Båth Magnus, Hansson Jonny
Department of Radiation Physics, Institute of Clinical Sciences, The Sahlgrenska Academy at University of Gothenburg, SE-413 45 Gothenburg, Sweden Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, SE-413 45 Gothenburg, Sweden
Department of Radiation Physics, Institute of Clinical Sciences, The Sahlgrenska Academy at University of Gothenburg, SE-413 45 Gothenburg, Sweden Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, SE-413 45 Gothenburg, Sweden.
Radiat Prot Dosimetry. 2016 Jun;169(1-4):46-53. doi: 10.1093/rpd/ncv542. Epub 2016 Jan 13.
Visual grading characteristics (VGC) analysis is a non-parametric rank-invariant method for analysis of visual grading data. In VGC analysis, image quality ratings for two different conditions are compared by producing a VGC curve, similar to how the ratings for normal and abnormal cases in receiver operating characteristic (ROC) analysis are used to create an ROC curve. The use of established ROC software for the analysis of VGC data has therefore previously been proposed. However, the ROC analysis is based on the assumption of independence between normal and abnormal cases. In VGC analysis, this independence cannot always be assumed, e.g. if the ratings are based on the same patients imaged under both conditions. A dedicated software intended for analysis of VGC studies, which takes possible dependencies between ratings into account in the statistical analysis of a VGC study, has therefore been developed. The software-VGC Analyzer-determines the area under the VGC curve and its uncertainty using non-parametric resampling techniques. This article gives an introduction to VGC Analyzer, describes the types of analyses that can be performed and instructs the user about the input and output data.
视觉分级特征（VGC）分析是一种用于分析视觉分级数据的非参数秩不变方法。在VGC分析中，通过生成VGC曲线来比较两种不同条件下的图像质量评级，这类似于在接收器操作特性（ROC）分析中使用正常和异常病例的评级来创建ROC曲线。因此，之前有人提议使用已有的ROC软件来分析VGC数据。然而，ROC分析基于正常和异常病例之间独立性的假设。在VGC分析中，这种独立性并非总能成立，例如，如果评级是基于在两种条件下对同一患者进行成像得到的。因此，已经开发了一款专门用于分析VGC研究的软件，该软件在VGC研究的统计分析中考虑了评级之间可能存在的相关性。该软件——VGC分析器——使用非参数重采样技术确定VGC曲线下的面积及其不确定性。本文介绍了VGC分析器，描述了可以执行的分析类型，并指导用户了解输入和输出数据。
