Automatically Enhanced OCT Scans of the Retina: A proof of concept study

In this work we evaluated a postprocessing, customized automatic retinal OCT B-scan enhancement software for noise reduction, contrast enhancement and improved depth quality applicable to Heidelberg Engineering Spectralis OCT devices. A trained deep neural network was used to process images from an...

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Autores principales: Apostolopoulos, Stefanos, Salas, Jazmín, Ordóñez, José L. P., Tan, Shern Shiou, Ciller, Carlos, Ebneter, Andreas, Zinkernagel, Martin, Sznitman, Raphael, Wolf, Sebastian, De Zanet, Sandro, Munk, Marion R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7210925/
https://www.ncbi.nlm.nih.gov/pubmed/32385371
http://dx.doi.org/10.1038/s41598-020-64724-8
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author Apostolopoulos, Stefanos
Salas, Jazmín
Ordóñez, José L. P.
Tan, Shern Shiou
Ciller, Carlos
Ebneter, Andreas
Zinkernagel, Martin
Sznitman, Raphael
Wolf, Sebastian
De Zanet, Sandro
Munk, Marion R.
author_facet Apostolopoulos, Stefanos
Salas, Jazmín
Ordóñez, José L. P.
Tan, Shern Shiou
Ciller, Carlos
Ebneter, Andreas
Zinkernagel, Martin
Sznitman, Raphael
Wolf, Sebastian
De Zanet, Sandro
Munk, Marion R.
author_sort Apostolopoulos, Stefanos
collection PubMed
description In this work we evaluated a postprocessing, customized automatic retinal OCT B-scan enhancement software for noise reduction, contrast enhancement and improved depth quality applicable to Heidelberg Engineering Spectralis OCT devices. A trained deep neural network was used to process images from an OCT dataset with ground truth biomarker gradings. Performance was assessed by the evaluation of two expert graders who evaluated image quality for B-scan with a clear preference for enhanced over original images. Objective measures such as SNR and noise estimation showed a significant improvement in quality. Presence grading of seven biomarkers IRF, SRF, ERM, Drusen, RPD, GA and iRORA resulted in similar intergrader agreement. Intergrader agreement was also compared with improvement in IRF and RPD, and disagreement in high variance biomarkers such as GA and iRORA.
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spelling pubmed-72109252020-05-15 Automatically Enhanced OCT Scans of the Retina: A proof of concept study Apostolopoulos, Stefanos Salas, Jazmín Ordóñez, José L. P. Tan, Shern Shiou Ciller, Carlos Ebneter, Andreas Zinkernagel, Martin Sznitman, Raphael Wolf, Sebastian De Zanet, Sandro Munk, Marion R. Sci Rep Article In this work we evaluated a postprocessing, customized automatic retinal OCT B-scan enhancement software for noise reduction, contrast enhancement and improved depth quality applicable to Heidelberg Engineering Spectralis OCT devices. A trained deep neural network was used to process images from an OCT dataset with ground truth biomarker gradings. Performance was assessed by the evaluation of two expert graders who evaluated image quality for B-scan with a clear preference for enhanced over original images. Objective measures such as SNR and noise estimation showed a significant improvement in quality. Presence grading of seven biomarkers IRF, SRF, ERM, Drusen, RPD, GA and iRORA resulted in similar intergrader agreement. Intergrader agreement was also compared with improvement in IRF and RPD, and disagreement in high variance biomarkers such as GA and iRORA. Nature Publishing Group UK 2020-05-08 /pmc/articles/PMC7210925/ /pubmed/32385371 http://dx.doi.org/10.1038/s41598-020-64724-8 Text en © The Author(s) 2020 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
Apostolopoulos, Stefanos
Salas, Jazmín
Ordóñez, José L. P.
Tan, Shern Shiou
Ciller, Carlos
Ebneter, Andreas
Zinkernagel, Martin
Sznitman, Raphael
Wolf, Sebastian
De Zanet, Sandro
Munk, Marion R.
Automatically Enhanced OCT Scans of the Retina: A proof of concept study
title Automatically Enhanced OCT Scans of the Retina: A proof of concept study
title_full Automatically Enhanced OCT Scans of the Retina: A proof of concept study
title_fullStr Automatically Enhanced OCT Scans of the Retina: A proof of concept study
title_full_unstemmed Automatically Enhanced OCT Scans of the Retina: A proof of concept study
title_short Automatically Enhanced OCT Scans of the Retina: A proof of concept study
title_sort automatically enhanced oct scans of the retina: a proof of concept study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7210925/
https://www.ncbi.nlm.nih.gov/pubmed/32385371
http://dx.doi.org/10.1038/s41598-020-64724-8
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