Health Sciences Research Centre, UCL University College, Niels Bohrs Alle 1, 5230, Odense M, Denmark.
Department of Radiology, Hospital Sonderjylland, University Hospitals of Southern Denmark, Kresten Philipsens Vej 15, 6200, Aabenraa, Denmark.
Radiography (Lond). 2021 Aug;27(3):877-882. doi: 10.1016/j.radi.2021.02.006. Epub 2021 Mar 4.
This study aimed to evaluate the effects of a newly developed Advanced Edge Enhancement software (AEE) (Canon Europe, Amsterdam, NL) on image quality (IQ) of Digital Radiography (DR) hand images focusing on rheumatoid arthritis (RA).
Fifty posterior-anterior hand images with or suspected for RA were collected. For each of the 50 images, six copies were made with each their AEE algorithm settings. A total of 330 images (30 images iterated) were evaluated using relative Visual Grading Analysis (VGA) by three observers and combined into a VGA Score (VGAS). Second, 50 images of a technical Contrast Detail Radiography Phantom (CDRAD) was produced with three different AEE software settings, each at level 1,5 and without the AEE software yielding 350 CDRAD images. All images was analysed by the CDRAD Analyser and included for an objective analysis of the AEE software.
The VGA study showed a significant difference in image quality between a standard image and images with AEE software applied. The average VGA score of the AEE software was better than the standard images (interval between 0.2 and 0.9). The AEE algorithms at level 5 scored significantly lower for noise but significantly higher for spatial resolution, sharpness and contrast in the VGA. The CDRAD images showed that all AEE algorithms had a statistically significant improvement for level 1 and deterioration for level 5 compared to the standard image.
Overall the AEE algorithm: small structure level 1 showed an improvement of all IQ criteria in the VGA and a better technical IQ.
The AEE software ought to be considered as a useful addition to the current software, possibly enabling visualisation of structures currently visible.
本研究旨在评估新开发的高级边缘增强软件（AEE）（佳能欧洲，阿姆斯特丹，NL）对关注类风湿关节炎（RA）的数字射线照相（DR）手部图像的图像质量（IQ）的影响。
共收集了 50 张前后位手部图像，其中包括或怀疑有 RA 的图像。对于 50 张图像中的每一张，都使用其 AEE 算法设置制作了六份副本。总共评估了 330 张图像（迭代了 30 张图像），由三位观察者使用相对视觉分级分析（VGA）进行评估，并将其组合成 VGA 评分（VGAS）。其次，使用三种不同的 AEE 软件设置在技术对比度细节射线照相体（CDRAD）上生成了 50 张图像，每种设置均为 1、5 级，不使用 AEE 软件生成了 350 张 CDRAD 图像。所有图像均由 CDRAD 分析器进行分析，并包括对 AEE 软件的客观分析。
VGA 研究表明，标准图像与应用 AEE 软件的图像之间的图像质量存在显著差异。AEE 软件的平均 VGA 评分优于标准图像（0.2 到 0.9 之间的间隔）。VGA 中的噪声方面，AEE 算法 5 级的得分明显较低，但空间分辨率、锐度和对比度得分明显较高。CDRAD 图像显示，与标准图像相比，所有 AEE 算法在 1 级都有统计学上的显著改善，而在 5 级则有统计学上的恶化。
总体而言，AEE 算法：小结构 1 级在 VGA 中显示出所有 IQ 标准的改善，以及更好的技术 IQ。
AEE 软件应被视为当前软件的有用补充，可能能够可视化当前可见的结构。
