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[用于X射线计算机断层扫描图像质量评估的信噪比估计]

[SNR Estimation for Image Quality Evaluation in X-ray CT].

作者信息

Tabuchi Motohiro, Kiguchi Takashi, Ikenaga Hiroyuki

机构信息

Department of Radiology, Konko Hospital Dojinkai.

Department of Radiological Technology, Diagnostic Imaging Center I, Kawasaki Medical School Hospital.

出版信息

Nihon Hoshasen Gijutsu Gakkai Zasshi. 2022 May 20;78(5):464-472. doi: 10.6009/jjrt.2022-1154. Epub 2022 Apr 7.

Abstract

PURPOSE

Although the signal-to-noise ratio (SNR) currently used in the field of medical X-ray CT is utilized for local image evaluation in a linear system, it is not used as a comprehensive evaluation index for an entire image. Additionally, since X-ray CT cannot produce a noiseless image for obtaining the signal power required to calculate the SNR, it is impossible to calculate SNR precisely even applying the conventional method. To resolve these problems, we propose SNR*, which is a new method for calculating the estimated value of SNR that can evaluate an entire image even when the original image cannot be obtained.

METHODS

First, we obtained SNR* using the signal power and noise power calculated respectively from covariance and the difference in the pair of observed images, which are noise-containing images scanned under the same imaging conditions. Next, we verified the error and the accuracy of SNR*. Third, we demonstrated the behavior and accuracy of the SNR* applied to the actually observed image.

RESULTS

In the verification experiment, the relative error of SNR* concerning the true value was 0.06% or less, and the coefficient of variation value of SNR* in the demonstration experiment was 0.015 or less, which denoted the accuracy of SNR*.

CONCLUSION

The proposed method realizes SNR measurement even in cases in which only observed images can be obtained and original images cannot be obtained, such as X-ray CT images.

摘要

目的

尽管医学X射线计算机断层扫描(CT)领域目前使用的信噪比(SNR)用于线性系统中的局部图像评估,但它并未用作整个图像的综合评估指标。此外,由于X射线CT无法生成用于获取计算SNR所需信号功率的无噪声图像,即使应用传统方法也无法精确计算SNR。为了解决这些问题,我们提出了SNR*,这是一种计算SNR估计值的新方法,即使在无法获得原始图像的情况下也能评估整个图像。

方法

首先,我们使用分别从协方差以及在相同成像条件下扫描的一对含噪声观测图像的差异中计算出的信号功率和噪声功率来获得SNR*。接下来,我们验证了SNR的误差和准确性。第三,我们展示了应用于实际观测图像的SNR的表现和准确性。

结果

在验证实验中,SNR相对于真值的相对误差为0.06%或更小,在演示实验中SNR的变异系数值为0.015或更小,这表明了SNR*的准确性。

结论

所提出的方法即使在只能获得观测图像而无法获得原始图像的情况下,如X射线CT图像,也能实现SNR测量。

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