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

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

109 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

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging
Computer Science Applications

UN SDGs

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

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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

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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

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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

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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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SN - 9781467320511

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

Abstract

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Conference

ASJC Scopus subject areas

UN SDGs

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