Cooper V N, Boone J M, Seibert J A
Department of Radiology, University of California Davis, Sacramento 95831, USA.
Med Phys. 2000 Jan;27(1):66-74. doi: 10.1118/1.598872.
A simulation method is described in this work that aids in quantifying the upper limits of lesion detectability as a function of lesion size, lesion contrast, pixel size, and x-ray exposure for digital x-ray imaging systems. The method entails random lesion placement with subsequent simulated imaging on idealized x-ray detectors with no additive noise and 100% quantum detective efficiency. Lesions of different size and thickness were simulated. Mean (expectation) lesion signal-to-noise ratios (LSNRs) were calculated and receiver operating characteristic (ROC) curves were constructed based on LSNR ensembles. Mean (expectation) values of the areas under the ROC curves were calculated for lesions of varying size on pixel arrays of varying size at different exposures. Analyses were performed across several parameters, including lesion size, pixel size, and exposure levels representative of various areas of radiography. As expected, lesion detectability increased with lesion size, contrast, pixel size, and exposure. The model suggests that lesion detectability is strongly dependent on the relative alignment (phase) of the lesion with the pixel matrix for lesions on the order of the pixel size.
本文描述了一种模拟方法,该方法有助于量化数字X射线成像系统中病变可检测性的上限,它是病变大小、病变对比度、像素大小和X射线曝光量的函数。该方法需要随机放置病变,随后在无附加噪声且量子检测效率为100%的理想化X射线探测器上进行模拟成像。模拟了不同大小和厚度的病变。计算了平均(期望)病变信噪比(LSNR),并基于LSNR总体构建了接收者操作特征(ROC)曲线。针对不同曝光量下不同大小像素阵列上不同大小的病变,计算了ROC曲线下面积的平均(期望)值。对包括病变大小、像素大小和代表各种放射区域的曝光水平在内的多个参数进行了分析。正如预期的那样,病变可检测性随着病变大小、对比度、像素大小和曝光量的增加而提高。该模型表明,对于像素大小量级的病变,病变可检测性强烈依赖于病变与像素矩阵的相对对齐(相位)。