Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis

Fengshou Yin; Jiang Liu; Damon Wing Kee Wong; Ngan Meng Tan; Carol Cheung; Mani Baskaran; Tin Aung; Tien Yin Wong

doi:10.1109/CBMS.2012.6266344

Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis

Fengshou Yin^*
, Jiang Liu
, Damon Wing Kee Wong
, Ngan Meng Tan
, Carol Cheung
, Mani Baskaran
, Tin Aung
, Tien Yin Wong

^*Corresponding author for this work

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

117 Citations (Scopus)

Abstract

The vertical Cup-to-Disc Ratio (CDR) is an important indicator in the diagnosis of glaucoma. Automatic segmentation of the optic disc (OD) and optic cup is crucial towards a good computer-aided diagnosis (CAD) system. This paper presents a statistical model-based method for the segmentation of the optic disc and optic cup from digital color fundus images. The method combines knowledge-based Circular Hough Transform and a novel optimal channel selection for segmentation of the OD. Moreover, we extended the method to optic cup segmentation, which is a more challenging task. The system was tested on a dataset of 325 images. The average Dice coefficient for the disc and cup segmentation is 0.92 and 0.81 respectively, which improves significantly over existing methods. The proposed method has a mean absolute CDR error of 0.10, which outperforms existing methods. The results are promising and thus demonstrate a good potential for this method to be used in a mass screening CAD system.

Original language	English
Title of host publication	Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012
DOIs	https://doi.org/10.1109/CBMS.2012.6266344
Publication status	Published - 2012
Externally published	Yes
Event	25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012 - Rome, Italy Duration: 20 Jun 2012 → 22 Jun 2012

Publication series

Name	Proceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)	1063-7125

Conference

Conference	25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012
Country/Territory	Italy
City	Rome
Period	20/06/12 → 22/06/12

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging
Computer Science Applications

Access to Document

10.1109/CBMS.2012.6266344

Cite this

Yin, F., Liu, J., Wong, D. W. K., Tan, N. M., Cheung, C., Baskaran, M., Aung, T., & Wong, T. Y. (2012). Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis. In Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012 Article 6266344 (Proceedings - IEEE Symposium on Computer-Based Medical Systems). https://doi.org/10.1109/CBMS.2012.6266344

@inproceedings{f82e26137aa64c9ba9aecd2d0804935d,

title = "Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis",

abstract = "The vertical Cup-to-Disc Ratio (CDR) is an important indicator in the diagnosis of glaucoma. Automatic segmentation of the optic disc (OD) and optic cup is crucial towards a good computer-aided diagnosis (CAD) system. This paper presents a statistical model-based method for the segmentation of the optic disc and optic cup from digital color fundus images. The method combines knowledge-based Circular Hough Transform and a novel optimal channel selection for segmentation of the OD. Moreover, we extended the method to optic cup segmentation, which is a more challenging task. The system was tested on a dataset of 325 images. The average Dice coefficient for the disc and cup segmentation is 0.92 and 0.81 respectively, which improves significantly over existing methods. The proposed method has a mean absolute CDR error of 0.10, which outperforms existing methods. The results are promising and thus demonstrate a good potential for this method to be used in a mass screening CAD system.",

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

year = "2012",

doi = "10.1109/CBMS.2012.6266344",

language = "English",

isbn = "9781467320511",

series = "Proceedings - IEEE Symposium on Computer-Based Medical Systems",

booktitle = "Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012",

}

Yin, F, Liu, J, Wong, DWK, Tan, NM, Cheung, C, Baskaran, M, Aung, T & Wong, TY 2012, Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis. in Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012., 6266344, Proceedings - IEEE Symposium on Computer-Based Medical Systems, 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012, Rome, Italy, 20/06/12. https://doi.org/10.1109/CBMS.2012.6266344

Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis. / Yin, Fengshou; Liu, Jiang; Wong, Damon Wing Kee et al.
Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012. 2012. 6266344 (Proceedings - IEEE Symposium on Computer-Based Medical Systems).

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

TY - GEN

T1 - Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis

AU - Yin, Fengshou

AU - Liu, Jiang

AU - Wong, Damon Wing Kee

AU - Tan, Ngan Meng

AU - Cheung, Carol

AU - Baskaran, Mani

AU - Aung, Tin

AU - Wong, Tien Yin

PY - 2012

Y1 - 2012

N2 - The vertical Cup-to-Disc Ratio (CDR) is an important indicator in the diagnosis of glaucoma. Automatic segmentation of the optic disc (OD) and optic cup is crucial towards a good computer-aided diagnosis (CAD) system. This paper presents a statistical model-based method for the segmentation of the optic disc and optic cup from digital color fundus images. The method combines knowledge-based Circular Hough Transform and a novel optimal channel selection for segmentation of the OD. Moreover, we extended the method to optic cup segmentation, which is a more challenging task. The system was tested on a dataset of 325 images. The average Dice coefficient for the disc and cup segmentation is 0.92 and 0.81 respectively, which improves significantly over existing methods. The proposed method has a mean absolute CDR error of 0.10, which outperforms existing methods. The results are promising and thus demonstrate a good potential for this method to be used in a mass screening CAD system.

AB - The vertical Cup-to-Disc Ratio (CDR) is an important indicator in the diagnosis of glaucoma. Automatic segmentation of the optic disc (OD) and optic cup is crucial towards a good computer-aided diagnosis (CAD) system. This paper presents a statistical model-based method for the segmentation of the optic disc and optic cup from digital color fundus images. The method combines knowledge-based Circular Hough Transform and a novel optimal channel selection for segmentation of the OD. Moreover, we extended the method to optic cup segmentation, which is a more challenging task. The system was tested on a dataset of 325 images. The average Dice coefficient for the disc and cup segmentation is 0.92 and 0.81 respectively, which improves significantly over existing methods. The proposed method has a mean absolute CDR error of 0.10, which outperforms existing methods. The results are promising and thus demonstrate a good potential for this method to be used in a mass screening CAD system.

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M3 - Conference contribution

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SN - 9781467320511

T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems

BT - Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012

T2 - 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012

Y2 - 20 June 2012 through 22 June 2012

ER -

Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis

Abstract

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UN SDGs

ASJC Scopus subject areas

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