Weber D M, Molloi S Y, Folts J D, Peppler W W, Mistretta C A
Department of Medical Physics, University of Wisconsin, Madison.
Invest Radiol. 1991 Jul;26(7):649-54.
The application of dual energy (DE) subtraction techniques to quantitative coronary arteriography (QCA) has the advantage of removing the tissue signal surrounding the vessel profile. We have compared the performance of two geometric QCA algorithms on DE-subtracted and -unsubtracted images to determine, for each, if DE subtraction is advantageous. The two algorithms under study were an edge detection algorithm and a Fourier analysis-based algorithm. For each algorithm, linear regression analysis was performed of measured cross-sectional area (CSA) versus actual CSA of coronary vessel phantoms. The edge detection algorithm was found to have improved precision (P less than .05) when applied to the DE-subtracted images. The Fourier analysis algorithm, however, was not effected by the DE subtraction. Among the unsubtracted image results, the Fourier measurements were more accurate (P less than .05) than the edge detection measurements. We conclude that the benefits to edge detection QCA of DE tissue subtraction outweigh the disadvantages of increased image noise and possible misregistration artifacts. However, the Fourier algorithm is relatively insensitive to tissue signal variations.
双能(DE)减影技术应用于定量冠状动脉造影(QCA)的优势在于去除血管轮廓周围的组织信号。我们比较了两种几何QCA算法在DE减影图像和未减影图像上的性能,以确定DE减影对每种算法是否具有优势。所研究的两种算法分别是边缘检测算法和基于傅里叶分析的算法。对于每种算法,对冠状动脉模型的测量横截面积(CSA)与实际CSA进行线性回归分析。结果发现,边缘检测算法应用于DE减影图像时精度有所提高(P小于0.05)。然而,傅里叶分析算法不受DE减影的影响。在未减影图像结果中,傅里叶测量比边缘检测测量更准确(P小于0.05)。我们得出结论,DE组织减影对边缘检测QCA的益处超过了图像噪声增加和可能的配准伪影等缺点。然而,傅里叶算法对组织信号变化相对不敏感。