Focal edge association to glaucoma diagnosis

Jun Cheng; Jiang Liu; Damon Wing Kee Wong; Ngan Meng Tan; Beng Hai Lee; Carol Cheung; Mani Baskaran; Tien Yin Wong; Tin Aung

doi:10.1109/IEMBS.2011.6091111

Focal edge association to glaucoma diagnosis

Jun Cheng
, Jiang Liu
, Damon Wing Kee Wong
, Ngan Meng Tan
, Beng Hai Lee
, Carol Cheung
, Mani Baskaran
, Tien Yin Wong
, Tin Aung

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

12 Citations (Scopus)

Abstract

Glaucoma is an optic nerve disease resulting in the loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Clinically, ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type as well as the degree of closure. However, manual grading of the iridocorneal angle images is subjective and often time consuming. In this paper, we propose focal edge for automated iridocorneal angle grading. The iris surface is located to determine focal region and focal edges. The association between focal edges and angle grades is built through machine learning. A modified grading system with three grades is adopted. The experimental results show that the proposed method can correctly classify 87.3% open angle and 88.4% closed angle. Moreover, it can correctly classify 75.0% grade 1 and 77.4% grade 0 for angle closure cases.

Original language	English
Title of host publication	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages	4481-4484
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2011.6091111
Publication status	Published - 2011
Externally published	Yes
Event	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States Duration: 30 Aug 2011 → 3 Sept 2011

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/Territory	United States
City	Boston, MA
Period	30/08/11 → 3/09/11

UN SDGs

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

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/IEMBS.2011.6091111

Cite this

Cheng, J., Liu, J., Wong, D. W. K., Tan, N. M., Lee, B. H., Cheung, C., Baskaran, M., Wong, T. Y., & Aung, T. (2011). Focal edge association to glaucoma diagnosis. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 4481-4484). Article 6091111 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6091111

@inproceedings{c33647f8801e49f7a54b312eae7be208,

title = "Focal edge association to glaucoma diagnosis",

abstract = "Glaucoma is an optic nerve disease resulting in the loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Clinically, ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type as well as the degree of closure. However, manual grading of the iridocorneal angle images is subjective and often time consuming. In this paper, we propose focal edge for automated iridocorneal angle grading. The iris surface is located to determine focal region and focal edges. The association between focal edges and angle grades is built through machine learning. A modified grading system with three grades is adopted. The experimental results show that the proposed method can correctly classify 87.3\% open angle and 88.4\% closed angle. Moreover, it can correctly classify 75.0\% grade 1 and 77.4\% grade 0 for angle closure cases.",

author = "Jun Cheng and Jiang Liu and Wong, \{Damon Wing Kee\} and Tan, \{Ngan Meng\} and Lee, \{Beng Hai\} and Carol Cheung and Mani Baskaran and Wong, \{Tien Yin\} and Tin Aung",

year = "2011",

doi = "10.1109/IEMBS.2011.6091111",

language = "English",

isbn = "9781424441211",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

pages = "4481--4484",

booktitle = "33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011",

note = "33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 ; Conference date: 30-08-2011 Through 03-09-2011",

}

Cheng, J, Liu, J, Wong, DWK, Tan, NM, Lee, BH, Cheung, C, Baskaran, M, Wong, TY & Aung, T 2011, Focal edge association to glaucoma diagnosis. in 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011., 6091111, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 4481-4484, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA, United States, 30/08/11. https://doi.org/10.1109/IEMBS.2011.6091111

Focal edge association to glaucoma diagnosis. / Cheng, Jun; Liu, Jiang; Wong, Damon Wing Kee et al.
33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 4481-4484 6091111 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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

TY - GEN

T1 - Focal edge association to glaucoma diagnosis

AU - Cheng, Jun

AU - Liu, Jiang

AU - Wong, Damon Wing Kee

AU - Tan, Ngan Meng

AU - Lee, Beng Hai

AU - Cheung, Carol

AU - Baskaran, Mani

AU - Wong, Tien Yin

AU - Aung, Tin

PY - 2011

Y1 - 2011

N2 - Glaucoma is an optic nerve disease resulting in the loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Clinically, ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type as well as the degree of closure. However, manual grading of the iridocorneal angle images is subjective and often time consuming. In this paper, we propose focal edge for automated iridocorneal angle grading. The iris surface is located to determine focal region and focal edges. The association between focal edges and angle grades is built through machine learning. A modified grading system with three grades is adopted. The experimental results show that the proposed method can correctly classify 87.3% open angle and 88.4% closed angle. Moreover, it can correctly classify 75.0% grade 1 and 77.4% grade 0 for angle closure cases.

AB - Glaucoma is an optic nerve disease resulting in the loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Clinically, ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type as well as the degree of closure. However, manual grading of the iridocorneal angle images is subjective and often time consuming. In this paper, we propose focal edge for automated iridocorneal angle grading. The iris surface is located to determine focal region and focal edges. The association between focal edges and angle grades is built through machine learning. A modified grading system with three grades is adopted. The experimental results show that the proposed method can correctly classify 87.3% open angle and 88.4% closed angle. Moreover, it can correctly classify 75.0% grade 1 and 77.4% grade 0 for angle closure cases.

UR - https://www.scopus.com/pages/publications/84055217309

U2 - 10.1109/IEMBS.2011.6091111

DO - 10.1109/IEMBS.2011.6091111

M3 - Conference contribution

C2 - 22255334

AN - SCOPUS:84055217309

SN - 9781424441211

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 4481

EP - 4484

BT - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011

T2 - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011

Y2 - 30 August 2011 through 3 September 2011

ER -

Cheng J, Liu J, Wong DWK, Tan NM, Lee BH, Cheung C et al. Focal edge association to glaucoma diagnosis. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 4481-4484. 6091111. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/IEMBS.2011.6091111

Focal edge association to glaucoma diagnosis

Abstract

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Conference

UN SDGs

ASJC Scopus subject areas

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