechter Guy, Shechter Barak, Resar Jon R, Beyar Rafael

机构信息

Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa 31096, Israel.

出版信息

IEEE Trans Med Imaging. 2005 Apr;24(4):441-50. doi: 10.1109/tmi.2004.839679.

Abstract

A method for prospective motion correction of X-ray imaging of the heart is presented. A 3D + t coronary model is reconstructed from a biplane coronary angiogram obtained during free breathing. The deformation field is parameterized by cardiac and respiratory phase, which enables the estimation of the state of the arteries at any phase of the cardiac-respiratory cycle. The motion of the three-dimensional (3-D) coronary model is projected onto the image planes and used to compute a dewarping function for motion correcting the images. The use of a 3-D coronary model facilitates motion correction of images acquired with the X-ray system at arbitrary orientations. The performance of the algorithm was measured by tracking the motion of selected left coronary landmarks using a template matching cross-correlation. In three patients, we motion corrected the same images used to construct their 3D + t coronary model. In this best case scenario, the algorithm reduced the motion of the landmarks by 84%-85%, from mean RMS displacements of 12.8-14.6 pixels to 2.1-2.2 pixels. Prospective motion correction was tested in five patients by building the coronary model from one dataset, and correcting a second dataset. The patient's cardiac and respiratory phase are monitored and used to calculate the appropriate correction parameters. The results showed a 48%-63% reduction in the motion of the landmarks, from a mean RMS displacement of 11.5-13.6 pixels to 4.4-7.1 pixels.

摘要

本文提出了一种用于心脏X射线成像的前瞻性运动校正方法。从自由呼吸期间获得的双平面冠状动脉血管造影重建三维(3D)+时间冠状动脉模型。变形场由心脏和呼吸相位参数化,这使得能够估计心脏-呼吸周期任何阶段的动脉状态。三维(3D)冠状动脉模型的运动投影到图像平面上,并用于计算用于对图像进行运动校正的去扭曲函数。使用三维冠状动脉模型有助于对用X射线系统在任意方向获取的图像进行运动校正。通过使用模板匹配互相关跟踪选定的左冠状动脉标志物的运动来测量算法的性能。在三名患者中,我们对用于构建其三维+时间冠状动脉模型的相同图像进行了运动校正。在这种最佳情况下,该算法将标志物的运动减少了84%-85%,平均均方根位移从12.8-14.6像素减少到2.1-2.2像素。通过从一个数据集构建冠状动脉模型并校正第二个数据集,在五名患者中测试了前瞻性运动校正。监测患者的心脏和呼吸相位,并用于计算适当的校正参数。结果表明,标志物的运动减少了48%-63%,平均均方根位移从11.5-13.6像素减少到4.4-7.1像素。

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