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Proceedings Paper

Comparing the performance of two observers using a novel utility-based performance metric for ROC analysis
Author(s): Darrin C. Edwards; Charles E. Metz
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Paper Abstract

We previously introduced a utility-based ROC performance metric, the "surface-averaged expected cost" (SAEC), to address difficulties which arise in generalizing the well-known area under the ROC curve (AUC) to classification tasks with more than two classes. In a two-class classification task, the SAEC can be shown explicitly to be twice the area above the conventional ROC curve (1-AUC) divided by the arclength along the ROC curve. In the present work, we show that in tasks comparing the performance of two observers whose behavior is described by the proper binormal model, our proposed performance metric is consistent with AUC in the qualitative sense of deciding which of the two observers is "better," and by how wide a margin.

Paper Details

Date Published: 12 March 2009
PDF: 7 pages
Proc. SPIE 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment, 72630W (12 March 2009); doi: 10.1117/12.810778
Show Author Affiliations
Darrin C. Edwards, The Univ. of Chicago (United States)
Charles E. Metz, The Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 7263:
Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment
Berkman Sahiner; David J. Manning, Editor(s)

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