Segmentation of retinal vasculature in colour fundus images

Yong Pang Kee; Iznita I. Lila; Fadzil M.H. Ahmad; A. N. Hanung; N. Hermawan; S. A. Vijanth

doi:10.1109/CITISIA.2009.5224176

Segmentation of retinal vasculature in colour fundus images

Yong Pang Kee
, Iznita I. Lila
, Fadzil M.H. Ahmad
, A. N. Hanung
, N. Hermawan
, S. A. Vijanth

Universiti Teknologi Petronas

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

14 Citations (Scopus)

Abstract

Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This paper presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing image enhancement using CLAHE followed by Bottomhat morphological transformation. Active contour model (snake) is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. A Graphic User Interface (GUI) has also been created to ease the user for the segmentation of the retinal vasculature.

Original language	English
Title of host publication	2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009
Pages	398-401
Number of pages	4
DOIs	https://doi.org/10.1109/CITISIA.2009.5224176
Publication status	Published - 2009
Externally published	Yes
Event	2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009 - Kuala Lumpur, Malaysia Duration: 25 Jul 2009 → 26 Jul 2009

Publication series

Name	2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009

Conference

Conference	2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009
Country/Territory	Malaysia
City	Kuala Lumpur
Period	25/07/09 → 26/07/09

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Active contour model
Fundus images
Retinal vasculature
Vessel segmentation

Access to Document

10.1109/CITISIA.2009.5224176

Cite this

Kee, Y. P., Lila, I. I., Ahmad, F. M. H., Hanung, A. N., Hermawan, N., & Vijanth, S. A. (2009). Segmentation of retinal vasculature in colour fundus images. In 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009 (pp. 398-401). Article 5224176 (2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009). https://doi.org/10.1109/CITISIA.2009.5224176

@inproceedings{c80cb43967a0448489451a402cc1f072,

title = "Segmentation of retinal vasculature in colour fundus images",

abstract = "Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This paper presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing image enhancement using CLAHE followed by Bottomhat morphological transformation. Active contour model (snake) is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. A Graphic User Interface (GUI) has also been created to ease the user for the segmentation of the retinal vasculature.",

keywords = "Active contour model, Fundus images, Retinal vasculature, Vessel segmentation",

author = "Kee, \{Yong Pang\} and Lila, \{Iznita I.\} and Ahmad, \{Fadzil M.H.\} and Hanung, \{A. N.\} and N. Hermawan and Vijanth, \{S. A.\}",

year = "2009",

doi = "10.1109/CITISIA.2009.5224176",

language = "English",

isbn = "9781424428878",

series = "2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009",

pages = "398--401",

booktitle = "2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009",

note = "2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009 ; Conference date: 25-07-2009 Through 26-07-2009",

}

Kee, YP, Lila, II, Ahmad, FMH, Hanung, AN, Hermawan, N & Vijanth, SA 2009, Segmentation of retinal vasculature in colour fundus images. in 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009., 5224176, 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009, pp. 398-401, 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009, Kuala Lumpur, Malaysia, 25/07/09. https://doi.org/10.1109/CITISIA.2009.5224176

Segmentation of retinal vasculature in colour fundus images. / Kee, Yong Pang; Lila, Iznita I.; Ahmad, Fadzil M.H. et al.
2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009. 2009. p. 398-401 5224176 (2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009).

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

TY - GEN

T1 - Segmentation of retinal vasculature in colour fundus images

AU - Kee, Yong Pang

AU - Lila, Iznita I.

AU - Ahmad, Fadzil M.H.

AU - Hanung, A. N.

AU - Hermawan, N.

AU - Vijanth, S. A.

PY - 2009

Y1 - 2009

N2 - Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This paper presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing image enhancement using CLAHE followed by Bottomhat morphological transformation. Active contour model (snake) is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. A Graphic User Interface (GUI) has also been created to ease the user for the segmentation of the retinal vasculature.

AB - Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This paper presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing image enhancement using CLAHE followed by Bottomhat morphological transformation. Active contour model (snake) is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. A Graphic User Interface (GUI) has also been created to ease the user for the segmentation of the retinal vasculature.

KW - Active contour model

KW - Fundus images

KW - Retinal vasculature

KW - Vessel segmentation

UR - https://www.scopus.com/pages/publications/70449098011

U2 - 10.1109/CITISIA.2009.5224176

DO - 10.1109/CITISIA.2009.5224176

M3 - Conference contribution

AN - SCOPUS:70449098011

SN - 9781424428878

T3 - 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009

SP - 398

EP - 401

BT - 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009

T2 - 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009

Y2 - 25 July 2009 through 26 July 2009

ER -

Kee YP, Lila II, Ahmad FMH, Hanung AN, Hermawan N, Vijanth SA. Segmentation of retinal vasculature in colour fundus images. In 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009. 2009. p. 398-401. 5224176. (2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009). doi: 10.1109/CITISIA.2009.5224176

Segmentation of retinal vasculature in colour fundus images

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this