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Title: Effect of correlation on combining diagnostic information from two images of the same patient

Abstract

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 moremore » often. These theoretical results are illustrated with analysis of a mammography study.« less

Authors:
; ;  [1]
  1. Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States)
Publication Date:
OSTI Identifier:
20726894
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 32; Journal Issue: 11; Other Information: DOI: 10.1118/1.2064787; (c) 2005 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; BIOMEDICAL RADIOGRAPHY; DIAGNOSIS; IMAGES; MAMMARY GLANDS; PATIENTS; PERFORMANCE; SENSITIVITY ANALYSIS

Citation Formats

Liu Bei, Metz, Charles E., and Jiang Yulei. Effect of correlation on combining diagnostic information from two images of the same patient. United States: N. p., 2005. Web. doi:10.1118/1.2064787.
Liu Bei, Metz, Charles E., & Jiang Yulei. Effect of correlation on combining diagnostic information from two images of the same patient. United States. doi:10.1118/1.2064787.
Liu Bei, Metz, Charles E., and Jiang Yulei. Tue . "Effect of correlation on combining diagnostic information from two images of the same patient". United States. doi:10.1118/1.2064787.
@article{osti_20726894,
title = {Effect of correlation on combining diagnostic information from two images of the same patient},
author = {Liu Bei and Metz, Charles E. and Jiang Yulei},
abstractNote = {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.},
doi = {10.1118/1.2064787},
journal = {Medical Physics},
number = 11,
volume = 32,
place = {United States},
year = {Tue Nov 15 00:00:00 EST 2005},
month = {Tue Nov 15 00:00:00 EST 2005}
}