Retinal vessel measurement using model fitting approach

Huiqi Li

doi:10.1109/ICIEA.2012.6361009

Retinal vessel measurement using model fitting approach

Huiqi Li^*

^*Corresponding author for this work

School of Information and Electronics

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

Abstract

Retinal vessels provide essential information for diagnosing retinal diseases and other diseases. Vessel detection and measurement in color retinal images are investigated in this paper. The source of blood vessels is identified by the matched Gaussian filter. A vessel is tracked from its source by the combined Gaussian and Kalman filters. A modified Gaussian model is applied to describe the vessel profile. The normal profiles along the vessel track are fitted to the proposed Gaussian model. The relationship between the vessel diameter and the obtained model parameter is studied for arteries and veins separately. Thirty-five retinal images were tested by the proposed algorithms. The mean difference of vessel measurement between our automatic algorithm and human grader is 7.5 μm (1.4 pixels on the image).

Original language	English
Title of host publication	Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Pages	1751-1754
Number of pages	4
DOIs	https://doi.org/10.1109/ICIEA.2012.6361009
Publication status	Published - 2012
Event	2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 - Singapore, Singapore Duration: 18 Jul 2012 → 20 Jul 2012

Publication series

Name	Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Conference

Conference	2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Country/Territory	Singapore
City	Singapore
Period	18/07/12 → 20/07/12

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

retinal image
vessel detection
vessel measurement

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10.1109/ICIEA.2012.6361009

Cite this

@inproceedings{23b0447a0268498aa663962a61849c3e,

title = "Retinal vessel measurement using model fitting approach",

abstract = "Retinal vessels provide essential information for diagnosing retinal diseases and other diseases. Vessel detection and measurement in color retinal images are investigated in this paper. The source of blood vessels is identified by the matched Gaussian filter. A vessel is tracked from its source by the combined Gaussian and Kalman filters. A modified Gaussian model is applied to describe the vessel profile. The normal profiles along the vessel track are fitted to the proposed Gaussian model. The relationship between the vessel diameter and the obtained model parameter is studied for arteries and veins separately. Thirty-five retinal images were tested by the proposed algorithms. The mean difference of vessel measurement between our automatic algorithm and human grader is 7.5 μm (1.4 pixels on the image).",

keywords = "retinal image, vessel detection, vessel measurement",

author = "Huiqi Li",

year = "2012",

doi = "10.1109/ICIEA.2012.6361009",

language = "English",

isbn = "9781457721175",

series = "Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012",

pages = "1751--1754",

booktitle = "Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012",

note = "2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 ; Conference date: 18-07-2012 Through 20-07-2012",

}

Li, H 2012, Retinal vessel measurement using model fitting approach. in Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012., 6361009, Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012, pp. 1751-1754, 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012, Singapore, Singapore, 18/07/12. https://doi.org/10.1109/ICIEA.2012.6361009

Retinal vessel measurement using model fitting approach. / Li, Huiqi.
Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012. 2012. p. 1751-1754 6361009 (Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012).

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

TY - GEN

T1 - Retinal vessel measurement using model fitting approach

AU - Li, Huiqi

PY - 2012

Y1 - 2012

N2 - Retinal vessels provide essential information for diagnosing retinal diseases and other diseases. Vessel detection and measurement in color retinal images are investigated in this paper. The source of blood vessels is identified by the matched Gaussian filter. A vessel is tracked from its source by the combined Gaussian and Kalman filters. A modified Gaussian model is applied to describe the vessel profile. The normal profiles along the vessel track are fitted to the proposed Gaussian model. The relationship between the vessel diameter and the obtained model parameter is studied for arteries and veins separately. Thirty-five retinal images were tested by the proposed algorithms. The mean difference of vessel measurement between our automatic algorithm and human grader is 7.5 μm (1.4 pixels on the image).

AB - Retinal vessels provide essential information for diagnosing retinal diseases and other diseases. Vessel detection and measurement in color retinal images are investigated in this paper. The source of blood vessels is identified by the matched Gaussian filter. A vessel is tracked from its source by the combined Gaussian and Kalman filters. A modified Gaussian model is applied to describe the vessel profile. The normal profiles along the vessel track are fitted to the proposed Gaussian model. The relationship between the vessel diameter and the obtained model parameter is studied for arteries and veins separately. Thirty-five retinal images were tested by the proposed algorithms. The mean difference of vessel measurement between our automatic algorithm and human grader is 7.5 μm (1.4 pixels on the image).

KW - retinal image

KW - vessel detection

KW - vessel measurement

UR - https://www.scopus.com/pages/publications/84871699502

U2 - 10.1109/ICIEA.2012.6361009

DO - 10.1109/ICIEA.2012.6361009

M3 - Conference contribution

AN - SCOPUS:84871699502

SN - 9781457721175

T3 - Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

SP - 1751

EP - 1754

BT - Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

T2 - 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Y2 - 18 July 2012 through 20 July 2012

ER -

Retinal vessel measurement using model fitting approach

Abstract

Publication series

Conference

UN SDGs

Keywords

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