Retina fundus image mask generation using pseudo parametric modeling technique
dc.contributor.author | Aibinu, Musa A. | |
dc.contributor.author | Salami, Momoh-Jimoh E. | |
dc.contributor.author | Shafie, A. A. | |
dc.date.accessioned | 2019-08-14T15:17:57Z | |
dc.date.available | 2019-08-14T15:17:57Z | |
dc.date.issued | 2010-11 | |
dc.description.abstract | ABSTRACT (abstract): The use of vascular intersection as one of the symptoms for monitoring and diagnosis of diabetic retinopathy from Fundus images have been widely reported in literatures. In this work, a new hybrid approach that makes use of three different methods of vascular intersection detection namely Modified Cross-Point Number (MCN), Combine Cross-Points Number (CCN) and Artificial Neural Network (ANN) technique is hereby proposed. Result obtained from the application of this technique to both simulated and experimental shows a very high accuracy and precision value in detecting both bifurcation and cross over points. Thus an improvement in bifurcation and vascular point detection and a good tool in the monitoring and diagnosis of diabetic retinopathy | en_US |
dc.identifier.citation | Aibinu, A. M., Salami, M. J. E., & Shafie, A. A. (2010). Retina fundus image mask generation using pseudo parametric modeling technique. IIUM Engineering Journal, 11(2), 163-177. | en_US |
dc.identifier.uri | http://repository.elizadeuniversity.edu.ng/handle/20.500.12398/510 | |
dc.language.iso | en | en_US |
dc.publisher | IIUM Engineering Journal | en_US |
dc.subject | Diabetes | en_US |
dc.subject | Parametric Modeling Technique | en_US |
dc.subject | Real-Valued Neural Network (RVNN) | en_US |
dc.subject | Retina Fundus Image | en_US |
dc.title | Retina fundus image mask generation using pseudo parametric modeling technique | en_US |
dc.type | Article | en_US |
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