• DocumentCode
    189989
  • Title

    Blood vessel extraction using morphological operation for diabetic retinopathy

  • Author

    Azani B. Wan Mustafa, Wan ; Yazid, Haniza ; Bin Yaacob, Sazali ; Bin Basah, Shafriza Nisha

  • Author_Institution
    Sch. of Mechatron., Univ. Malaysia Perlis, Arau, Malaysia
  • fYear
    2014
  • fDate
    14-16 April 2014
  • Firstpage
    208
  • Lastpage
    212
  • Abstract
    Diabetic retinopathy is an eye problem that faced by the diabetic´s patient. Diabetic Retinopathy (DR) is caused by the changes of the blood vessel in the retina. In first stage in DR, the blood vessels leak fluid and expandable. However, in the advance stage of DR a new blood vessel that fragile and abnormal may formed and leaks blood to the retina. This can caused vision loss or even blindness. Therefore, this paper proposes to extract the blood vessel based on peak and valley detection. The proposed methods utilized a green channel image and the inversion image. In this work, 20 images are utilized namely from Digital Retina Images for Vessel Extraction (DRIVE). The resulting images are compared with the benchmark images in term of sensitivity and specificity. The average sensitivity and specificity for the proposed method is 99.6% and 47.9% respectively.
  • Keywords
    biomedical optical imaging; blood vessels; diseases; eye; feature extraction; medical image processing; vision defects; DRIVE; Digital Retina Images for Vessel Extraction; blindness; blood leaks; blood vessel extraction; diabetic retinopathy; eye problem; green channel image; inversion image; morphological operation; peak detection; retina; sensitivity; specificity; valley detection; vision loss; Biomedical imaging; Blood vessels; Diabetes; Morphology; Retina; Retinopathy; Sensitivity; blood vessel extraction; diabetic retinopathy; peak detection; valley detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Region 10 Symposium, 2014 IEEE
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4799-2028-0
  • Type

    conf

  • DOI
    10.1109/TENCONSpring.2014.6863027
  • Filename
    6863027