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成像系统评估方法、FROC分析及搜索模型的最新进展

Recent developments in imaging system assessment methodology, FROC analysis and the search model.

作者信息

Chakraborty Dev P

机构信息

University of Pittsburgh, USA.

出版信息

Nucl Instrum Methods Phys Res A. 2011 Aug 21;648 Supplement 1:S297-S301. doi: 10.1016/j.nima.2010.11.042.

Abstract

A frequent problem in imaging is assessing whether a new imaging system is an improvement over an existing standard. Observer performance methods, in particular the receiver operating characteristic (ROC) paradigm, are widely used in this context. In ROC analysis lesion location information is not used and consequently scoring ambiguities can arise in tasks, such as nodule detection, involving finding localized lesions. This paper reviews progress in the free-response ROC (FROC) paradigm in which the observer marks and rates suspicious regions and the location information is used to determine whether lesions were correctly localized. Reviewed are FROC data analysis, a search-model for simulating FROC data, predictions of the model and a method for estimating the parameters. The search model parameters are physically meaningful quantities that can guide system optimization.

摘要

成像中的一个常见问题是评估新的成像系统是否比现有的标准系统有所改进。在这种情况下,观察者性能方法,特别是接收器操作特性(ROC)范式被广泛使用。在ROC分析中,病变位置信息未被使用,因此在诸如结节检测等涉及发现局部病变的任务中可能会出现评分模糊性。本文综述了自由响应ROC(FROC)范式的进展,在该范式中观察者标记并评估可疑区域,并使用位置信息来确定病变是否被正确定位。综述内容包括FROC数据分析、用于模拟FROC数据的搜索模型、模型预测以及参数估计方法。搜索模型参数是具有物理意义的量,可指导系统优化。

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