Ophthalmic diagnosis using deep learning with fundus images – A critical review

Sourya Sengupta; Amitojdeep Singh; Henry A. Leopold; Tanmay Gulati; Vasudevan Lakshminarayanan

doi:10.1016/j.artmed.2019.101758

Ophthalmic diagnosis using deep learning with fundus images – A critical review

Sourya Sengupta^*
, Amitojdeep Singh
, Henry A. Leopold
, Tanmay Gulati
, Vasudevan Lakshminarayanan

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

178 Citations (Scopus)

Abstract

An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, optic cup, blood vessels as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, and diabetic retinopathy are also discussed. Important critical insights and future research directions are given.

Original language	English
Article number	101758
Journal	Artificial Intelligence in Medicine
Volume	102
DOIs	https://doi.org/10.1016/j.artmed.2019.101758
Publication status	Published - 01-2020
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Medicine (miscellaneous)
Artificial Intelligence

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10.1016/j.artmed.2019.101758

Cite this

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title = "Ophthalmic diagnosis using deep learning with fundus images – A critical review",

abstract = "An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, optic cup, blood vessels as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, and diabetic retinopathy are also discussed. Important critical insights and future research directions are given.",

author = "Sourya Sengupta and Amitojdeep Singh and Leopold, \{Henry A.\} and Tanmay Gulati and Vasudevan Lakshminarayanan",

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year = "2020",

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doi = "10.1016/j.artmed.2019.101758",

language = "English",

volume = "102",

journal = "Artificial Intelligence in Medicine",

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AU - Sengupta, Sourya

AU - Singh, Amitojdeep

AU - Leopold, Henry A.

AU - Gulati, Tanmay

AU - Lakshminarayanan, Vasudevan

PY - 2020/1

Y1 - 2020/1

N2 - An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, optic cup, blood vessels as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, and diabetic retinopathy are also discussed. Important critical insights and future research directions are given.

AB - An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, optic cup, blood vessels as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, and diabetic retinopathy are also discussed. Important critical insights and future research directions are given.

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UR - https://www.scopus.com/pages/publications/85076241283#tab=citedBy

U2 - 10.1016/j.artmed.2019.101758

DO - 10.1016/j.artmed.2019.101758

M3 - Review article

C2 - 31980096

AN - SCOPUS:85076241283

SN - 0933-3657

VL - 102

JO - Artificial Intelligence in Medicine

JF - Artificial Intelligence in Medicine

M1 - 101758

ER -

Ophthalmic diagnosis using deep learning with fundus images – A critical review

Abstract

UN SDGs

All Science Journal Classification (ASJC) codes

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