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Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps

Disentangling 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...

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Autores principales: Romero-Bascones, David, Barrenechea, Maitane, Murueta-Goyena, Ane, Galdós, Marta, Gómez-Esteban, Juan Carlos, Gabilondo, Iñigo, Ayala, Unai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227188/
https://www.ncbi.nlm.nih.gov/pubmed/34205877
http://dx.doi.org/10.3390/e23060699
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author Romero-Bascones, David
Barrenechea, Maitane
Murueta-Goyena, Ane
Galdós, Marta
Gómez-Esteban, Juan Carlos
Gabilondo, Iñigo
Ayala, Unai
author_facet Romero-Bascones, David
Barrenechea, Maitane
Murueta-Goyena, Ane
Galdós, Marta
Gómez-Esteban, Juan Carlos
Gabilondo, Iñigo
Ayala, Unai
author_sort Romero-Bascones, David
collection PubMed
description Disentangling 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.
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spelling pubmed-82271882021-06-26 Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps Romero-Bascones, David Barrenechea, Maitane Murueta-Goyena, Ane Galdós, Marta Gómez-Esteban, Juan Carlos Gabilondo, Iñigo Ayala, Unai Entropy (Basel) Article Disentangling 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. MDPI 2021-06-01 /pmc/articles/PMC8227188/ /pubmed/34205877 http://dx.doi.org/10.3390/e23060699 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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/).
spellingShingle Article
Romero-Bascones, David
Barrenechea, Maitane
Murueta-Goyena, Ane
Galdós, Marta
Gómez-Esteban, Juan Carlos
Gabilondo, Iñigo
Ayala, Unai
Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
title Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
title_full Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
title_fullStr Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
title_full_unstemmed Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
title_short Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
title_sort foveal pit morphology characterization: a quantitative analysis of the key methodological steps
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227188/
https://www.ncbi.nlm.nih.gov/pubmed/34205877
http://dx.doi.org/10.3390/e23060699
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