Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images

Abstract Given the capacity of Optical Coherence Tomography (OCT) imaging to display structural changes in a wide variety of eye diseases and neurological disorders, the need for OCT image segmentation and the corresponding data interpretation is latterly felt more than ever before. In this paper, w...

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Autores principales: Mansooreh Montazerin, Zahra Sajjadifar, Elias Khalili Pour, Hamid Riazi-Esfahani, Tahereh Mahmoudi, Hossein Rabbani, Hossein Movahedian, Alireza Dehghani, Mohammadreza Akhlaghi, Rahele Kafieh
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Publicado: Nature Portfolio 2021
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spelling oai:doaj.org-article:e418d66acc344723906b16f575020da72021-12-02T16:10:37ZLivelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images10.1038/s41598-021-92713-y2045-2322https://doaj.org/article/e418d66acc344723906b16f575020da72021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92713-yhttps://doaj.org/toc/2045-2322Abstract Given the capacity of Optical Coherence Tomography (OCT) imaging to display structural changes in a wide variety of eye diseases and neurological disorders, the need for OCT image segmentation and the corresponding data interpretation is latterly felt more than ever before. In this paper, we wish to address this need by designing a semi-automatic software program for applying reliable segmentation of 8 different macular layers as well as outlining retinal pathologies such as diabetic macular edema. The software accommodates a novel graph-based semi-automatic method, called “Livelayer” which is designed for straightforward segmentation of retinal layers and fluids. This method is chiefly based on Dijkstra’s Shortest Path First (SPF) algorithm and the Live-wire function together with some preprocessing operations on the to-be-segmented images. The software is indeed suitable for obtaining detailed segmentation of layers, exact localization of clear or unclear fluid objects and the ground truth, demanding far less endeavor in comparison to a common manual segmentation method. It is also valuable as a tool for calculating the irregularity index in deformed OCT images. The amount of time (seconds) that Livelayer required for segmentation of Inner Limiting Membrane, Inner Plexiform Layer–Inner Nuclear Layer, Outer Plexiform Layer–Outer Nuclear Layer was much less than that for the manual segmentation, 5 s for the ILM (minimum) and 15.57 s for the OPL–ONL (maximum). The unsigned errors (pixels) between the semi-automatically labeled and gold standard data was on average 2.7, 1.9, 2.1 for ILM, IPL–INL, OPL–ONL, respectively. The Bland–Altman plots indicated perfect concordance between the Livelayer and the manual algorithm and that they could be used interchangeably. The repeatability error was around one pixel for the OPL–ONL and < 1 for the other two. The unsigned errors between the Livelayer and the manual algorithm was 1.33 for ILM and 1.53 for Nerve Fiber Layer–Ganglion Cell Layer in peripapillary B-Scans. The Dice scores for comparing the two algorithms and for obtaining the repeatability on segmentation of fluid objects were at acceptable levels.Mansooreh MontazerinZahra SajjadifarElias Khalili PourHamid Riazi-EsfahaniTahereh MahmoudiHossein RabbaniHossein MovahedianAlireza DehghaniMohammadreza AkhlaghiRahele KafiehNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Mansooreh Montazerin
Zahra Sajjadifar
Elias Khalili Pour
Hamid Riazi-Esfahani
Tahereh Mahmoudi
Hossein Rabbani
Hossein Movahedian
Alireza Dehghani
Mohammadreza Akhlaghi
Rahele Kafieh
Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
description Abstract Given the capacity of Optical Coherence Tomography (OCT) imaging to display structural changes in a wide variety of eye diseases and neurological disorders, the need for OCT image segmentation and the corresponding data interpretation is latterly felt more than ever before. In this paper, we wish to address this need by designing a semi-automatic software program for applying reliable segmentation of 8 different macular layers as well as outlining retinal pathologies such as diabetic macular edema. The software accommodates a novel graph-based semi-automatic method, called “Livelayer” which is designed for straightforward segmentation of retinal layers and fluids. This method is chiefly based on Dijkstra’s Shortest Path First (SPF) algorithm and the Live-wire function together with some preprocessing operations on the to-be-segmented images. The software is indeed suitable for obtaining detailed segmentation of layers, exact localization of clear or unclear fluid objects and the ground truth, demanding far less endeavor in comparison to a common manual segmentation method. It is also valuable as a tool for calculating the irregularity index in deformed OCT images. The amount of time (seconds) that Livelayer required for segmentation of Inner Limiting Membrane, Inner Plexiform Layer–Inner Nuclear Layer, Outer Plexiform Layer–Outer Nuclear Layer was much less than that for the manual segmentation, 5 s for the ILM (minimum) and 15.57 s for the OPL–ONL (maximum). The unsigned errors (pixels) between the semi-automatically labeled and gold standard data was on average 2.7, 1.9, 2.1 for ILM, IPL–INL, OPL–ONL, respectively. The Bland–Altman plots indicated perfect concordance between the Livelayer and the manual algorithm and that they could be used interchangeably. The repeatability error was around one pixel for the OPL–ONL and < 1 for the other two. The unsigned errors between the Livelayer and the manual algorithm was 1.33 for ILM and 1.53 for Nerve Fiber Layer–Ganglion Cell Layer in peripapillary B-Scans. The Dice scores for comparing the two algorithms and for obtaining the repeatability on segmentation of fluid objects were at acceptable levels.
format article
author Mansooreh Montazerin
Zahra Sajjadifar
Elias Khalili Pour
Hamid Riazi-Esfahani
Tahereh Mahmoudi
Hossein Rabbani
Hossein Movahedian
Alireza Dehghani
Mohammadreza Akhlaghi
Rahele Kafieh
author_facet Mansooreh Montazerin
Zahra Sajjadifar
Elias Khalili Pour
Hamid Riazi-Esfahani
Tahereh Mahmoudi
Hossein Rabbani
Hossein Movahedian
Alireza Dehghani
Mohammadreza Akhlaghi
Rahele Kafieh
author_sort Mansooreh Montazerin
title Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
title_short Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
title_full Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
title_fullStr Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
title_full_unstemmed Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
title_sort livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/e418d66acc344723906b16f575020da7
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