Evaluating estimation techniques in medical imaging without a gold standard: Experimental validation

John W. Hoppin, Matthew A. Kupinski, Donald W. Wilson, Todd Peterson, Benjamin Gershman, George Kastis, Eric Clarkson, Lars Furenlid, Harrison H. Barrett

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations


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 to quantify 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. An estimation method is typically evaluated by plotting its results against the results of another (more accepted) estimation method. This approach results in the use of one set of estimates as the pseudo-gold standard. We have developed a maximum-likelihood approach for comparing different estimation methods to the gold standard without the use of the gold standard. In previous works we have displayed the results of numerous simulation studies indicating the method can precisely and accurately estimate the parameters of a regression line without a gold standard, i.e., without the x-axis. In an attempt to further validate our method we have designed an experiment performing volume estimation using a physical phantom and two imaging systems (SPECT,CT).

Original languageEnglish (US)
Pages (from-to)230-237
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2003
EventMedical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment - San Diego, CA, United States
Duration: Feb 18 2003Feb 20 2003


  • Image quality
  • Parameter estimation
  • Regression analysis

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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