• DocumentCode
    133893
  • Title

    A method for identifying distribution pattern of cone cells in retina image

  • Author

    Morooka, Ken´ichi ; Yuanting Ji ; Martinez Mozos, Oscar ; Tsuji, Tokuo ; Kurazume, Ryo ; Ahnelt, Peter K.

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan
  • fYear
    2014
  • fDate
    3-7 Aug. 2014
  • Firstpage
    774
  • Lastpage
    778
  • Abstract
    This paper proposes a method to identify the spatial distribution patterns of cone cells related with blood vessel in a given retina image. We define three types of the distribution patterns between cones and vessels. Positive correlation distribution (PCD) and negative correlation distribution (NCD) indicate that the cones tend to be close to or far from the vessels. While the cone cells do not have significant correlation with vessels, the cone distribution is regarded as the random distribution (RD). In our method, RD is modeled by many virtual retina images, each of which is generated by the vessels extracted from the original retina image and the virtual cells are selected randomly from the image. Using the virtual images, we estimate the distribution range of RD. When the distribution of the original cells is above the upper limit or below the lower limit of the RD distribution, the cell distribution is NCD or PCD. Otherwise, the cell distribution is regarded as RD.
  • Keywords
    biology computing; eye; feature extraction; image recognition; NCD; PCD; RD; cone cells distribution pattern; negative correlation distribution; positive correlation distribution; random distribution; retina image; spatial distribution pattern identification; vessel extraction; Biology; Correlation; Image resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    World Automation Congress (WAC), 2014
  • Conference_Location
    Waikoloa, HI
  • Type

    conf

  • DOI
    10.1109/WAC.2014.6936144
  • Filename
    6936144