Automatic Optic Disc Boundary Extraction from Color Fundus Images

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Automatic Optic Disc Boundary Extraction from Color Fundus Images

Show simple item record Tessamma, Thomas Thresiamma, Devasia Poulose Jacob,K 2014-08-12T09:46:36Z 2014-08-12T09:46:36Z 2014
dc.description (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 5, No. 7, 2014 en_US
dc.description.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. Moreover 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 en_US
dc.description.sponsorship Cochin University of Science and Technology en_US
dc.language.iso en en_US
dc.subject fundus image en_US
dc.subject optic nerve head en_US
dc.subject optic disc en_US
dc.subject Fuzzy C-Means clustering en_US
dc.title Automatic Optic Disc Boundary Extraction from Color Fundus Images en_US
dc.type Article en_US

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