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心脏负荷和静息再定位SPECT图像在模板上的自动配准与对齐。

Automatic registration and alignment on a template of cardiac stress and rest reoriented SPECT images.

作者信息

Declerck J, Feldmar J, Goris M L, Betting F

机构信息

Epidaure Group, INRIA, Sophia-Antipolis, France.

出版信息

IEEE Trans Med Imaging. 1997 Dec;16(6):727-37. doi: 10.1109/42.650870.

Abstract

Single photon emission computed tomography (SPECT) imaging with 201Tl or 99mTc agent is used to assess the location or the extent of myocardial infarction or ischemia. A method is proposed to decrease the effect of operator variability in the visual or quantitative interpretation of scintigraphic myocardial perfusion studies. To effect this, the patient's myocardial images (target cases) are registered automatically over a template image, utilizing a nonrigid transformation. The intermediate steps are: 1) Extraction of feature points in both stress and rest three-dimensional (3-D) images. The images are resampled in a polar geometry to detect edge points, which in turn are filtered by the use of a priori constraints. The remaining feature points are assumed to be points on the edges of the left ventricular myocardium. 2) Registration of stress and rest images with a global affine transformation. The matching method is an adaptation of the iterative closest point algorithm. 3) Registration and morphological matching of both stress and rest images on a template using a nonrigid local spline transformation following a global affine transformation. 4) Resampling of both stress and rest images in the geometry of the template. Optimization of the method was performed on a database of 40 pairs of stress and rest images selected to obtain a wide variation of images and abnormalities. Further testing was performed on 250 cases selected from the same database on the basis of the availability of angiographic results and patient stratification.

摘要

使用201铊或99m锝剂进行单光子发射计算机断层扫描(SPECT)成像,用于评估心肌梗死或缺血的位置或范围。本文提出了一种方法,以减少在心肌灌注闪烁显像研究的视觉或定量解释中操作者变异性的影响。为此,利用非刚性变换将患者的心肌图像(目标病例)自动配准到模板图像上。中间步骤如下:1)在负荷和静息三维(3-D)图像中提取特征点。图像在极坐标几何中重新采样以检测边缘点,然后利用先验约束对边缘点进行滤波。其余特征点被假定为左心室心肌边缘上的点。2)通过全局仿射变换对负荷和静息图像进行配准。匹配方法是对迭代最近点算法的一种改进。3)在全局仿射变换之后,使用非刚性局部样条变换在模板上对负荷和静息图像进行配准和形态学匹配。4)在模板几何中对负荷和静息图像进行重新采样。该方法在一个由40对负荷和静息图像组成的数据库上进行了优化,这些图像经过挑选以获得广泛的图像变化和异常情况。基于血管造影结果的可用性和患者分层,从同一数据库中选取了250例病例进行进一步测试。

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