Literature DB >> 12906249

Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels.

Adam Hoover1, Michael Goldbaum.   

Abstract

We describe an automated method to locate the optic nerve in images of the ocular fundus. Our method uses a novel algorithm we call fuzzy convergence to determine the origination of the blood vessel network. We evaluate our method using 31 images of healthy retinas and 50 images of diseased retinas, containing such diverse symptoms as tortuous vessels, choroidal neovascularization, and hemorrhages that completely obscure the actual nerve. On this difficult data set, our method achieved 89% correct detection. We also compare our method against three simpler methods, demonstrating the performance improvement. All our images and data are freely available for other researchers to use in evaluating related methods.

Entities:  

Mesh:

Year:  2003        PMID: 12906249     DOI: 10.1109/TMI.2003.815900

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  42 in total

1.  An approach to identify optic disc in human retinal images using ant colony optimization method.

Authors:  Ganesan Kavitha; Swaminathan Ramakrishnan
Journal:  J Med Syst       Date:  2009-04-28       Impact factor: 4.460

2.  Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy.

Authors:  Sameh A Salem; Nancy M Salem; Asoke K Nandi
Journal:  Med Biol Eng Comput       Date:  2007-02-15       Impact factor: 2.602

Review 3.  Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease.

Authors:  Hyun-Jin Yang; Rinki Ratnapriya; Tiziana Cogliati; Jung-Woong Kim; Anand Swaroop
Journal:  Prog Retin Eye Res       Date:  2015-02-07       Impact factor: 21.198

4.  The automatic detection of the optic disc location in retinal images using optic disc location regression.

Authors:  Michael D Abràmoff; Meindert Niemeijer
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006

5.  Validation of retinal image registration algorithms by a projective imaging distortion model.

Authors:  Sangyeol Lee; Michael D Abramoff; Joseph M Reinhardt
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2007

6.  Detection of the optic nerve head in fundus images of the retina using the Hough transform for circles.

Authors:  Xiaolu Zhu; Rangaraj M Rangayyan; Anna L Ells
Journal:  J Digit Imaging       Date:  2010-06       Impact factor: 4.056

Review 7.  Optic disc detection in retinal fundus images using gravitational law-based edge detection.

Authors:  Mohammad Alshayeji; Suood Abdulaziz Al-Roomi; Sa'ed Abed
Journal:  Med Biol Eng Comput       Date:  2016-09-16       Impact factor: 2.602

8.  A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding.

Authors:  Jasem Almotiri; Khaled Elleithy; Abdelrahman Elleithy
Journal:  IEEE J Transl Eng Health Med       Date:  2018-05-17       Impact factor: 3.316

Review 9.  Detection of the optic nerve head in fundus images of the retina with Gabor filters and phase portrait analysis.

Authors:  Rangaraj M Rangayyan; Xiaolu Zhu; Fábio J Ayres; Anna L Ells
Journal:  J Digit Imaging       Date:  2010-01-12       Impact factor: 4.056

10.  Automatic detection of microaneurysms and hemorrhages in digital fundus images.

Authors:  Giri Babu Kande; T Satya Savithri; P Venkata Subbaiah
Journal:  J Digit Imaging       Date:  2009-11-17       Impact factor: 4.056

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