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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish
Title of host publicationWorld Automation Congress Proceedings
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781889335490
Publication statusPublished - Oct 24 2014
Externally publishedYes
Event2014 World Automation Congress, WAC 2014 - Waikoloa, United States
Duration: Aug 3 2014Aug 7 2014

Publication series

NameWorld Automation Congress Proceedings
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832


Conference2014 World Automation Congress, WAC 2014
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Control and Systems Engineering


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