Anam Choirul, Amilia Riska, Naufal Ariij, Sutanto Heri, Budi Wahyu S, Dougherty Geoff
Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Indonesia.
Department of Applied Physics and Medical Imaging, California State University Channel Islands, Camarillo, CA 93012, USA.
J Imaging. 2025 May 26;11(6):175. doi: 10.3390/jimaging11060175.
This study evaluates the performance of a statistical-based automatic contrast-to-noise ratio (CNR) measurement method on images of the ACR CT phantom under varying imaging parameters. A statistical automatic method for segmenting low-contrast objects and for measuring CNR was recently introduced. The method employs a 25 mm region of interest (ROI), rotated in 2° clockwise steps, to identify the low-contrast object by locating the maximum CT value. The CNR was measured on images acquired with different parameters: tube voltage (80-140 kVp), tube current (80-200 mA), slice thickness (1.25-10 mm), field of view (190-230 mm), and convolution kernel (edge, ultra, lung, bone, chest, standard). The automatic results were compared to manual measurements. The automatic method accurately identified the largest low-contrast object. The CNR values from the automatic and manual methods showed no significant difference ( > 0.05). The CNR increased with higher tube voltage and current, and with thinner slice thickness. Chest and standard kernels yielded higher CNRs, while edge, ultra, lung, and bone kernels yielded lower ones. The CNR remained stable with minor FOV changes. The statistical-based automatic method provided accurate and consistent CNR measurements across a range of imaging settings for the ACR CT phantom.
本研究评估了一种基于统计的自动对比噪声比（CNR）测量方法在不同成像参数下对美国放射学会（ACR）CT体模图像的性能。最近引入了一种用于分割低对比度物体和测量CNR的统计自动方法。该方法采用一个25毫米的感兴趣区域（ROI），以顺时针2°步长旋转，通过定位最大CT值来识别低对比度物体。在使用不同参数采集的图像上测量CNR：管电压（80 - 140 kVp）、管电流（80 - 200 mA）、层厚（1.25 - 10毫米）、视野（190 - 230毫米）和卷积核（边缘、超、肺、骨、胸部、标准）。将自动测量结果与手动测量结果进行比较。自动方法准确识别出最大的低对比度物体。自动测量和手动测量得到的CNR值无显著差异（>0.05）。CNR随着管电压和电流的升高以及层厚的变薄而增加。胸部和标准卷积核产生较高的CNR值，而边缘、超、肺和骨卷积核产生较低的CNR值。随着视野的微小变化，CNR保持稳定。基于统计的自动方法在一系列成像设置下为ACR CT体模提供了准确且一致的CNR测量结果。
