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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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Proceedings ArticleDOI
The role of extra-foveal processing in 3D imaging.
TL;DR: It is suggested that observer performance findings with 2D search might not always generalize to 3D search, and the development of a new family of model observers that take into account the inhomogeneous visual processing across the retina (foveated model observers) is motivated.
Journal ArticleDOI
The temporal dynamics of selective attention of the visual periphery as measured by classification images.
TL;DR: A selective attention effect earlier than those found in previous behavioral and event-related potential (ERP) studies, which generally have estimated the latency for selective attention effects to be 75-100 ms, is estimated.
Proceedings ArticleDOI
Interactions of lesion detectability and size across single-slice DBT and 3D DBT.
Miguel A. Lago,Craig K. Abbey,Bruno Barufaldi,Predrag R. Bakic,Susan P. Weinstein,Andrew D. A. Maidment,Miguel P. Eckstein +6 more
TL;DR: The results extend previous findings with synthetic textures and highlight how search in 3D images is distinct from 2D search as a consequence of the interaction between search strategies and the visibility of signals in the visual periphery.
Journal ArticleDOI
Inter-laboratory comparison of channelized hotelling observer computation.
Alexandre Ba,Craig K. Abbey,Jongduk Baek,Minah Han,Ramona W. Bouwman,Christiana Balta,Jovan G. Brankov,Francesc Massanes,Howard C. Gifford,I. Hernandez-Giron,Wouter J. H. Veldkamp,Dimitar Petrov,Nicholas Marshall,Frank W. Samuelson,Rongping Zeng,Justin Solomon,Ehsan Samei,Pontus Timberg,Hannie Förnvik,Ingrid Reiser,Lifeng Yu,Hao Gong,François Bochud +22 more
TL;DR: This intercomparison helped define the state of the art of model observer performance computation and with thirteen participants, reflects openness and trust within the medical imaging community.
Journal ArticleDOI
Stimulus information contaminates summation tests of independent neural representations of features.
TL;DR: In a visual search task with spatial frequency and orientation as the component features, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.