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Proceedings Paper

Binary ROC curve and three-class 2-D ROC surface
Author(s): Xin He; Eric C. Frey
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Paper Abstract

In this work, we compared the binary ROC curve and the 2-D three-class ROC surface. We found that the 2-D three-class ROC surface shares most of the properties of the binary ROC curve. In particular, the curve (or surface) has the same DOF as the as the decision rule that is used to generate it; the curve (or surface) contains all the optimal operating points under various decision criteria (note that for three-class, the equal error utility assumption is assumed, same below); different decision criteria result in the same ROC curve (or surface) by considering all the possible prior information; ROC curve (or surface) uniquely corresponds to one pair (or triplet) of likelihood ratio distributions, assuming such a pair (or triplet) exists; the ROC curve (or surface) is concave; and the ROC curve (or surface) provides graphic information as well as figure-of-merit for task performance. We thus conclude that that the 2-D ROC surface may be preferable as a starting point for comparing systems used to perform 3-class diagnostic tasks.

Paper Details

Date Published: 3 March 2010
PDF: 7 pages
Proc. SPIE 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 762710 (3 March 2010); doi: 10.1117/12.844593
Show Author Affiliations
Xin He, The Johns Hopkins School of Medicine (United States)
Eric C. Frey, The Johns Hopkins School of Medicine (United States)


Published in SPIE Proceedings Vol. 7627:
Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment
David J. Manning; Craig K. Abbey, Editor(s)

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