Objective comparison of quantitative imaging modalities without the use of a gold standard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Imaging is often used for the purpose of estimating the value of some parameter of interest. For example, a cardiologist may measure the ejection fraction (EF) of the heart in order to know how much blood is being pumped out of the heart on each stroke. In clinical practice, however, it is difficult to evaluate an estimation method because the gold standard is not known, e.g., a cardiologist does not know the true EF of a patient. Thus, researchers have often evaluated an estimation method by plotting its results against the results of another (more accepted) estimation method, which amounts to using one set of estimates as the pseudogold standard. In this paper, we present a maximum likelihood approach for evaluating and comparing different estimation methods without the use of a gold standard with specific emphasis on the problem of evaluating EF estimation methods. Results of numerous simulation studies will be presented and indicate that the method can precisely and accurately estimate the parameters of a regression line without a gold standard, i.e., without the x-axis.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages12-23
Number of pages12
Volume2082
ISBN (Print)3540422455, 9783540422457
Publication statusPublished - 2001
Event17th International Conference on Information Processing in Medical Imaging, IPMI 2001 - Davis, United States
Duration: Jun 18 2001Jun 22 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2082
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other17th International Conference on Information Processing in Medical Imaging, IPMI 2001
CountryUnited States
CityDavis
Period6/18/016/22/01

    Fingerprint

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Hoppin, J., Kupinski, M. A., Kastis, G., Clarkson, E. W., & Barrett, H. H. (2001). Objective comparison of quantitative imaging modalities without the use of a gold standard. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2082, pp. 12-23). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2082). Springer Verlag.