Cargando…

Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns

Age-related macular degeneration is a visual disorder caused by abnormalities in a part of the eye’s retina and is a leading source of blindness. The correct detection, precise location, classification, and diagnosis of choroidal neovascularization (CNV) may be challenging if the lesion is small or...

Descripción completa

Detalles Bibliográficos
Autores principales: Liew, Alex, Agaian, Sos, Benbelkacem, Samir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9956029/
https://www.ncbi.nlm.nih.gov/pubmed/36832215
http://dx.doi.org/10.3390/diagnostics13040729
_version_ 1784894492314173440
author Liew, Alex
Agaian, Sos
Benbelkacem, Samir
author_facet Liew, Alex
Agaian, Sos
Benbelkacem, Samir
author_sort Liew, Alex
collection PubMed
description Age-related macular degeneration is a visual disorder caused by abnormalities in a part of the eye’s retina and is a leading source of blindness. The correct detection, precise location, classification, and diagnosis of choroidal neovascularization (CNV) may be challenging if the lesion is small or if Optical Coherence Tomography (OCT) images are degraded by projection and motion. This paper aims to develop an automated quantification and classification system for CNV in neovascular age-related macular degeneration using OCT angiography images. OCT angiography is a non-invasive imaging tool that visualizes retinal and choroidal physiological and pathological vascularization. The presented system is based on new retinal layers in the OCT image-specific macular diseases feature extractor, including Multi-Size Kernels ξcho-Weighted Median Patterns (MSKξMP). Computer simulations show that the proposed method: (i) outperforms current state-of-the-art methods, including deep learning techniques; and (ii) achieves an overall accuracy of 99% using ten-fold cross-validation on the Duke University dataset and over 96% on the noisy Noor Eye Hospital dataset. In addition, MSKξMP performs well in binary eye disease classifications and is more accurate than recent works in image texture descriptors.
format Online
Article
Text
id pubmed-9956029
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-99560292023-02-25 Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns Liew, Alex Agaian, Sos Benbelkacem, Samir Diagnostics (Basel) Article Age-related macular degeneration is a visual disorder caused by abnormalities in a part of the eye’s retina and is a leading source of blindness. The correct detection, precise location, classification, and diagnosis of choroidal neovascularization (CNV) may be challenging if the lesion is small or if Optical Coherence Tomography (OCT) images are degraded by projection and motion. This paper aims to develop an automated quantification and classification system for CNV in neovascular age-related macular degeneration using OCT angiography images. OCT angiography is a non-invasive imaging tool that visualizes retinal and choroidal physiological and pathological vascularization. The presented system is based on new retinal layers in the OCT image-specific macular diseases feature extractor, including Multi-Size Kernels ξcho-Weighted Median Patterns (MSKξMP). Computer simulations show that the proposed method: (i) outperforms current state-of-the-art methods, including deep learning techniques; and (ii) achieves an overall accuracy of 99% using ten-fold cross-validation on the Duke University dataset and over 96% on the noisy Noor Eye Hospital dataset. In addition, MSKξMP performs well in binary eye disease classifications and is more accurate than recent works in image texture descriptors. MDPI 2023-02-14 /pmc/articles/PMC9956029/ /pubmed/36832215 http://dx.doi.org/10.3390/diagnostics13040729 Text en © 2023 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
Liew, Alex
Agaian, Sos
Benbelkacem, Samir
Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns
title Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns
title_full Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns
title_fullStr Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns
title_full_unstemmed Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns
title_short Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns
title_sort distinctions between choroidal neovascularization and age macular degeneration in ocular disease predictions via multi-size kernels ξcho-weighted median patterns
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9956029/
https://www.ncbi.nlm.nih.gov/pubmed/36832215
http://dx.doi.org/10.3390/diagnostics13040729
work_keys_str_mv AT liewalex distinctionsbetweenchoroidalneovascularizationandagemaculardegenerationinoculardiseasepredictionsviamultisizekernelsxchoweightedmedianpatterns
AT agaiansos distinctionsbetweenchoroidalneovascularizationandagemaculardegenerationinoculardiseasepredictionsviamultisizekernelsxchoweightedmedianpatterns
AT benbelkacemsamir distinctionsbetweenchoroidalneovascularizationandagemaculardegenerationinoculardiseasepredictionsviamultisizekernelsxchoweightedmedianpatterns