DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity

Retinopathy of Prematurity (ROP) affects preterm neonates and could cause blindness. Deep Learning (DL) can assist ophthalmologists in the diagnosis of ROP. This paper proposes an automated and reliable diagnostic tool based on DL techniques called DIAROP to support the ophthalmologic diagnosis of R...

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Autor principal:	Omneya Attallah
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Retinopathy of Prematurity (ROP) Deep Learning (DL) transfer learning Convolutional Neural Networks (CNN) Computer-Aided Diagnosis Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/1c087511efde4ca2a357748cad11289c
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spelling	oai:doaj.org-article:1c087511efde4ca2a357748cad11289c2021-11-25T17:20:58ZDIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity10.3390/diagnostics111120342075-4418https://doaj.org/article/1c087511efde4ca2a357748cad11289c2021-11-01T00:00:00Zhttps://www.mdpi.com/2075-4418/11/11/2034https://doaj.org/toc/2075-4418Retinopathy of Prematurity (ROP) affects preterm neonates and could cause blindness. Deep Learning (DL) can assist ophthalmologists in the diagnosis of ROP. This paper proposes an automated and reliable diagnostic tool based on DL techniques called DIAROP to support the ophthalmologic diagnosis of ROP. It extracts significant features by first obtaining spatial features from the four Convolution Neural Networks (CNNs) DL techniques using transfer learning and then applying Fast Walsh Hadamard Transform (FWHT) to integrate these features. Moreover, DIAROP explores the best-integrated features extracted from the CNNs that influence its diagnostic capability. The results of DIAROP indicate that DIAROP achieved an accuracy of 93.2% and an area under receiving operating characteristic curve (AUC) of 0.98. Furthermore, DIAROP performance is compared with recent ROP diagnostic tools. Its promising performance shows that DIAROP may assist the ophthalmologic diagnosis of ROP.Omneya AttallahMDPI AGarticleRetinopathy of Prematurity (ROP)Deep Learning (DL)transfer learningConvolutional Neural Networks (CNN)Computer-Aided DiagnosisMedicine (General)R5-920ENDiagnostics, Vol 11, Iss 2034, p 2034 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Retinopathy of Prematurity (ROP) Deep Learning (DL) transfer learning Convolutional Neural Networks (CNN) Computer-Aided Diagnosis Medicine (General) R5-920
spellingShingle	Retinopathy of Prematurity (ROP) Deep Learning (DL) transfer learning Convolutional Neural Networks (CNN) Computer-Aided Diagnosis Medicine (General) R5-920 Omneya Attallah DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity
description	Retinopathy of Prematurity (ROP) affects preterm neonates and could cause blindness. Deep Learning (DL) can assist ophthalmologists in the diagnosis of ROP. This paper proposes an automated and reliable diagnostic tool based on DL techniques called DIAROP to support the ophthalmologic diagnosis of ROP. It extracts significant features by first obtaining spatial features from the four Convolution Neural Networks (CNNs) DL techniques using transfer learning and then applying Fast Walsh Hadamard Transform (FWHT) to integrate these features. Moreover, DIAROP explores the best-integrated features extracted from the CNNs that influence its diagnostic capability. The results of DIAROP indicate that DIAROP achieved an accuracy of 93.2% and an area under receiving operating characteristic curve (AUC) of 0.98. Furthermore, DIAROP performance is compared with recent ROP diagnostic tools. Its promising performance shows that DIAROP may assist the ophthalmologic diagnosis of ROP.
format	article
author	Omneya Attallah
author_facet	Omneya Attallah
author_sort	Omneya Attallah
title	DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity
title_short	DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity
title_full	DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity
title_fullStr	DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity
title_full_unstemmed	DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity
title_sort	diarop: automated deep learning-based diagnostic tool for retinopathy of prematurity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1c087511efde4ca2a357748cad11289c
work_keys_str_mv	AT omneyaattallah diaropautomateddeeplearningbaseddiagnostictoolforretinopathyofprematurity
_version_	1718412454903414784

DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity

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