Using image processing methods for diagnosis diabetic retinopathy

Ali Shojaeipour, Md. Jan Nordin, Nooshin Hadavi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

According to the increasing consumption of sugar materials in human life and growing trend of the machine life, the prevalence of diabetes is on the rise. It is observed all patients with this disease mostly suffer from decrease or loss their vision. For the automatic diagnosis of diabetic retinopathy (DR) and determination of a diabetic eye from a healthy eye, we need to extract several features from retinopathy images. There are various possible characteristics can be extracted from the retina photography images, hence it is significant to discover the most effective features for detection of diabetic retinopathy. In this study the Gaussian filter is used to enhance images and separate vessels with a high brightness intensity distribution. Next, wavelets transform is used to extract vessels. After that according to some criteria such as vessels density, the location of optic disc was determined. Then after optic disc extraction, exudates regions were determined. Finally we classified the images with a boosting classifier. With utilizing the boosting algorithm, the suggested system can have a power classifier. It is generated by a combination of some weak and simple learners. Hence, this approach can reduce the complication and time consuming operation.

Original languageEnglish
Title of host publication2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages154-159
Number of pages6
ISBN (Print)9781479957651
DOIs
Publication statusPublished - 9 Oct 2015
EventIEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014 - Kuala Lumpur, Malaysia
Duration: 15 Dec 201416 Dec 2014

Other

OtherIEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014
CountryMalaysia
CityKuala Lumpur
Period15/12/1416/12/14

Fingerprint

Optics
Image processing
Classifiers
Photography
Medical problems
Sugars
Wavelet transforms
Luminance

Keywords

  • adaboost algorithm
  • blood vessele detection
  • Computer aided diagnosis
  • diabetic retinopathy
  • exudates
  • image processing
  • optic disc
  • pattern recognition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Cite this

Shojaeipour, A., Nordin, M. J., & Hadavi, N. (2015). Using image processing methods for diagnosis diabetic retinopathy. In 2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014 (pp. 154-159). [7295879] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROMA.2014.7295879

Using image processing methods for diagnosis diabetic retinopathy. / Shojaeipour, Ali; Nordin, Md. Jan; Hadavi, Nooshin.

2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 154-159 7295879.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shojaeipour, A, Nordin, MJ & Hadavi, N 2015, Using image processing methods for diagnosis diabetic retinopathy. in 2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014., 7295879, Institute of Electrical and Electronics Engineers Inc., pp. 154-159, IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014, Kuala Lumpur, Malaysia, 15/12/14. https://doi.org/10.1109/ROMA.2014.7295879
Shojaeipour A, Nordin MJ, Hadavi N. Using image processing methods for diagnosis diabetic retinopathy. In 2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 154-159. 7295879 https://doi.org/10.1109/ROMA.2014.7295879
Shojaeipour, Ali ; Nordin, Md. Jan ; Hadavi, Nooshin. / Using image processing methods for diagnosis diabetic retinopathy. 2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 154-159
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