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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 7, 2014.
Abstract: Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. More over it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases.
Thresiamma Devasia, Paulose Jacob and Tessamma Thomas, “Automatic Optic Disc Boundary Extraction from Color Fundus Images” International Journal of Advanced Computer Science and Applications(IJACSA), 5(7), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050718
@article{Devasia2014,
title = {Automatic Optic Disc Boundary Extraction from Color Fundus Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050718},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050718},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {7},
author = {Thresiamma Devasia and Paulose Jacob and Tessamma Thomas}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.