Please use this identifier to cite or link to this item:
|Title:||Focal edge association to glaucoma diagnosis||Authors:||Cheng, J.
|Issue Date:||2011||Citation:||Cheng, J.,Liu, J.,Wong, D.W.K.,Tan, N.M.,Lee, B.H.,Cheung, C.,Baskaran, M.,Wong, T.Y.,Aung, T. (2011). Focal edge association to glaucoma diagnosis. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS : 4481-4484. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2011.6091111||Abstract:||Glaucoma is an optic nerve disease resulting in the loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Clinically, ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type as well as the degree of closure. However, manual grading of the iridocorneal angle images is subjective and often time consuming. In this paper, we propose focal edge for automated iridocorneal angle grading. The iris surface is located to determine focal region and focal edges. The association between focal edges and angle grades is built through machine learning. A modified grading system with three grades is adopted. The experimental results show that the proposed method can correctly classify 87.3% open angle and 88.4% closed angle. Moreover, it can correctly classify 75.0% grade 1 and 77.4% grade 0 for angle closure cases. © 2011 IEEE.||Source Title:||Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS||URI:||http://scholarbank.nus.edu.sg/handle/10635/53522||ISBN:||9781424441211||ISSN:||1557170X||DOI:||10.1109/IEMBS.2011.6091111|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Apr 14, 2019
checked on Apr 7, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.