Automatic optic cup segmentation using Kåsa's circle fitting technique

J. R.Harish Kumar, S. Harsha, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We present a technique for optic cup segmentation and outlining based on Kåsa's circle fit model. The outlining problem is posed as a task of fitting a circle to the sparse set of optic cup boundary points. For automatic localization of the optic disc, we use the matched filtering technique. We clear-off the non-optic disc area by drawing a circle with point of optic disc localization as the coordinates of the center and diameter just above the normal optic disc diameter to overcome the problem of optic cup overestimation due to any retinal pathology. We report validation results on three publicly available fundus image databases, amounting to a total of 1411 fundus images for automatic optic disc localization, and 300 fundus images randomly selected for optic cup segmentation and outlining. The proposed method results in an optic disc localization accuracy of 94.06%, 94.17%, and 95.45%, and an average Dice similarity index of 0.7302, 0.7050, and 0.7120 on DRISHTI-GS, MESSIDOR, and DRIONS-DB fundus image databases, respectively. The average computation times for optic disc localization and optic cup segmentation are 3.83 and 5.33 seconds, respectively.

Original languageEnglish
Title of host publicationTENCON 2017 - 2017 IEEE Region 10 Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages25-30
Number of pages6
Volume2017-December
ISBN (Electronic)9781509011339
DOIs
Publication statusPublished - 19-12-2017
Event2017 IEEE Region 10 Conference, TENCON 2017 - Penang, Malaysia
Duration: 05-11-201708-11-2017

Conference

Conference2017 IEEE Region 10 Conference, TENCON 2017
CountryMalaysia
CityPenang
Period05-11-1708-11-17

Fingerprint

Optics
Pathology

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Kumar, J. R. H., Harsha, S., Kamath, Y., Jampala, R., & Seelamantula, C. S. (2017). Automatic optic cup segmentation using Kåsa's circle fitting technique. In TENCON 2017 - 2017 IEEE Region 10 Conference (Vol. 2017-December, pp. 25-30). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2017.8227830
Kumar, J. R.Harish ; Harsha, S. ; Kamath, Yogish ; Jampala, Rajani ; Seelamantula, Chandra Sekhar. / Automatic optic cup segmentation using Kåsa's circle fitting technique. TENCON 2017 - 2017 IEEE Region 10 Conference. Vol. 2017-December Institute of Electrical and Electronics Engineers Inc., 2017. pp. 25-30
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abstract = "We present a technique for optic cup segmentation and outlining based on K{\aa}sa's circle fit model. The outlining problem is posed as a task of fitting a circle to the sparse set of optic cup boundary points. For automatic localization of the optic disc, we use the matched filtering technique. We clear-off the non-optic disc area by drawing a circle with point of optic disc localization as the coordinates of the center and diameter just above the normal optic disc diameter to overcome the problem of optic cup overestimation due to any retinal pathology. We report validation results on three publicly available fundus image databases, amounting to a total of 1411 fundus images for automatic optic disc localization, and 300 fundus images randomly selected for optic cup segmentation and outlining. The proposed method results in an optic disc localization accuracy of 94.06{\%}, 94.17{\%}, and 95.45{\%}, and an average Dice similarity index of 0.7302, 0.7050, and 0.7120 on DRISHTI-GS, MESSIDOR, and DRIONS-DB fundus image databases, respectively. The average computation times for optic disc localization and optic cup segmentation are 3.83 and 5.33 seconds, respectively.",
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Kumar, JRH, Harsha, S, Kamath, Y, Jampala, R & Seelamantula, CS 2017, Automatic optic cup segmentation using Kåsa's circle fitting technique. in TENCON 2017 - 2017 IEEE Region 10 Conference. vol. 2017-December, Institute of Electrical and Electronics Engineers Inc., pp. 25-30, 2017 IEEE Region 10 Conference, TENCON 2017, Penang, Malaysia, 05-11-17. https://doi.org/10.1109/TENCON.2017.8227830

Automatic optic cup segmentation using Kåsa's circle fitting technique. / Kumar, J. R.Harish; Harsha, S.; Kamath, Yogish; Jampala, Rajani; Seelamantula, Chandra Sekhar.

TENCON 2017 - 2017 IEEE Region 10 Conference. Vol. 2017-December Institute of Electrical and Electronics Engineers Inc., 2017. p. 25-30.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Seelamantula, Chandra Sekhar

PY - 2017/12/19

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N2 - We present a technique for optic cup segmentation and outlining based on Kåsa's circle fit model. The outlining problem is posed as a task of fitting a circle to the sparse set of optic cup boundary points. For automatic localization of the optic disc, we use the matched filtering technique. We clear-off the non-optic disc area by drawing a circle with point of optic disc localization as the coordinates of the center and diameter just above the normal optic disc diameter to overcome the problem of optic cup overestimation due to any retinal pathology. We report validation results on three publicly available fundus image databases, amounting to a total of 1411 fundus images for automatic optic disc localization, and 300 fundus images randomly selected for optic cup segmentation and outlining. The proposed method results in an optic disc localization accuracy of 94.06%, 94.17%, and 95.45%, and an average Dice similarity index of 0.7302, 0.7050, and 0.7120 on DRISHTI-GS, MESSIDOR, and DRIONS-DB fundus image databases, respectively. The average computation times for optic disc localization and optic cup segmentation are 3.83 and 5.33 seconds, respectively.

AB - We present a technique for optic cup segmentation and outlining based on Kåsa's circle fit model. The outlining problem is posed as a task of fitting a circle to the sparse set of optic cup boundary points. For automatic localization of the optic disc, we use the matched filtering technique. We clear-off the non-optic disc area by drawing a circle with point of optic disc localization as the coordinates of the center and diameter just above the normal optic disc diameter to overcome the problem of optic cup overestimation due to any retinal pathology. We report validation results on three publicly available fundus image databases, amounting to a total of 1411 fundus images for automatic optic disc localization, and 300 fundus images randomly selected for optic cup segmentation and outlining. The proposed method results in an optic disc localization accuracy of 94.06%, 94.17%, and 95.45%, and an average Dice similarity index of 0.7302, 0.7050, and 0.7120 on DRISHTI-GS, MESSIDOR, and DRIONS-DB fundus image databases, respectively. The average computation times for optic disc localization and optic cup segmentation are 3.83 and 5.33 seconds, respectively.

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Kumar JRH, Harsha S, Kamath Y, Jampala R, Seelamantula CS. Automatic optic cup segmentation using Kåsa's circle fitting technique. In TENCON 2017 - 2017 IEEE Region 10 Conference. Vol. 2017-December. Institute of Electrical and Electronics Engineers Inc. 2017. p. 25-30 https://doi.org/10.1109/TENCON.2017.8227830