Hussner E D, Sundby S, Outzen C B, Jensen J, Tingberg A, Precht H
Health Sciences Research Centre, Radiography education, UCL University College, Odense, Denmark.
Department of Radiology, Odense University Hospital, Denmark; Research and Innovation Unit of Radiology, University of Southern Denmark, Denmark.
J Med Imaging Radiat Sci. 2025 Mar;56(2):101814. doi: 10.1016/j.jmir.2024.101814. Epub 2024 Dec 6.
This study aims to evaluate the effects of a novel noise reduction software (INR, Canon Europe, Amsterdam, NL) on image quality (IQ) in Digital Radiography (DR) pelvic phantom images.
In total, 53 pelvic phantom images and 360 technical images of a Contrast Detail Radiography phantom (CDRAD) were collected, including 8 different exposure levels (between 0.8 and 40 mAs at 70 kV) and 6 intensities of INR (ranging from settings 0-10). The pelvic images were evaluated by three reporting radiographers using absolute Visual Grading Analysis (VGA). The CDRAD images were analyzed with a CDRAD computer software.
The VGA showed that the images with the INR software had higher IQ than the images with no INR. The observers gave a high VGA score to the images with INR of 3.2 mAs and higher. There was a tendency for an INR level of 5 or 7 to give the highest VGA scores. In addition, the CDRAD study showed a significant improvement in IQ with increasing INR levels at the lower exposure levels.
An improvement in overall IQ was seen at lower exposure levels when the INR software was used both for the VGA and the CDRAD study. Clinical tests including patient images need to be performed before implementing INR in practice to verify accurate diagnostic performance.
本研究旨在评估一种新型降噪软件（INR，佳能欧洲公司，荷兰阿姆斯特丹）对数字X线摄影（DR）骨盆体模图像质量（IQ）的影响。
总共收集了53张骨盆体模图像和360张对比细节X线摄影体模（CDRAD）的技术图像，包括8种不同的曝光水平（70 kV时0.8至40 mAs之间）和6种INR强度（设置范围为0 - 10）。三位报告放射技师使用绝对视觉分级分析（VGA）对骨盆图像进行评估。CDRAD图像使用CDRAD计算机软件进行分析。
VGA显示，使用INR软件的图像比未使用INR的图像具有更高的IQ。观察者对INR为3.2 mAs及以上的图像给予了较高的VGA评分。INR水平为5或7时倾向于给出最高的VGA评分。此外，CDRAD研究表明，在较低曝光水平下，随着INR水平的增加，IQ有显著改善。
在VGA和CDRAD研究中使用INR软件时，在较低曝光水平下整体IQ有所提高。在实际应用INR之前，需要进行包括患者图像在内的临床试验，以验证准确的诊断性能。
