Human and quasi-Bayesian observers of images limited by quantum noise, object variability, and artifacts

Kyle J. Myers, Robert F. Wagner, Kenneth M. Hanson, Harrison H. Barrett, Jannick P. Rolland

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

4 Scopus citations

Abstract

Many investigators have pointed out the need for performance measures that describe how well the images produced by a medical imaging system aid the end user in performing a particular diagnostic task. To this end we have investigated a variety of imaging tasks to determine the applicability of Bayesian and related strategies for predicting human performance. We have compared Bayesian and human classification performance for tasks involving a number of sources of decision-variable spread, including quantum fluctuations contained in the data set, inherent biological variability within each patient class, and deterministic artifacts due to limited data sets.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsHarold L. Kundel
PublisherPubl by Society of Photo-Optical Instrumentation Engineers
Pages180-190
Number of pages11
ISBN (Print)0819414611
StatePublished - 1994
EventMedical Imaging 1994: Image Perception - Newport Beach, CA, USA
Duration: Feb 17 1994Feb 18 1994

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2166
ISSN (Print)0277-786X

Other

OtherMedical Imaging 1994: Image Perception
CityNewport Beach, CA, USA
Period2/17/942/18/94

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Human and quasi-Bayesian observers of images limited by quantum noise, object variability, and artifacts'. Together they form a unique fingerprint.

Cite this