• DocumentCode
    740825
  • Title

    Vessel transform for automatic optic disk detection in retinal images

  • Author

    Muangnak, Nittaya ; Aimmanee, Pakinee ; Makhanov, Stanislav ; Uyyanonvara, Bunyarit

  • Author_Institution
    Sirindhorn Int. Inst. of Technol., Thammasat Univ., Pathumthani, Thailand
  • Volume
    9
  • Issue
    9
  • fYear
    2015
  • Firstpage
    743
  • Lastpage
    750
  • Abstract
    Precise localisation of an optic disk (OD) in the retinal images is one of the most important problems in the ophthalmic image processing. Although a considerable progress has been made towards a computerised solution of the problem, the numerical algorithms often fail on retinal images characterised by poor quality. Therefore, the authors propose a new method suitable for low-quality images based on exploiting the convergence of the blood vessels to the OD. The novelty of the proposed techniques includes clustering the vessels endowed with a novel correction procedure and the vessel transform (VT) which measures the distance to the main clusters. The algorithm is integrated into the scale-space (SS) analysis to detect the boundary of the OD. The integrated method is called SS algorithm with VT (SSVT). SSVT has been tested on retinal images from two databases with fair and poor images against the fuzzy convergence (FC) method and a modification of the circular transform proposed by Lu. The absolute improvement on sensitivity of SSVT against FC and Lu´s are up to 12.37% and 8.18%. Bigger improvements of SSVT in terms of positive predictive value are up to 37.46% and 30.84% against FC and Lu´s, respectively.
  • Keywords
    biomedical optical imaging; blood vessels; convergence of numerical methods; eye; fuzzy set theory; medical image processing; transforms; FC method; SS algorithm; SSVT sensitivity; automatic optic disk detection; blood vessels; circular transform; computerised solution; fuzzy convergence method; integrated method; low-quality images; numerical algorithms; ophthalmic image processing; retinal images; scale-space analysis; vessel clustering; vessel transform;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9659
  • Type

    jour

  • DOI
    10.1049/iet-ipr.2015.0030
  • Filename
    7224099