title: The radiology task: Bayesian theory and perception.
abstract: The use of a Bayesian framework to understand how radiologists search images for pathology is important as it formalizes, mathematically, how visual and cognitive processes control eye movements by modelling the ideal searcher against which human performance can be compared. It is important that the interpretation of medical images is understood so that new developments in the ways images are presented and the use of image processing software are matched to human abilities and limitations.
authors.affiliation: School of Medical Imaging Sciences, St Martin's College, Bowerham Road, Lancaster LA1 3JD, UK. t.donovan@ucsm.ac.uk
authors.forename: T
authors.initials: T
authors.lastname: Donovan
authors.forename: D J
authors.initials: DJ
authors.lastname: Manning
mesh_terms: D001499:Bayes Theorem; D003071:Cognition; D003657:Decision Making; D006801:Humans; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D021641:Recognition, Psychology; D012160:Retina / Q000502:physiology; D014796:Visual Perception / Q000502:physiology