Unsupervised feature extraction of anterior chamber OCT images for ordering and classification

We propose an image processing method for ordering anterior chamber optical coherence tomography (OCT) images in a fully unsupervised manner. The method consists of three steps: Firstly we preprocess the images (filtering the noise, aligning and normalizing the resolution); secondly, a distance meas...

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Detalles Bibliográficos
Autores principales: Amil, Pablo, González, Laura, Arrondo, Elena, Salinas, Cecilia, Guell, J. L., Masoller, Cristina, Parlitz, Ulrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362085/
https://www.ncbi.nlm.nih.gov/pubmed/30718688
http://dx.doi.org/10.1038/s41598-018-38136-8
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author Amil, Pablo
González, Laura
Arrondo, Elena
Salinas, Cecilia
Guell, J. L.
Masoller, Cristina
Parlitz, Ulrich
author_facet Amil, Pablo
González, Laura
Arrondo, Elena
Salinas, Cecilia
Guell, J. L.
Masoller, Cristina
Parlitz, Ulrich
author_sort Amil, Pablo
collection PubMed
description We propose an image processing method for ordering anterior chamber optical coherence tomography (OCT) images in a fully unsupervised manner. The method consists of three steps: Firstly we preprocess the images (filtering the noise, aligning and normalizing the resolution); secondly, a distance measure between images is computed for every pair of images; thirdly we apply a machine learning algorithm that exploits the distance measure to order the images in a two-dimensional plane. The method is applied to a large (~1000) database of anterior chamber OCT images of healthy subjects and patients with angle-closure and the resulting unsupervised ordering and classification is validated by two ophthalmologists.
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spelling pubmed-63620852019-02-06 Unsupervised feature extraction of anterior chamber OCT images for ordering and classification Amil, Pablo González, Laura Arrondo, Elena Salinas, Cecilia Guell, J. L. Masoller, Cristina Parlitz, Ulrich Sci Rep Article We propose an image processing method for ordering anterior chamber optical coherence tomography (OCT) images in a fully unsupervised manner. The method consists of three steps: Firstly we preprocess the images (filtering the noise, aligning and normalizing the resolution); secondly, a distance measure between images is computed for every pair of images; thirdly we apply a machine learning algorithm that exploits the distance measure to order the images in a two-dimensional plane. The method is applied to a large (~1000) database of anterior chamber OCT images of healthy subjects and patients with angle-closure and the resulting unsupervised ordering and classification is validated by two ophthalmologists. Nature Publishing Group UK 2019-02-04 /pmc/articles/PMC6362085/ /pubmed/30718688 http://dx.doi.org/10.1038/s41598-018-38136-8 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Amil, Pablo
González, Laura
Arrondo, Elena
Salinas, Cecilia
Guell, J. L.
Masoller, Cristina
Parlitz, Ulrich
Unsupervised feature extraction of anterior chamber OCT images for ordering and classification
title Unsupervised feature extraction of anterior chamber OCT images for ordering and classification
title_full Unsupervised feature extraction of anterior chamber OCT images for ordering and classification
title_fullStr Unsupervised feature extraction of anterior chamber OCT images for ordering and classification
title_full_unstemmed Unsupervised feature extraction of anterior chamber OCT images for ordering and classification
title_short Unsupervised feature extraction of anterior chamber OCT images for ordering and classification
title_sort unsupervised feature extraction of anterior chamber oct images for ordering and classification
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362085/
https://www.ncbi.nlm.nih.gov/pubmed/30718688
http://dx.doi.org/10.1038/s41598-018-38136-8
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