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dc.contributor.authorRomero-Bascones, David
dc.contributor.authorBarrenechea, Maitane
dc.contributor.authorMurueta-Goyena Larrañaga, Ane
dc.contributor.authorGaldós Iztueta, Marta
dc.contributor.authorGómez Esteban, Juan Carlos
dc.contributor.authorGabilondo Cuellar, Iñigo
dc.contributor.authorAyala, Unai
dc.date.accessioned2021-07-02T10:14:14Z
dc.date.available2021-07-02T10:14:14Z
dc.date.issued2021-06-01
dc.identifier.citationEntropy 23(6) : (2021) // Article ID 699es_ES
dc.identifier.issn1099-4300
dc.identifier.urihttp://hdl.handle.net/10810/52155
dc.description.abstractDisentangling the cellular anatomy that gives rise to human visual perception is one of the main challenges of ophthalmology. Of particular interest is the foveal pit, a concave depression located at the center of the retina that captures light from the gaze center. In recent years, there has been a growing interest in studying the morphology of the foveal pit by extracting geometrical features from optical coherence tomography (OCT) images. Despite this, research has devoted little attention to comparing existing approaches for two key methodological steps: the location of the foveal center and the mathematical modelling of the foveal pit. Building upon a dataset of 185 healthy subjects imaged twice, in the present paper the image alignment accuracy of four different foveal center location methods is studied in the first place. Secondly, state-of-the-art foveal pit mathematical models are compared in terms of fitting error, repeatability, and bias. The results indicate the importance of using a robust foveal center location method to align images. Moreover, we show that foveal pit models can improve the agreement between different acquisition protocols. Nevertheless, they can also introduce important biases in the parameter estimates that should be considered.es_ES
dc.description.sponsorshipThis research was funded by the Department of Health of the Basque Government through the projects 2019111100 and 2020333033, Instituto de Salud Carlos III through the project PI16/00005 (Co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”/”Investing in your future”) and the Basque Foundation for Health Innovation and Research (BIOEF) through the 2017 EITB Telemaratoia call (BIO17/ND/010).es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectoptical coherence tomographyes_ES
dc.subjectretinaes_ES
dc.subjectfoveaes_ES
dc.subjectretinal imaginges_ES
dc.titleFoveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Stepses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2021-06-24T14:10:59Z
dc.rights.holder2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/1099-4300/23/6/699/htmes_ES
dc.identifier.doi10.3390/e23060699
dc.departamentoesMedicina preventiva y salud pública
dc.departamentoeuPrebentzio medikuntza eta osasun publikoa


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2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).