A nonparametric approach to comparing the areas under correlated LROC curves

Adam Wunderlich; Frédéric Noo

doi:10.1117/12.913557

22 February 2012 A nonparametric approach to comparing the areas under correlated LROC curves

Adam Wunderlich, Frédéric Noo

Proceedings Volume 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment; 83180F (2012) https://doi.org/10.1117/12.913557
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

In contrast to the ROC assessment paradigm, localization ROC (LROC) analysis provides a means to jointly assess the accuracy of visual search and detection in an observer study. In a typical multireader, multicase (MRMC) evaluation, the data sets are paired so that correlations arise in observer performance both between observers and between image reconstruction methods (or modalities). Therefore,MRMC evaluations motivate the need for a statistical methodology to compare correlated LROC curves. In this work, we suggest a nonparametric strategy for this purpose. Specifically, we find that seminal work of Sen on U-statistics can be applied to estimate the covariance matrix for a vector of LROC area estimates. The resulting covariance estimator is the LROC analog of the covariance estimator given by DeLong et al. for ROC analysis. Once the covariance matrix is estimated, it can be used to construct confidence intervals and/or confidence regions for purposes of comparing observer performance across reconstruction methods. The utility of our covariance estimator is illustrated with a human-observer LROC evaluation of three reconstruction strategies for fan-beam CT.

Citation Download Citation

Adam Wunderlich and Frédéric Noo "A nonparametric approach to comparing the areas under correlated LROC curves", Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 83180F (22 February 2012); https://doi.org/10.1117/12.913557

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KEYWORDS

Reconstruction algorithms

Statistical analysis

Analog electronics

Data modeling

Head

Image filtering

Image restoration

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