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Craig K. Abbey
Researcher at University of California, Santa Barbara
Publications - 238
Citations - 4738
Craig K. Abbey is an academic researcher from University of California, Santa Barbara. The author has contributed to research in topics: Observer (quantum physics) & Imaging phantom. The author has an hindex of 37, co-authored 218 publications receiving 4407 citations. Previous affiliations of Craig K. Abbey include University of California, San Francisco & University of Arizona.
Papers
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Journal ArticleDOI
Computer aided detection of masses in mammography using subregion Hotelling observers.
TL;DR: Using subregion Hotelling observers in combination with LDs can provide a strong backbone for a CAD scheme to help radiologists with detection and could be used in conjunction with CAD systems for false positive reduction.
Journal ArticleDOI
Learning cue validity through performance feedback.
TL;DR: Results show that saccadic and perceptual decisions reflect larger cueing effects as feedback information increased, which suggests that internal signals generated from response selection are insufficient for exploiting cue validity, but that reinforcement may be sufficient.
Journal ArticleDOI
Visual signal detection in structured backgrounds. IV. Figures of merit for model performance in multiple-alternative forced-choice detection tasks with correlated responses.
TL;DR: In this paper, the authors investigate the effect of response correlations on model performance and compare different figures of merit for these conditions, and show that using the standard d′ index of detectability assuming statistical independence can lead to erroneous underestimates of Pc and misleading comparisons of models.
Journal ArticleDOI
Search for lesions in mammograms: statistical characterization of observer responses.
TL;DR: Results show that human performance in a multiple-alternative forced-choice experiment can be used to predict performance in the clinically realistic free search experiment when the investigator takes into account the search area and the observers' inherent spatial imprecision to localize the targets.
Proceedings ArticleDOI
Effect of image compression in model and human performance
TL;DR: All three model-observers predicted reasonably well the degradation in human performance as a function of JPEG image compression, although the NPWEW and the channelized Hotelling models (with internal noise proportional to the external noise) were better predictors than the Hotelling model.