Literature DB >> 21950923

Automated determination of cup-to-disc ratio for classification of glaucomatous and normal eyes on stereo retinal fundus images.

Chisako Muramatsu1, Toshiaki Nakagawa, Akira Sawada, Yuji Hatanaka, Tetsuya Yamamoto, Hiroshi Fujita.   

Abstract

Early diagnosis of glaucoma, which is the second leading cause of blindness in the world, can halt or slow the progression of the disease. We propose an automated method for analyzing the optic disc and measuring the cup-to-disc ratio (CDR) on stereo retinal fundus images to improve ophthalmologists' diagnostic efficiency and potentially reduce the variation on the CDR measurement. The method was developed using 80 retinal fundus image pairs, including 25 glaucomatous, and 55 nonglaucomatous eyes, obtained at our institution. A disc region was segmented using the active contour method with the brightness and edge information. The segmentation of a cup region was performed using a depth map of the optic disc, which was reconstructed on the basis of the stereo disparity. The CDRs were measured and compared with those determined using the manual segmentation results by an expert ophthalmologist. The method was applied to a new database which consisted of 98 stereo image pairs including 60 and 30 pairs with and without signs of glaucoma, respectively. Using the CDRs, an area under the receiver operating characteristic curve of 0.90 was obtained for classification of the glaucomatous and nonglaucomatous eyes. The result indicates potential usefulness of the automated determination of CDRs for the diagnosis of glaucoma.

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Year:  2011        PMID: 21950923     DOI: 10.1117/1.3622755

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  4 in total

1.  Validating retinal fundus image analysis algorithms: issues and a proposal.

Authors:  Emanuele Trucco; Alfredo Ruggeri; Thomas Karnowski; Luca Giancardo; Edward Chaum; Jean Pierre Hubschman; Bashir Al-Diri; Carol Y Cheung; Damon Wong; Michael Abràmoff; Gilbert Lim; Dinesh Kumar; Philippe Burlina; Neil M Bressler; Herbert F Jelinek; Fabrice Meriaudeau; Gwénolé Quellec; Tom Macgillivray; Bal Dhillon
Journal:  Invest Ophthalmol Vis Sci       Date:  2013-05-01       Impact factor: 4.799

Review 2.  Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey.

Authors:  Ahmed Almazroa; Ritambhar Burman; Kaamran Raahemifar; Vasudevan Lakshminarayanan
Journal:  J Ophthalmol       Date:  2015-11-25       Impact factor: 1.909

3.  Artificial intelligence integrated smartphone fundus camera for screening the glaucomatous optic disc.

Authors:  Toshit Varshney; Divya R Parthasarathy; Viney Gupta
Journal:  Indian J Ophthalmol       Date:  2021-12       Impact factor: 1.848

4.  Software-Assisted Depth Analysis of Optic Nerve Stereoscopic Images in Telemedicine.

Authors:  Tian Xia; Shriji N Patel; Ben C Szirth; Anton M Kolomeyer; Albert S Khouri
Journal:  Int J Telemed Appl       Date:  2016-04-14
  4 in total

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