Automatic detection of pathological myopia using machine learning

Abstract Pathological myopia is a severe case of myopia, i.e., nearsightedness. Pathological myopia is also known as degenerative myopia because it ultimately leads to blindness. In pathological myopia, certain myopia-specific pathologies occur at the eye’s posterior i.e., Foster-Fuchs’s spot, Cysto...

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Autores principales:	Namra Rauf, Syed Omer Gilani, Asim Waris
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7ffad55c8e254665822f0227156e050d
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spelling	oai:doaj.org-article:7ffad55c8e254665822f0227156e050d2021-12-02T15:10:54ZAutomatic detection of pathological myopia using machine learning10.1038/s41598-021-95205-12045-2322https://doaj.org/article/7ffad55c8e254665822f0227156e050d2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95205-1https://doaj.org/toc/2045-2322Abstract Pathological myopia is a severe case of myopia, i.e., nearsightedness. Pathological myopia is also known as degenerative myopia because it ultimately leads to blindness. In pathological myopia, certain myopia-specific pathologies occur at the eye’s posterior i.e., Foster-Fuchs’s spot, Cystoid degeneration, Liquefaction, Macular degeneration, Vitreous opacities, Weiss’s reflex, Posterior staphyloma, etc. This research is aimed at developing a machine learning (ML) approach for the automatic detection of pathological myopia based on fundus images. A deep learning technique of convolutional neural network (CNN) is employed for this purpose. A CNN model is developed in Spyder. The fundus images are first preprocessed. The preprocessed images are then fed to the designed CNN model. The CNN model automatically extracts the features from the input images and classifies the images i.e., normal image or pathological myopia. The best performing CNN model achieved an AUC score of 0.9845. The best validation loss obtained is 0.1457. The results show that the model can be successfully employed to detect pathological myopia from the fundus images.Namra RaufSyed Omer GilaniAsim WarisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Namra Rauf Syed Omer Gilani Asim Waris Automatic detection of pathological myopia using machine learning
description	Abstract Pathological myopia is a severe case of myopia, i.e., nearsightedness. Pathological myopia is also known as degenerative myopia because it ultimately leads to blindness. In pathological myopia, certain myopia-specific pathologies occur at the eye’s posterior i.e., Foster-Fuchs’s spot, Cystoid degeneration, Liquefaction, Macular degeneration, Vitreous opacities, Weiss’s reflex, Posterior staphyloma, etc. This research is aimed at developing a machine learning (ML) approach for the automatic detection of pathological myopia based on fundus images. A deep learning technique of convolutional neural network (CNN) is employed for this purpose. A CNN model is developed in Spyder. The fundus images are first preprocessed. The preprocessed images are then fed to the designed CNN model. The CNN model automatically extracts the features from the input images and classifies the images i.e., normal image or pathological myopia. The best performing CNN model achieved an AUC score of 0.9845. The best validation loss obtained is 0.1457. The results show that the model can be successfully employed to detect pathological myopia from the fundus images.
format	article
author	Namra Rauf Syed Omer Gilani Asim Waris
author_facet	Namra Rauf Syed Omer Gilani Asim Waris
author_sort	Namra Rauf
title	Automatic detection of pathological myopia using machine learning
title_short	Automatic detection of pathological myopia using machine learning
title_full	Automatic detection of pathological myopia using machine learning
title_fullStr	Automatic detection of pathological myopia using machine learning
title_full_unstemmed	Automatic detection of pathological myopia using machine learning
title_sort	automatic detection of pathological myopia using machine learning
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7ffad55c8e254665822f0227156e050d
work_keys_str_mv	AT namrarauf automaticdetectionofpathologicalmyopiausingmachinelearning AT syedomergilani automaticdetectionofpathologicalmyopiausingmachinelearning AT asimwaris automaticdetectionofpathologicalmyopiausingmachinelearning
_version_	1718387640870371328

Automatic detection of pathological myopia using machine learning

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