Computer aided diagnosis of nuclear cataract

Huiqi Li; Hwee Lim Joo; Jiang Liu; Damon Wing Kee Wong; T. Y. Wong

doi:10.1109/ICIEA.2008.4582838

Computer aided diagnosis of nuclear cataract

Huiqi Li, Hwee Lim Joo, Jiang Liu, Damon Wing Kee Wong, T. Y. Wong

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

4 Citations (Scopus)

Abstract

An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support Vector Machine (SVM) regression model is further trained to predict the grades of nuclear cataract automatically. The proposed approach was tested using 900 images and the mean grading error is 0.36. The encouraging results show that it is promising to apply the proposed approach to clinical diagnosis.

Original language	English
Title of host publication	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Pages	1841-1844
Number of pages	4
DOIs	https://doi.org/10.1109/ICIEA.2008.4582838
Publication status	Published - 2008
Externally published	Yes
Event	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 - Singapore, Singapore Duration: 3 Jun 2008 → 5 Jun 2008

Publication series

Name	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Conference

Conference	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Country/Territory	Singapore
City	Singapore
Period	3/06/08 → 5/06/08

ASJC Scopus subject areas

Electrical and Electronic Engineering
Industrial and Manufacturing Engineering

Access to Document

10.1109/ICIEA.2008.4582838

Cite this

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title = "Computer aided diagnosis of nuclear cataract",

abstract = "An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support Vector Machine (SVM) regression model is further trained to predict the grades of nuclear cataract automatically. The proposed approach was tested using 900 images and the mean grading error is 0.36. The encouraging results show that it is promising to apply the proposed approach to clinical diagnosis.",

author = "Huiqi Li and Joo, {Hwee Lim} and Jiang Liu and Wong, {Damon Wing Kee} and Wong, {T. Y.}",

note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 ; Conference date: 03-06-2008 Through 05-06-2008",

year = "2008",

doi = "10.1109/ICIEA.2008.4582838",

language = "English",

isbn = "9781424417186",

series = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008",

pages = "1841--1844",

booktitle = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008",

}

Li, H, Joo, HL, Liu, J, Wong, DWK & Wong, TY 2008, Computer aided diagnosis of nuclear cataract. in 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008., 4582838, 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, pp. 1841-1844, 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, Singapore, Singapore, 3/06/08. https://doi.org/10.1109/ICIEA.2008.4582838

Computer aided diagnosis of nuclear cataract. / Li, Huiqi; Joo, Hwee Lim; Liu, Jiang et al.
2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008. 2008. p. 1841-1844 4582838 (2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008).

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

TY - GEN

T1 - Computer aided diagnosis of nuclear cataract

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AU - Joo, Hwee Lim

AU - Liu, Jiang

AU - Wong, Damon Wing Kee

AU - Wong, T. Y.

PY - 2008

Y1 - 2008

N2 - An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support Vector Machine (SVM) regression model is further trained to predict the grades of nuclear cataract automatically. The proposed approach was tested using 900 images and the mean grading error is 0.36. The encouraging results show that it is promising to apply the proposed approach to clinical diagnosis.

AB - An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support Vector Machine (SVM) regression model is further trained to predict the grades of nuclear cataract automatically. The proposed approach was tested using 900 images and the mean grading error is 0.36. The encouraging results show that it is promising to apply the proposed approach to clinical diagnosis.

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U2 - 10.1109/ICIEA.2008.4582838

DO - 10.1109/ICIEA.2008.4582838

M3 - Conference contribution

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SN - 9781424417186

T3 - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

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BT - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

T2 - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Y2 - 3 June 2008 through 5 June 2008

ER -

Computer aided diagnosis of nuclear cataract

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ASJC Scopus subject areas

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