Leuven University Center of Medical Physics in Radiology, University Hospitals Leuven, Belgium.
Br J Radiol. 2012 Dec;85(1020):e1233-41. doi: 10.1259/bjr/22608279. Epub 2012 Jul 27.
To compare two methods for assessment of image-processing algorithms in digital mammography: free-response receiver operating characteristic (FROC) for the specific task of microcalcification detection and visual grading analysis (VGA).
The FROC study was conducted prior to the VGA study reported here. 200 raw data files of low breast density (Breast Imaging-Reporting and Data System I-II) mammograms (Novation DR, Siemens, Germany)-100 of which abnormal-were processed by four image-processing algorithms: Raffaello (IMS, Bologna, Italy), Sigmoid (Sectra, Linköping, Sweden), and OpView v. 2 and v. 1 (Siemens, Erlangen, Germany). Four radiologists assessed the mammograms for the detection of microcalcifications. 8 months after the FROC study, a subset (200) of the 800 images was reinterpreted by the same radiologists, using the VGA methodology in a side-by-side approach. The VGA grading was based on noise, saturation, contrast, sharpness and confidence with the image in terms of normal structures. Ordinal logistic regression was applied; OpView v. 1 was the reference processing algorithm.
In the FROC study all algorithms performed better than OpView v. 1. From the current VGA study and for confidence with the image, Sigmoid and Raffaello were significantly worse (p<0.001) than OpView v. 1; OpView v. 2 was significantly better (p=0.01). For the image quality criteria, results were mixed; Raffaello and Sigmoid for example were better than OpView v. 1 for sharpness and contrast (although not always significantly).
VGA and FROC discordant results should be attributed to the different clinical task addressed.
The method to use for image-processing assessment depends on the clinical task tested.
比较两种用于评估数字乳腺摄影图像处理算法的方法:用于微钙化检测的特定任务的自由响应接收器操作特性(FROC)和视觉分级分析(VGA)。
本研究的 FROC 研究先于此处报告的 VGA 研究进行。200 份低乳腺密度(乳腺影像报告和数据系统 I-II)乳腺 X 线摄影原始数据文件(德国西门子 Novation DR)-其中 100 份异常-由四种图像处理算法处理:Raffaello(意大利博洛尼亚 IMS)、Sigmoid(瑞典 Linköping Sectra)、OpView v. 2 和 v. 1(德国西门子 Erlangen)。四位放射科医生评估了这些乳腺 X 线片以检测微钙化。在 FROC 研究 8 个月后,同一批 800 张图像中的 200 张由同一位放射科医生使用 VGA 方法进行并排解读。VGA 分级基于噪声、饱和度、对比度、锐度以及对正常结构图像的信心。应用有序逻辑回归;OpView v. 1 是参考处理算法。
在 FROC 研究中,所有算法的性能均优于 OpView v. 1。从当前的 VGA 研究来看,对于对图像的信心,Sigmoid 和 Raffaello 明显劣于 OpView v. 1(p<0.001);OpView v. 2 明显更好(p=0.01)。对于图像质量标准,结果参差不齐;例如,Raffaello 和 Sigmoid 在锐度和对比度方面优于 OpView v. 1(尽管并不总是显著)。
VGA 和 FROC 不一致的结果归因于所测试的不同临床任务。
用于图像处理评估的方法取决于测试的临床任务。