• DocumentCode
    1951410
  • Title

    A new method of vascular point detection using artificial neural network

  • Author

    Kader, S. ; Aibinu, A.M. ; Salami, M.J.E.

  • Author_Institution
    Mechatron. Eng. Dept., Int. Islamic Univ., Kuala Lumpur, Malaysia
  • fYear
    2012
  • fDate
    17-19 Dec. 2012
  • Firstpage
    728
  • Lastpage
    733
  • Abstract
    Vascular intersection is an important feature in retina fundus image (RFI). It can be used to monitor the progress of diabetes hence accurately determining vascular point is of utmost important. In this work a new method of vascular point detection using artificial neural network model has been proposed. The method uses a 5×5 window in order to detect the combination of bifurcation and crossover points in a retina fundus image. Simulated images have been used to train the artificial neural network and on convergence the network is used to test (RFI) from DRIVE database. Performance analysis of the system shows that ANN based technique achieves 100% accuracy on simulated images and minimum of 92% accuracy on RFI obtained from DRIVE database.
  • Keywords
    biomedical optical imaging; blood vessels; diseases; eye; learning (artificial intelligence); medical image processing; neural nets; DRIVE database; RFI; artificial neural network model; artificial neural network training; diabetes progression; retina fundus image; simulated images; vascular intersection; vascular point detection method; vessel bifurcation point; vessel crossover point; Artificial Neural Network; Diabetic Retinopathy; Retina; Vascular points;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on
  • Conference_Location
    Langkawi
  • Print_ISBN
    978-1-4673-1664-4
  • Type

    conf

  • DOI
    10.1109/IECBES.2012.6498142
  • Filename
    6498142