归一化图像噪声作为二维乳房x线摄影性能评估的绝对数量

N. Paruccini, R. Villa, N. Oberhofer
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引用次数: 0

摘要

提出了一种方法,通过暴露一个简单的测试对象,其中包括夹在PMMA板之间的铝阶梯楔,将测量到的噪声等同于铝的厚度。缩放过程将用mmAl表示的图像噪声转化为反映曝光条件的绝对量。定义了第二个量,即与剂量无关的归一化图像噪声。它是每个乳房x光检查单元/模型和幻影设置的特征值,代表了系统在临床条件下的整体检测效率的度量。在较宽的平均腺剂量(AGD)范围内,对不同制造商和检测技术的8台乳房x线照相术单元进行了PMMA厚度3,5和7cm的评估。计算的归一化图像噪声值是可重复的(不确定性为3-5%),并且与已知的探测器-网格组合的物理特性一致。图像噪声对辐射光谱和散射量非常敏感。从阈值对比度检测开始用CDMAM方法。3.4幻影,可以识别符合足够图像质量的图像噪声可接受/可实现阈值。基于拟议测试对象的信号噪声差(SDNR)分析与根据EUREF指南进行的SDNR评估结果吻合良好(差1- 7%)。转换系数、图像噪声和归一化图像噪声都可以从单次曝光中得出,而无需事先确定探测器的响应曲线,这对于非线性响应特别有利。考虑到图像噪声对辐射质量和剂量的敏感性,它是一个合适的优化度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Normalized image noise as an absolute quantity for performance assessment in 2D mammography
A method is proposed to equate the measured noise to a thickness of Aluminium by exposing a simple test object which includes an Aluminium step-wedge sandwiched between PMMA slabs. The scaling process turns the Image Noise expressed in mmAl into an absolute quantity which reflects exposure conditions. A second quantity, the dose independent Normalized Image Noise is defined. It is a characteristic value for every mammography unit/model and phantom setup and represents a measure of a system’s overall detection efficiency in clinical conditions. 8 mammography units of different manufacturers and detector technologies have been evaluated for PMMA thickness 3, 5 and 7 cm over a wide average glandular dose (AGD) range. The calculated Normalised Image Noise values were reproducible (uncertainty 3-5%) and coherent with known physical characteristics of the detector-grid combinations. Image Noise resulted sensitive to radiation spectra and scatter amount. Starting from threshold contrast detection with the CDMAM ver. 3.4 phantom, it was possible to identify Image Noiseacceptable/achievable thresholds which correspond to adequate image quality. Signal difference to noise (SDNR) analysis based on the proposed test object was in good agreement with SDNR evaluation according to the EUREF guideline (difference 1- 7%). Conversion coefficient, Image Noise and Normalised Image Noise could all be derived from a single exposure without having to determine the detector's response curve beforehand which is particularly advantageous for non-linear response. Given the sensitivity of Image Noise to radiation quality and dose, it is a suitable metric for optimization.
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