Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding

Dinial Utami Nurul Qomariah; Handayani Tjandrasa

doi:10.1109/ICTS.2017.8265642

Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding

Dinial Utami Nurul Qomariah
, Handayani Tjandrasa

Laboratory of Intelligent Computing and Vision

Institut Teknologi Sepuluh Nopember

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

15 Citations (Scopus)

Abstract

Diabetic retinopathy (DR) is a microvascular complication of diabetes, causing abnormalities in the retina, and it is can cause blindness. Diabetic retinopathy can be detected by the appearance of hard exudates. Hard exudates are lipid formations leaking from these weakened blood vessels. Automatic detection of exudates is an early handler to diagnose diabetic retinopathy. This research proposed automatic detection of exudates using Renyi entropy thresholding and mathematical morphology. Renyi entropy thresholding has a controlling variable so that the obtained threshold value is more optimal. The proposed method using Renyi entropy thresholding and mathematical morphology has three stages: (1) preprocessing using contrast enhancement, (2) initial exudates detection based on mathematical morphology, and (3) exudates detection based on Renyi entropy thresholding. The test was performed using measurement evaluation method, sensitivity, specificity, and accuracy were 85.06%, 99.63%, and 99.54% respectively.

Original language	English
Title of host publication	Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	31-36
Number of pages	6
ISBN (Electronic)	9781538628256
DOIs	https://doi.org/10.1109/ICTS.2017.8265642
Publication status	Published - 19 Jan 2018
Event	11th International Conference on Information and Communication Technology and System, ICTS 2017 - Surabaya, Indonesia Duration: 31 Oct 2017 → 31 Oct 2017

Publication series

Name	Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017
Volume	2018-January

Conference

Conference	11th International Conference on Information and Communication Technology and System, ICTS 2017
Country/Territory	Indonesia
City	Surabaya
Period	31/10/17 → 31/10/17

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Exudate
Mathematical Morphology
Renyi entropy thresholding
Segmentation

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10.1109/ICTS.2017.8265642

Cite this

Qomariah, D. U. N., & Tjandrasa, H. (2018). Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding. In Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017 (pp. 31-36). (Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTS.2017.8265642

Qomariah, Dinial Utami Nurul ; Tjandrasa, Handayani. / Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding. Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 31-36 (Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017).

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title = "Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding",

abstract = "Diabetic retinopathy (DR) is a microvascular complication of diabetes, causing abnormalities in the retina, and it is can cause blindness. Diabetic retinopathy can be detected by the appearance of hard exudates. Hard exudates are lipid formations leaking from these weakened blood vessels. Automatic detection of exudates is an early handler to diagnose diabetic retinopathy. This research proposed automatic detection of exudates using Renyi entropy thresholding and mathematical morphology. Renyi entropy thresholding has a controlling variable so that the obtained threshold value is more optimal. The proposed method using Renyi entropy thresholding and mathematical morphology has three stages: (1) preprocessing using contrast enhancement, (2) initial exudates detection based on mathematical morphology, and (3) exudates detection based on Renyi entropy thresholding. The test was performed using measurement evaluation method, sensitivity, specificity, and accuracy were 85.06\%, 99.63\%, and 99.54\% respectively.",

keywords = "Exudate, Mathematical Morphology, Renyi entropy thresholding, Segmentation",

author = "Qomariah, \{Dinial Utami Nurul\} and Handayani Tjandrasa",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 11th International Conference on Information and Communication Technology and System, ICTS 2017 ; Conference date: 31-10-2017 Through 31-10-2017",

year = "2018",

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doi = "10.1109/ICTS.2017.8265642",

language = "English",

series = "Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017",

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Qomariah, DUN & Tjandrasa, H 2018, Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding. in Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017. Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 31-36, 11th International Conference on Information and Communication Technology and System, ICTS 2017, Surabaya, Indonesia, 31/10/17. https://doi.org/10.1109/ICTS.2017.8265642

Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding. / Qomariah, Dinial Utami Nurul; Tjandrasa, Handayani.
Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 31-36 (Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017; Vol. 2018-January).

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

TY - GEN

T1 - Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding

AU - Qomariah, Dinial Utami Nurul

AU - Tjandrasa, Handayani

PY - 2018/1/19

Y1 - 2018/1/19

N2 - Diabetic retinopathy (DR) is a microvascular complication of diabetes, causing abnormalities in the retina, and it is can cause blindness. Diabetic retinopathy can be detected by the appearance of hard exudates. Hard exudates are lipid formations leaking from these weakened blood vessels. Automatic detection of exudates is an early handler to diagnose diabetic retinopathy. This research proposed automatic detection of exudates using Renyi entropy thresholding and mathematical morphology. Renyi entropy thresholding has a controlling variable so that the obtained threshold value is more optimal. The proposed method using Renyi entropy thresholding and mathematical morphology has three stages: (1) preprocessing using contrast enhancement, (2) initial exudates detection based on mathematical morphology, and (3) exudates detection based on Renyi entropy thresholding. The test was performed using measurement evaluation method, sensitivity, specificity, and accuracy were 85.06%, 99.63%, and 99.54% respectively.

AB - Diabetic retinopathy (DR) is a microvascular complication of diabetes, causing abnormalities in the retina, and it is can cause blindness. Diabetic retinopathy can be detected by the appearance of hard exudates. Hard exudates are lipid formations leaking from these weakened blood vessels. Automatic detection of exudates is an early handler to diagnose diabetic retinopathy. This research proposed automatic detection of exudates using Renyi entropy thresholding and mathematical morphology. Renyi entropy thresholding has a controlling variable so that the obtained threshold value is more optimal. The proposed method using Renyi entropy thresholding and mathematical morphology has three stages: (1) preprocessing using contrast enhancement, (2) initial exudates detection based on mathematical morphology, and (3) exudates detection based on Renyi entropy thresholding. The test was performed using measurement evaluation method, sensitivity, specificity, and accuracy were 85.06%, 99.63%, and 99.54% respectively.

KW - Exudate

KW - Mathematical Morphology

KW - Renyi entropy thresholding

KW - Segmentation

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DO - 10.1109/ICTS.2017.8265642

M3 - Conference contribution

AN - SCOPUS:85050534246

T3 - Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017

SP - 31

EP - 36

BT - Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th International Conference on Information and Communication Technology and System, ICTS 2017

Y2 - 31 October 2017 through 31 October 2017

ER -

Qomariah DUN, Tjandrasa H. Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding. In Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 31-36. (Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017). doi: 10.1109/ICTS.2017.8265642

Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding

Abstract

Publication series

Conference

UN SDGs

Keywords

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