Literature DB >> 35018540

Detection of Optic Disc Localization from Retinal Fundus Image Using Optimized Color Space.

Buket Toptaş1, Murat Toptaş2, Davut Hanbay3.   

Abstract

Optic disc localization offers an important clue in detecting other retinal components such as the macula, fovea, and retinal vessels. With the correct detection of this area, sudden vision loss caused by diseases such as age-related macular degeneration and diabetic retinopathy can be prevented. Therefore, there is an increase in computer-aided diagnosis systems in this field. In this paper, an automated method for detecting optic disc localization is proposed. In the proposed method, the fundus images are moved from RGB color space to a new color space by using an artificial bee colony algorithm. In the new color space, the localization of the optical disc is clearer than in the RGB color space. In this method, a matrix called the feature matrix is created. This matrix is obtained from the color pixel values of the image patches containing the optical disc and the image patches not containing the optical disc. Then, the conversion matrix is created. The initial values of this matrix are randomly determined. These two matrices are processed in the artificial bee colony algorithm. Ultimately, the conversion matrix becomes optimal and is applied over the original fundus images. Thus, the images are moved to the new color space. Thresholding is applied to these images, and the optic disc localization is obtained. The success rate of the proposed method has been tested on three general datasets. The accuracy success rate for the DRIVE, DRIONS, and MESSIDOR datasets, respectively, is 100%, 96.37%, and 94.42% for the proposed method.
© 2021. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.

Entities:  

Keywords:  Artificial bee colony; Eigenvalue; Fundus image; Optic disc localization

Mesh:

Year:  2022        PMID: 35018540      PMCID: PMC8921449          DOI: 10.1007/s10278-021-00566-8

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  19 in total

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Journal:  J Diabetes Complications       Date:  2016-03-21       Impact factor: 2.852

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7.  Optic disk edema with cotton-wool spots.

Authors:  M Wall
Journal:  Surv Ophthalmol       Date:  1995 May-Jun       Impact factor: 6.048

8.  Using a multi-agent system approach for microaneurysm detection in fundus images.

Authors:  Carla Pereira; Diana Veiga; Jason Mahdjoub; Zahia Guessoum; Luís Gonçalves; Manuel Ferreira; João Monteiro
Journal:  Artif Intell Med       Date:  2013-12-28       Impact factor: 5.326

Review 9.  Computer-aided diagnosis of glaucoma using fundus images: A review.

Authors:  Yuki Hagiwara; Joel En Wei Koh; Jen Hong Tan; Sulatha V Bhandary; Augustinus Laude; Edward J Ciaccio; Louis Tong; U Rajendra Acharya
Journal:  Comput Methods Programs Biomed       Date:  2018-07-26       Impact factor: 5.428

10.  Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior.

Authors:  Wei Zhou; Yugen Yi; Yuan Gao; Jiangyan Dai
Journal:  Comput Math Methods Med       Date:  2019-11-20       Impact factor: 2.238

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Journal:  Front Neurol       Date:  2022-07-27       Impact factor: 4.086

  1 in total

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