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dc.contributor.authorDalimier, Eugénie
dc.contributor.authorPailos, Eliseo
dc.contributor.authorRivera, Ricardo
dc.contributor.authorNavarro, Rafael
dc.date.accessioned2010-03-10T10:07:09Z
dc.date.available2010-03-10T10:07:09Z
dc.date.issued2009
dc.identifier.citationExperimental validation of a Bayesian model of visual acuity. 2009, 9 (7):12 J Visen
dc.identifier.issn1534-7362
dc.identifier.pmid19761327
dc.identifier.doi10.1167/9.7.12
dc.identifier.urihttp://hdl.handle.net/10147/94034
dc.description.abstractBased on standard procedures used in optometry clinics, we compare measurements of visual acuity for 10 subjects (11 eyes tested) in the presence of natural ocular aberrations and different degrees of induced defocus, with the predictions given by a Bayesian model customized with aberrometric data of the eye. The absolute predictions of the model, without any adjustment, show good agreement with the experimental data, in terms of correlation and absolute error. The efficiency of the model is discussed in comparison with image quality metrics and other customized visual process models. An analysis of the importance and customization of each stage of the model is also given; it stresses the potential high predictive power from precise modeling of ocular and neural transfer functions.
dc.language.isoenen
dc.subject.meshAberrometry
dc.subject.meshAdult
dc.subject.meshBayes Theorem
dc.subject.meshFixation, Ocular
dc.subject.meshHumans
dc.subject.meshMiddle Aged
dc.subject.meshModels, Biological
dc.subject.meshOcular Physiological Phenomena
dc.subject.meshPattern Recognition, Visual
dc.subject.meshRefraction, Ocular
dc.subject.meshVisual Acuity
dc.subject.meshYoung Adult
dc.titleExperimental validation of a Bayesian model of visual acuity.en
dc.contributor.departmentApplied Optics Group, School of Physics, National University of Ireland, Galway, Ireland. eugenie.dalimier@nuigalway.ieen
dc.identifier.journalJournal of visionen
refterms.dateFOA2018-09-03T10:28:50Z
html.description.abstractBased on standard procedures used in optometry clinics, we compare measurements of visual acuity for 10 subjects (11 eyes tested) in the presence of natural ocular aberrations and different degrees of induced defocus, with the predictions given by a Bayesian model customized with aberrometric data of the eye. The absolute predictions of the model, without any adjustment, show good agreement with the experimental data, in terms of correlation and absolute error. The efficiency of the model is discussed in comparison with image quality metrics and other customized visual process models. An analysis of the importance and customization of each stage of the model is also given; it stresses the potential high predictive power from precise modeling of ocular and neural transfer functions.


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