Literature DB >> 16350917

Restrictions on the three-class ideal observer's decision boundary lines.

Darrin C Edwards1, Charles E Metz.   

Abstract

We are attempting to develop expressions for the coordinates of points on the three-class ideal observer's receiver operating characteristic (ROC) hypersurface as functions of the set of decision criteria used by the ideal observer. This is considerably more difficult than in the two-class classification task, because the conditional probabilities in question are not simply related to the cumulative distribution functions of the decision variables, and because the slopes and intercepts of the decision boundary lines are not independent; given the locations of two of the lines, the location of the third will be constrained depending on the other two. In this paper, we attempt to characterize those constraining relationships among the three-class ideal observer's decision boundary lines. As a result, we show that the relationship between the decision criteria and the misclassification probabilities is not one-to-one, as it is for the two-class ideal observer.

Mesh:

Year:  2005        PMID: 16350917     DOI: 10.1109/TMI.2005.859212

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  8 in total

Review 1.  ROC analysis in medical imaging: a tutorial review of the literature.

Authors:  Charles E Metz
Journal:  Radiol Phys Technol       Date:  2007-10-27

2.  Performance analysis of three-class classifiers: properties of a 3-D ROC surface and the normalized volume under the surface for the ideal observer.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski
Journal:  IEEE Trans Med Imaging       Date:  2008-02       Impact factor: 10.048

3.  Validation of Monte Carlo estimates of three-class ideal observer operating points for normal data.

Authors:  Darrin C Edwards
Journal:  Acad Radiol       Date:  2013-07       Impact factor: 3.173

4.  The meaning and use of the volume under a three-class ROC surface (VUS).

Authors:  Xin He; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2008-05       Impact factor: 10.048

5.  Three-class ROC analysis--toward a general decision theoretic solution.

Authors:  Xin He; Brandon D Gallas; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2009-10-30       Impact factor: 10.048

6.  The three-class ideal observer for univariate normal data: Decision variable and ROC surface properties.

Authors:  Darrin C Edwards; Charles E Metz
Journal:  J Math Psychol       Date:  2012-06-20       Impact factor: 2.223

7.  Application of three-class ROC analysis to task-based image quality assessment of simultaneous dual-isotope myocardial perfusion SPECT (MPS).

Authors:  Xin He; Xiyun Song; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2008-11       Impact factor: 10.048

8.  The validity of three-class Hotelling trace (3-HT) in describing three-class task performance: comparison of three-class volume under ROC surface (VUS) and 3-HT.

Authors:  Xin He; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2009-02       Impact factor: 10.048

  8 in total

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