Publication result detail

Image Processing Based Automatic Diagnosis of Glaucoma using Wavelet Features of Segmented Optic Disc from Fundus Image

SINGH, A.; DUTTA, M.; PARTHASARATHI, M.; UHER, V.; BURGET, R.

Original Title

Image Processing Based Automatic Diagnosis of Glaucoma using Wavelet Features of Segmented Optic Disc from Fundus Image

English Title

Image Processing Based Automatic Diagnosis of Glaucoma using Wavelet Features of Segmented Optic Disc from Fundus Image

Type

WoS Article

Original Abstract

Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7 % and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification

English abstract

Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7 % and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification

Keywords

Glaucoma; Fundus image; Optic Disc; Blood Vessels; Wavelet Transform; Feature Extraction; Classification

Key words in English

Glaucoma; Fundus image; Optic Disc; Blood Vessels; Wavelet Transform; Feature Extraction; Classification

Authors

SINGH, A.; DUTTA, M.; PARTHASARATHI, M.; UHER, V.; BURGET, R.

RIV year

2016

Released

23.10.2015

Publisher

Elsevier Ireland Ltd

Location

Irsko

ISBN

0169-2607

Periodical

Computer Methods and Programs in Biomedicine

Volume

122

Number

2

State

Kingdom of the Netherlands

Pages from

1

Pages to

12

Pages count

12

URL

http://www.sciencedirect.com/science/article/pii/S0169260715002709

BibTex

@article{BUT118014,
  author="SINGH, A. and DUTTA, M. and PARTHASARATHI, M. and UHER, V. and BURGET, R.",
  title="Image Processing Based Automatic Diagnosis of Glaucoma using Wavelet Features of Segmented Optic Disc from Fundus Image",
  journal="Computer Methods and Programs in Biomedicine",
  year="2015",
  volume="122",
  number="2",
  pages="1--12",
  doi="10.1016/j.cmpb.2015.10.010",
  issn="0169-2607",
  url="http://www.sciencedirect.com/science/article/pii/S0169260715002709"
}