• DocumentCode
    704694
  • Title

    Extraction of retinal vasculature by using morphology in fundus images

  • Author

    Sengar, Namita ; Dutta, Malay Kishore ; Parthasarthi, M. ; Burget, Radim

  • Author_Institution
    Dept. of Electron. & Commun., Amity Univ. Noida, Noida, India
  • fYear
    2015
  • fDate
    19-20 Feb. 2015
  • Firstpage
    139
  • Lastpage
    142
  • Abstract
    In this paper algorithm is proposed for detection of vessels present in a fundus image of an eye. Blood vessels extraction and removal are used to detect the other artifacts like lesions, the fovea and optic nerve. The proposed algorithm used the combination of different morphological operators which make this method less complex and also computationally efficient. Two different channels of an image green and L respectively are utilized to get the final vessel structure. This method also gives the region of interest for macula which may make macula detection easy. The proposed algorithm is tested on DRIVE data set of fundus image of an eye. The result gives good detection of vessel structure and the proposed method is computationally efficient.
  • Keywords
    biomedical optical imaging; blood vessels; eye; feature extraction; medical image processing; object detection; DRIVE data set; artifacts; blood vessel extraction; blood vessel removal; eye; final vessel structure; fovea; fundus images; image green; lesions; macula detection; morphological operators; optic nerve; region of interest; retinal vasculature extraction; vessel detection; Algorithm design and analysis; Biomedical imaging; Blood vessels; Feature extraction; Noise; Retina; Signal processing algorithms; Blood Vessels; Fundus image processing; morphological operators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-5990-7
  • Type

    conf

  • DOI
    10.1109/SPIN.2015.7095382
  • Filename
    7095382