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自由响应ROC曲线(FROC)下面积及相关汇总指标。

Area under the free-response ROC curve (FROC) and a related summary index.

作者信息

Bandos Andriy I, Rockette Howard E, Song Tao, Gur David

机构信息

Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA.

出版信息

Biometrics. 2009 Mar;65(1):247-56. doi: 10.1111/j.1541-0420.2008.01049.x. Epub 2008 May 13.

Abstract

Free-response assessment of diagnostic systems continues to gain acceptance in areas related to the detection, localization, and classification of one or more "abnormalities" within a subject. A free-response receiver operating characteristic (FROC) curve is a tool for characterizing the performance of a free-response system at all decision thresholds simultaneously. Although the importance of a single index summarizing the entire curve over all decision thresholds is well recognized in ROC analysis (e.g., area under the ROC curve), currently there is no widely accepted summary of a system being evaluated under the FROC paradigm. In this article, we propose a new index of the free-response performance at all decision thresholds simultaneously, and develop a nonparametric method for its analysis. Algebraically, the proposed summary index is the area under the empirical FROC curve penalized for the number of erroneous marks, rewarded for the fraction of detected abnormalities, and adjusted for the effect of the target size (or "acceptance radius"). Geometrically, the proposed index can be interpreted as a measure of average performance superiority over an artificial "guessing" free-response process and it represents an analogy to the area between the ROC curve and the "guessing" or diagonal line. We derive the ideal bootstrap estimator of the variance, which can be used for a resampling-free construction of asymptotic bootstrap confidence intervals and for sample size estimation using standard expressions. The proposed procedure is free from any parametric assumptions and does not require an assumption of independence of observations within a subject. We provide an example with a dataset sampled from a diagnostic imaging study and conduct simulations that demonstrate the appropriateness of the developed procedure for the considered sample sizes and ranges of parameters.

摘要

在与检测、定位和分类受检者体内一个或多个“异常”相关的领域中,诊断系统的自由反应评估越来越受到认可。自由反应接收器操作特性(FROC)曲线是一种用于同时表征自由反应系统在所有决策阈值下性能的工具。尽管在ROC分析中,一个总结整个曲线在所有决策阈值上情况的单一指标的重要性已得到广泛认可(例如,ROC曲线下的面积),但目前在FROC范式下,对于正在评估的系统还没有广泛接受的总结指标。在本文中,我们提出了一个同时适用于所有决策阈值的自由反应性能新指标,并开发了一种用于其分析的非参数方法。从代数角度看,所提出的总结指标是经验FROC曲线下的面积,该面积因错误标记的数量而受到惩罚,因检测到的异常比例而得到奖励,并针对目标大小(或“接受半径”)的影响进行了调整。从几何角度看,所提出的指标可以解释为相对于人工“猜测”自由反应过程的平均性能优势的度量,它类似于ROC曲线与“猜测”或对角线之间的面积。我们推导了方差的理想自助估计量,可用于无重采样构建渐近自助置信区间以及使用标准表达式进行样本量估计。所提出的方法不受任何参数假设的限制,并且不需要假设受检者内观察值的独立性。我们提供了一个从诊断成像研究中采样的数据集示例,并进行了模拟,结果表明所开发的方法对于所考虑的样本量和参数范围是合适的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5d/2776072/b9024dce15aa/nihms-145737-f0001.jpg

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