Please use this identifier to cite or link to this item:
|Title:||Learning-based approach for the automatic detection of the optic disc in digital retinal fundus photographs||Authors:||Wong, D.W.K.
|Issue Date:||2010||Citation:||Wong, D.W.K., Liu, J., Tan, N.M., Yin, F., Lee, B.H., Wong, T.Y. (2010). Learning-based approach for the automatic detection of the optic disc in digital retinal fundus photographs. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 : 5355-5358. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2010.5626466||Abstract:||The optic disc is an important feature in the retina. We propose a method for the detection of the optic disc based on a supervised learning scheme. The method employs pixel and local neighbourhood features extracted from the ROI of a digital retinal fundus photograph. A support vector machine based classification mechanism is used to classify each image point as belonging to the cup and retina. The proposed method is evaluated on a sample image set of 68 retinal fundus images. The results show a high correlation (r>0.9) with the ground truth segmentation, with an overlap error of 6.02%, and found to be comparable to the inter-observer variability based on an independent second observer segmentation of the same data set. © 2010 IEEE.||Source Title:||2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10||URI:||http://scholarbank.nus.edu.sg/handle/10635/109757||ISBN:||9781424441235||DOI:||10.1109/IEMBS.2010.5626466|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 21, 2019
WEB OF SCIENCETM
checked on Sep 13, 2019
checked on Sep 20, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.