ROC Analysis of Imaging System Evaluations

现在在成像系统的评估和比较期间进行的许多研究包括正常和异常情况的解释（阅读）研究，其通过受试者操作特征分析（ROC）或其衍生物来评估。不幸的是，在目前的系统评估方法的局限性，导致极其复杂和昂贵的研究设计和数据方法，应用不同的配方的一个众所周知的统计这个问题，并验证所提出的方法，使用模拟和大量的实验数据集提供给我们。Wilcoxon统计是一种非参数方法，在使用评分数据时通常用于获得ROC曲线下面积，该方法具有比较阴性和阳性情况下所有可能的观察值对的公式。虽然这个问题的概念化可以用来进一步发展和扩展ROC方法。我们计划利用这一概念来开发一种敏感的统计检验，以比较两种或更多种ROC曲线下面积，使我们能够评估选定变量对ROC曲线下面积的影响，以总结多疾病环境中的诊断准确性，并对两种（或更多种）模式的诊断准确性差异进行定性。作为不同参数的函数，并且可能在并入效用函数之后。

Many of the investigations that are now carried out during imaging systems' evaluations and comparisons include interpretation (reading) studies of normal and abnormal cases that are evaluated by receiver operating characteristic analyses (ROC) or derivatives thereof. Unfortunately, limitations in present methodology for systems evaluations have results in extremely complicated and costly study designs and data methodology to apply a different formulation of a well- known statistic to this problem and verify the proposed approach using both simulation and a large set of experimental data available to us. The Wilcoxon statistic, a non-parametric method often used to obtain the area under the ROC curve when scoring data is used, has a formulation that compares all possible pairs of observations of a negative and a positive case. Although this conceptualization of the problem can be used to further develop and extend ROC methodology. We plan to exploit this conceptualization to develop a sensitive statistical test to compare the areas under two or more ROC curses in a manner that will enable us to assess the effect of selected variables on the area under the ROC curve as to summarize diagnostic accuracy in the multi-disease setting and to quality the difference in diagnostic accuracy of two modalities (or more) as a function of different parameters and possibly after the incorporation of utility function.