Publication detail

An Efficient Imaging Technique for Automated Macula Localization from Fundus Images

ISSAC, A. SENGAR, N. SINGH, A. DUTTA, M. PŘINOSIL, J. ŘÍHA, K.

Original Title

An Efficient Imaging Technique for Automated Macula Localization from Fundus Images

Type

conference paper

Language

English

Original Abstract

Localization of macula from fundus image plays an important role to design an automated screening tool for detection of retinal diseases. The similar color and texture of red lesions act as a bottleneck in accurate localization of macula in the fundus image. This paper presents a computer vision algorithm for automated and efficient localization of macula from low contrast and diabetic retinopathy affected fundus images. A statistical based model is used to detect macula in a specified region of fundus image which is designed using the geometric features of optic disc. The performance of the proposed algorithm of macula detection was tested on 200 normal/affected fundus images and results are significant. The computational efficiency and accurate localization of macula makes the proposed method competent enough to be used as a part of an automated screening tool for detection of retinal diseases.

Keywords

Fundus Image; Macula; Optic Disc; Retinal Diseases; Statistical features

Authors

ISSAC, A.; SENGAR, N.; SINGH, A.; DUTTA, M.; PŘINOSIL, J.; ŘÍHA, K.

Released

18. 10. 2016

ISBN

978-1-4673-8817-7

Book

8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops - ICUMT

Pages from

387

Pages to

391

Pages count

5

URL

https://ieeexplore.ieee.org/document/7765390

BibTex

@inproceedings{BUT129290,
  author="Ashish {Issac} and Namita {Sengar} and Anushikha {Singh} and Malay Kishore {Dutta} and Jiří {Přinosil} and Kamil {Říha}",
  title="An Efficient Imaging Technique for Automated Macula Localization from Fundus Images",
  booktitle="8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops - ICUMT",
  year="2016",
  pages="387--391",
  doi="10.1109/ICUMT.2016.7765390",
  isbn="978-1-4673-8817-7",
  url="https://ieeexplore.ieee.org/document/7765390"
}