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
Link To Document :
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