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

doi:10.1117/12.171740

1 April 1994 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

Proceedings Volume 2166, Medical Imaging 1994: Image Perception; (1994) https://doi.org/10.1117/12.171740
Event: Medical Imaging 1994, 1994, Newport Beach, CA, United States

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.

Citation Download Citation

Kyle J. Myers, Robert F. Wagner, Kenneth M. Hanson, Harrison H. Barrett, and Jannick P. Rolland "Human and quasi-Bayesian observers of images limited by quantum noise, object-variability, and artifacts", Proc. SPIE 2166, Medical Imaging 1994: Image Perception, (1 April 1994); https://doi.org/10.1117/12.171740

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