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Automatic Separation of Retinal Vessels into Arteries and Veins Using Ensemble Learning

In: Integral Methods in Science and Engineering

Author

Listed:
  • N. Ramezani

    (Islamic Azad University)

  • H. Pourreza

    (Islamic Azad University)

  • O. Khoshdel Borj

    (Islamic Azad University)

Abstract

Separating the retinal vessels into arteries and veins is vital for recognizing the stage of the disease in the diabetics. Precise separation of retinal vessels is highly effective in eyesight improvement of the diabetics. For an appropriate classification of retinal vessels, a proper pre-process, efficient segmentation, extracting distinctive features and using high care classifiers will be essential. The method presented for vessels segmentation in this paper is based on Ensemble Learning whose main goal is to use a number of efficient and complementary classifiers for classifying the characteristics of vessels segments. The results of proposed method are compared with manual labeled Images from VICAVR database. The rate of accuracy of the proposed method equals 95.5% which is the highest value as compared with other methods.

Suggested Citation

  • N. Ramezani & H. Pourreza & O. Khoshdel Borj, 2015. "Automatic Separation of Retinal Vessels into Arteries and Veins Using Ensemble Learning," Springer Books, in: Christian Constanda & Andreas Kirsch (ed.), Integral Methods in Science and Engineering, edition 1, chapter 0, pages 527-538, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-16727-5_44
    DOI: 10.1007/978-3-319-16727-5_44
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