Ideal-observer performance under signal and background uncertainty

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2732, Issue , 2003, Pages 342-353

  Park, S ^a   Kupinski, M A ^a   Clarkson, E ^a   Barrett, H H ^a  

^a UNIVERSITY OF ARIZONA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGING SYSTEMS; MARKOV PROCESSES; MEDICAL IMAGING; STATISTICAL TESTS;

DETECTION INFORMATIONS; HARDWARE OPTIMIZATION; HIGH-DIMENSIONAL; IDEAL OBSERVERS; LIKELIHOOD RATIOS; MARKOV CHAIN MONTE-CARLO; PSYCHOPHYSICAL STUDIES; TEST STATISTICS;

UNCERTAINTY ANALYSIS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CLINICAL TRIAL; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; OBSERVER VARIATION; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; STATISTICS; THREE DIMENSIONAL IMAGING; VALIDATION STUDY; VISION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; LIKELIHOOD FUNCTIONS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; OBSERVER VARIATION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STOCHASTIC PROCESSES; SUBTRACTION TECHNIQUE; VISUAL PERCEPTION;

EID: 24644444517     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-45087-0_29     Document Type: Article

References (11)

1. H. H. Barrett and C. K. Abbey: Bayesian Detection of Random Signals on Random Backgrounds. 4th International Conference on Information Processing in Medical Imaging, 1997.
2. H. H. Barrett, C. K. Abbey, and E. Clarkson: Objective assessment of image quality III: ROC metrics, ideal observers, and likelihood- generating functions. J. Opt. Soc. Am. A 15, 1520-1535 (1998).
3. H. H. Barrett, C. K. Abbey, and E. Clarkson: Some unlikely properties of the likelihood ratio and its logarithm. Proc. SPIE 3340 (1998).
4. E. Clarkson and H. H. Barrett: Approximation to ideal-observer performance on signal-detection tasks. Applied Optics 39, 1783-1794 (2000).
5. E. Clarkson: Bounds on the area under the receiver operating characteristic curve for the ideal observer. J. Opt. Soc. Am. A 19 1963-1968 (2001).
6. W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (Eds): Markov Chain Monte Carlo in Practice. Chapman and Hall, Boca Raton (1996).
7. M. A. Kupinski, J. W. Hoppin, E. Clarkson, and H. H. Barrett: Ideal Observer Computation Using Markov-Chain Monte Carlo. J. Opt. Soc. Am. A (Accepted) (2002).
8. C. E. Metz, B. A. Herman, and J. H. Shen: Maximum Likelihood Estimation of Receiver Operating Characteristic (ROC) Curves from Continuously -Distributed Data. Statistics In Medicine 17, 1033-1053 (1998).
9. C. E. Metz and X. Pan: Proper Binormal ROC Curves: Theory and Maximum-Likelihood Estimation. Journal of Mathematical Psychology 43, 1-33 (1999).
10. J. P. Rolland and H. H. Barrett: Effect of random background inhomogeneity on observer detection performance. J. Opt. Soc. Am. A 9, 649-658 (1992).
11. H. Zhang: Signal Detection in Medical Imaging. Ph.D. Dissertation, The University of Arizona (2001).