Focal biologically inspired feature for glaucoma type classification

Jun Cheng; Dacheng Tao; Jiang Liu; Damon Wing Kee Wong; Beng Hai Lee; Mani Baskaran; Tien Yin Wong; Tin Aung

doi:10.1007/978-3-642-23626-6_12

Focal biologically inspired feature for glaucoma type classification

Jun Cheng^*
, Dacheng Tao
, Jiang Liu
, Damon Wing Kee Wong
, Beng Hai Lee
, Mani Baskaran
, Tien Yin Wong
, Tin Aung

^*Corresponding author for this work

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

17 Citations (Scopus)

Abstract

Glaucoma is an optic nerve disease resulting in 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. Ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type. However, manual classification/grading of the iridocorneal angle images is subjective and time consuming. To save workload and facilitate large-scale clinical use, it is essential to determine glaucoma type automatically. In this paper, we propose to use focal biologically inspired feature for the classification. The iris surface is located to determine the focal region. The association between focal biologically inspired feature and angle grades is built. The experimental results show that the proposed method can correctly classify 85.2% images from open angle glaucoma and 84.3% images from angle closure glaucoma. The accuracy could be improved close to 90% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologists and diagnosis cost.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
Pages	91-98
Number of pages	8
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-23626-6_12
Publication status	Published - 2011
Externally published	Yes
Event	14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 - Toronto, ON, Canada Duration: 18 Sept 2011 → 22 Sept 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	6893 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Country/Territory	Canada
City	Toronto, ON
Period	18/09/11 → 22/09/11

UN SDGs

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

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-23626-6_12

Cite this

Cheng, J., Tao, D., Liu, J., Wong, D. W. K., Lee, B. H., Baskaran, M., Wong, T. Y., & Aung, T. (2011). Focal biologically inspired feature for glaucoma type classification. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings (PART 3 ed., pp. 91-98). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6893 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-23626-6_12

Cheng, Jun ; Tao, Dacheng ; Liu, Jiang et al. / Focal biologically inspired feature for glaucoma type classification. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings. PART 3. ed. 2011. pp. 91-98 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

@inproceedings{e12100a64780471da8c246816f60bda0,

title = "Focal biologically inspired feature for glaucoma type classification",

abstract = "Glaucoma is an optic nerve disease resulting in 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. Ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type. However, manual classification/grading of the iridocorneal angle images is subjective and time consuming. To save workload and facilitate large-scale clinical use, it is essential to determine glaucoma type automatically. In this paper, we propose to use focal biologically inspired feature for the classification. The iris surface is located to determine the focal region. The association between focal biologically inspired feature and angle grades is built. The experimental results show that the proposed method can correctly classify 85.2\% images from open angle glaucoma and 84.3\% images from angle closure glaucoma. The accuracy could be improved close to 90\% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologists and diagnosis cost.",

author = "Jun Cheng and Dacheng Tao and Jiang Liu and Wong, \{Damon Wing Kee\} and Lee, \{Beng Hai\} and Mani Baskaran and Wong, \{Tien Yin\} and Tin Aung",

year = "2011",

doi = "10.1007/978-3-642-23626-6\_12",

language = "English",

isbn = "9783642236259",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 3",

pages = "91--98",

booktitle = "Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings",

edition = "PART 3",

note = "14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 ; Conference date: 18-09-2011 Through 22-09-2011",

}

Cheng, J, Tao, D, Liu, J, Wong, DWK, Lee, BH, Baskaran, M, Wong, TY & Aung, T 2011, Focal biologically inspired feature for glaucoma type classification. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 6893 LNCS, pp. 91-98, 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011, Toronto, ON, Canada, 18/09/11. https://doi.org/10.1007/978-3-642-23626-6_12

Focal biologically inspired feature for glaucoma type classification. / Cheng, Jun; Tao, Dacheng; Liu, Jiang et al.
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings. PART 3. ed. 2011. p. 91-98 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6893 LNCS, No. PART 3).

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

TY - GEN

T1 - Focal biologically inspired feature for glaucoma type classification

AU - Cheng, Jun

AU - Tao, Dacheng

AU - Liu, Jiang

AU - Wong, Damon Wing Kee

AU - Lee, Beng Hai

AU - Baskaran, Mani

AU - Wong, Tien Yin

AU - Aung, Tin

PY - 2011

Y1 - 2011

N2 - Glaucoma is an optic nerve disease resulting in 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. Ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type. However, manual classification/grading of the iridocorneal angle images is subjective and time consuming. To save workload and facilitate large-scale clinical use, it is essential to determine glaucoma type automatically. In this paper, we propose to use focal biologically inspired feature for the classification. The iris surface is located to determine the focal region. The association between focal biologically inspired feature and angle grades is built. The experimental results show that the proposed method can correctly classify 85.2% images from open angle glaucoma and 84.3% images from angle closure glaucoma. The accuracy could be improved close to 90% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologists and diagnosis cost.

AB - Glaucoma is an optic nerve disease resulting in 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. Ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type. However, manual classification/grading of the iridocorneal angle images is subjective and time consuming. To save workload and facilitate large-scale clinical use, it is essential to determine glaucoma type automatically. In this paper, we propose to use focal biologically inspired feature for the classification. The iris surface is located to determine the focal region. The association between focal biologically inspired feature and angle grades is built. The experimental results show that the proposed method can correctly classify 85.2% images from open angle glaucoma and 84.3% images from angle closure glaucoma. The accuracy could be improved close to 90% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologists and diagnosis cost.

UR - https://www.scopus.com/pages/publications/80053496197

U2 - 10.1007/978-3-642-23626-6_12

DO - 10.1007/978-3-642-23626-6_12

M3 - Conference contribution

C2 - 22003688

AN - SCOPUS:80053496197

SN - 9783642236259

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 91

EP - 98

BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings

T2 - 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011

Y2 - 18 September 2011 through 22 September 2011

ER -

Cheng J, Tao D, Liu J, Wong DWK, Lee BH, Baskaran M et al. Focal biologically inspired feature for glaucoma type classification. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings. PART 3 ed. 2011. p. 91-98. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-23626-6_12

Focal biologically inspired feature for glaucoma type classification

Abstract

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ASJC Scopus subject areas

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