Image based diagnosis of cortical cataract

Huiqi Li; Liling Ko; Joo Hwee Lim; Jiang Liu; Damon Wing Kee Wong; Tien Yin Wong

Image based diagnosis of cortical cataract

Huiqi Li, Liling Ko, Joo Hwee Lim, Jiang Liu, Damon Wing Kee Wong, Tien Yin Wong

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

33 Citations (Scopus)

Abstract

An automatic approach to detect cortical opacities and grade the severity of cortical cataract from retroillumination images is proposed. The spoke-like feature of cortical opacity is employed to separate from other opacity type. The proposed algorithms were tested by images from a community study. The success rate of region of interest (ROI) detection is 98.2% for 611 images. For 466 images tested, the mean error of opacity area detection is 3.15% compared with human grader and 85.6% of exact cortical cataract grading is obtained. The experimental results show that the proposed approach is promising in clinical diagnosis.

Original language	English
Title of host publication	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages	3904-3907
Number of pages	4
Publication status	Published - 2008
Externally published	Yes
Event	30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada Duration: 20 Aug 2008 → 25 Aug 2008

Publication series

Name	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Conference

Conference	30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/Territory	Canada
City	Vancouver, BC
Period	20/08/08 → 25/08/08

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing
Biomedical Engineering
Health Informatics

Cite this

Li, H., Ko, L., Lim, J. H., Liu, J., Wong, D. W. K., & Wong, T. Y. (2008). Image based diagnosis of cortical cataract. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 3904-3907). Article 4650063 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

Li, Huiqi ; Ko, Liling ; Lim, Joo Hwee et al. / Image based diagnosis of cortical cataract. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. pp. 3904-3907 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

@inproceedings{d2a35dc38d4c414298d206cfaab0014a,

title = "Image based diagnosis of cortical cataract",

abstract = "An automatic approach to detect cortical opacities and grade the severity of cortical cataract from retroillumination images is proposed. The spoke-like feature of cortical opacity is employed to separate from other opacity type. The proposed algorithms were tested by images from a community study. The success rate of region of interest (ROI) detection is 98.2% for 611 images. For 466 images tested, the mean error of opacity area detection is 3.15% compared with human grader and 85.6% of exact cortical cataract grading is obtained. The experimental results show that the proposed approach is promising in clinical diagnosis.",

author = "Huiqi Li and Liling Ko and Lim, {Joo Hwee} and Jiang Liu and Wong, {Damon Wing Kee} and Wong, {Tien Yin}",

note = "Copyright: Copyright 2009 Elsevier B.V., All rights reserved.; 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 ; Conference date: 20-08-2008 Through 25-08-2008",

year = "2008",

language = "English",

isbn = "9781424418152",

series = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - {"}Personalized Healthcare through Technology{"}",

pages = "3904--3907",

booktitle = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08",

}

Li, H, Ko, L, Lim, JH, Liu, J, Wong, DWK & Wong, TY 2008, Image based diagnosis of cortical cataract. in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08., 4650063, Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology", pp. 3904-3907, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, Canada, 20/08/08.

Image based diagnosis of cortical cataract. / Li, Huiqi; Ko, Liling; Lim, Joo Hwee et al.
Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 3904-3907 4650063 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

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

TY - GEN

T1 - Image based diagnosis of cortical cataract

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AU - Ko, Liling

AU - Lim, Joo Hwee

AU - Liu, Jiang

AU - Wong, Damon Wing Kee

AU - Wong, Tien Yin

PY - 2008

Y1 - 2008

N2 - An automatic approach to detect cortical opacities and grade the severity of cortical cataract from retroillumination images is proposed. The spoke-like feature of cortical opacity is employed to separate from other opacity type. The proposed algorithms were tested by images from a community study. The success rate of region of interest (ROI) detection is 98.2% for 611 images. For 466 images tested, the mean error of opacity area detection is 3.15% compared with human grader and 85.6% of exact cortical cataract grading is obtained. The experimental results show that the proposed approach is promising in clinical diagnosis.

AB - An automatic approach to detect cortical opacities and grade the severity of cortical cataract from retroillumination images is proposed. The spoke-like feature of cortical opacity is employed to separate from other opacity type. The proposed algorithms were tested by images from a community study. The success rate of region of interest (ROI) detection is 98.2% for 611 images. For 466 images tested, the mean error of opacity area detection is 3.15% compared with human grader and 85.6% of exact cortical cataract grading is obtained. The experimental results show that the proposed approach is promising in clinical diagnosis.

UR - http://www.scopus.com/inward/record.url?scp=61849111254&partnerID=8YFLogxK

M3 - Conference contribution

C2 - 19163566

AN - SCOPUS:61849111254

SN - 9781424418152

T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

SP - 3904

EP - 3907

BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08

T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08

Y2 - 20 August 2008 through 25 August 2008

ER -

Li H, Ko L, Lim JH, Liu J, Wong DWK, Wong TY. Image based diagnosis of cortical cataract. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 3904-3907. 4650063. (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

Image based diagnosis of cortical cataract

Abstract

Publication series

Conference

ASJC Scopus subject areas

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