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Effect of correlation on combining diagnostic information from two images of the same patient
Author(s) -
Liu Bei,
Metz Charles E.,
Jiang Yulei
Publication year - 2005
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2064787
Subject(s) - correlation , receiver operating characteristic , context (archaeology) , computer science , monotonic function , artificial intelligence , mathematics , pattern recognition (psychology) , mammography , medical imaging , image (mathematics) , spatial correlation , statistics , medicine , paleontology , mathematical analysis , geometry , cancer , breast cancer , biology
We have shown previously, in the context of computer‐aided diagnosis (CAD), that information derived from multiple images of the same patient can be used to improve diagnostic performance. In that work, we ignored the correlation among multiple images of the same patient. In the present study, we investigate theoretically, within the framework of receiver operating characteristic (ROC) analysis, the effect of correlation on three methods for combining quantitative diagnostic information from two images: taking the average, the maximum, and the minimum of a pair of normally distributed decision variables. We assume, as in our previous work, that the quantitative diagnostic information obtained from the two images of a given patient can be transformed monotonically to two latent decision variables that are normally distributed. Similar to the situation of uncorrelated images, we found that (1) the average always improves the area under the ROC curve (AUC) compared to the single‐view image; (2) the maximum and the minimum can also, but not always, improve the AUC; and (3) each method can be the best method in certain situations. In addition, as the correlation strength increases, the average performs the best less often, whereas the maximum and the minimum perform the best more often. These theoretical results are illustrated with analysis of a mammography study.