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https://doi.org/10.1109/IEMBS.2010.5626466
Title: | Learning-based approach for the automatic detection of the optic disc in digital retinal fundus photographs | Authors: | Wong, D.W.K. Liu, J. Tan, N.M. Yin, F. Lee, B.H. Wong, T.Y. |
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 |
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