Detection of diabetic retinopathy using image processing

Ratikanlaya Tanthuwapathom; Narit Hnoohom

doi:10.1007/978-3-319-70016-8_22

Detection of diabetic retinopathy using image processing

Ratikanlaya Tanthuwapathom
, Narit Hnoohom

Department of Computer Engineering

Mahidol University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Diabetic retinopathy has been found in from 22% of diabetic patients from the latest survey, which can lead to blindness later. Thus, eye exams should be scheduled no less than annually for patients with diabetes. On the other hand, there is an apparent deficiency in the number of medical professionals specializing in ophthalmology, which may hinder the discovery and care of diabetic retinopathy. The idea to stimulate a detection system for screening of diabetic retinopathy by using morphological and image segmentation methods to facilitate and make a preliminary decision with ophthalmologists is introduced. From the experimental results, the detection system provides good exudate detection and classification results for all 60 retina images for accurate up to 85%.

Original language	English
Title of host publication	Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology
Editors	Rachada Kongkachandra, Thepchai Supnithi, Thanaruk Theeramunkong
Publisher	Springer Verlag
Pages	259-265
Number of pages	7
ISBN (Print)	9783319700151
DOIs	https://doi.org/10.1007/978-3-319-70016-8_22
Publication status	Published - 2018
Event	11th International Symposium on Natural Language Processing, SNLP-2016 and 1st Workshop in Intelligent Informatics and Smart Technology, 2016 - Phranakhon Si Ayutthaya, Thailand Duration: 10 Feb 2016 → 12 Feb 2016

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	684
ISSN (Print)	2194-5357

Conference

Conference	11th International Symposium on Natural Language Processing, SNLP-2016 and 1st Workshop in Intelligent Informatics and Smart Technology, 2016
Country/Territory	Thailand
City	Phranakhon Si Ayutthaya
Period	10/02/16 → 12/02/16

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Exudate
Microaneurysms
Optic disc
Retina image
Retinal hemorrhages

Access to Document

10.1007/978-3-319-70016-8_22

Cite this

Tanthuwapathom, R., & Hnoohom, N. (2018). Detection of diabetic retinopathy using image processing. In R. Kongkachandra, T. Supnithi, & T. Theeramunkong (Eds.), Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology (pp. 259-265). (Advances in Intelligent Systems and Computing; Vol. 684). Springer Verlag. https://doi.org/10.1007/978-3-319-70016-8_22

Tanthuwapathom, Ratikanlaya ; Hnoohom, Narit. / Detection of diabetic retinopathy using image processing. Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology. editor / Rachada Kongkachandra ; Thepchai Supnithi ; Thanaruk Theeramunkong. Springer Verlag, 2018. pp. 259-265 (Advances in Intelligent Systems and Computing).

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title = "Detection of diabetic retinopathy using image processing",

abstract = "Diabetic retinopathy has been found in from 22\% of diabetic patients from the latest survey, which can lead to blindness later. Thus, eye exams should be scheduled no less than annually for patients with diabetes. On the other hand, there is an apparent deficiency in the number of medical professionals specializing in ophthalmology, which may hinder the discovery and care of diabetic retinopathy. The idea to stimulate a detection system for screening of diabetic retinopathy by using morphological and image segmentation methods to facilitate and make a preliminary decision with ophthalmologists is introduced. From the experimental results, the detection system provides good exudate detection and classification results for all 60 retina images for accurate up to 85\%.",

keywords = "Exudate, Microaneurysms, Optic disc, Retina image, Retinal hemorrhages",

author = "Ratikanlaya Tanthuwapathom and Narit Hnoohom",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.; 11th International Symposium on Natural Language Processing, SNLP-2016 and 1st Workshop in Intelligent Informatics and Smart Technology, 2016 ; Conference date: 10-02-2016 Through 12-02-2016",

year = "2018",

doi = "10.1007/978-3-319-70016-8\_22",

language = "English",

isbn = "9783319700151",

series = "Advances in Intelligent Systems and Computing",

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editor = "Rachada Kongkachandra and Thepchai Supnithi and Thanaruk Theeramunkong",

booktitle = "Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology",

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Tanthuwapathom, R & Hnoohom, N 2018, Detection of diabetic retinopathy using image processing. in R Kongkachandra, T Supnithi & T Theeramunkong (eds), Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology. Advances in Intelligent Systems and Computing, vol. 684, Springer Verlag, pp. 259-265, 11th International Symposium on Natural Language Processing, SNLP-2016 and 1st Workshop in Intelligent Informatics and Smart Technology, 2016, Phranakhon Si Ayutthaya, Thailand, 10/02/16. https://doi.org/10.1007/978-3-319-70016-8_22

Detection of diabetic retinopathy using image processing. / Tanthuwapathom, Ratikanlaya; Hnoohom, Narit.
Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology. ed. / Rachada Kongkachandra; Thepchai Supnithi; Thanaruk Theeramunkong. Springer Verlag, 2018. p. 259-265 (Advances in Intelligent Systems and Computing; Vol. 684).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Tanthuwapathom, Ratikanlaya

AU - Hnoohom, Narit

N1 - Publisher Copyright: © Springer International Publishing AG 2018.

PY - 2018

Y1 - 2018

N2 - Diabetic retinopathy has been found in from 22% of diabetic patients from the latest survey, which can lead to blindness later. Thus, eye exams should be scheduled no less than annually for patients with diabetes. On the other hand, there is an apparent deficiency in the number of medical professionals specializing in ophthalmology, which may hinder the discovery and care of diabetic retinopathy. The idea to stimulate a detection system for screening of diabetic retinopathy by using morphological and image segmentation methods to facilitate and make a preliminary decision with ophthalmologists is introduced. From the experimental results, the detection system provides good exudate detection and classification results for all 60 retina images for accurate up to 85%.

AB - Diabetic retinopathy has been found in from 22% of diabetic patients from the latest survey, which can lead to blindness later. Thus, eye exams should be scheduled no less than annually for patients with diabetes. On the other hand, there is an apparent deficiency in the number of medical professionals specializing in ophthalmology, which may hinder the discovery and care of diabetic retinopathy. The idea to stimulate a detection system for screening of diabetic retinopathy by using morphological and image segmentation methods to facilitate and make a preliminary decision with ophthalmologists is introduced. From the experimental results, the detection system provides good exudate detection and classification results for all 60 retina images for accurate up to 85%.

KW - Exudate

KW - Microaneurysms

KW - Optic disc

KW - Retina image

KW - Retinal hemorrhages

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BT - Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology

A2 - Kongkachandra, Rachada

A2 - Supnithi, Thepchai

A2 - Theeramunkong, Thanaruk

PB - Springer Verlag

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ER -

Tanthuwapathom R, Hnoohom N. Detection of diabetic retinopathy using image processing. In Kongkachandra R, Supnithi T, Theeramunkong T, editors, Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology. Springer Verlag. 2018. p. 259-265. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-70016-8_22

Detection of diabetic retinopathy using image processing

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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