Please use this identifier to cite or link to this item: http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/510
Title: Retina fundus image mask generation using pseudo parametric modeling technique
Authors: Aibinu, Musa A.
Salami, Momoh-Jimoh E.
Shafie, A. A.
Keywords: Diabetes
Parametric Modeling Technique
Real-Valued Neural Network (RVNN)
Retina Fundus Image
Issue Date: Nov-2010
Publisher: IIUM Engineering Journal
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.
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
URI: http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/510
Appears in Collections:Research Articles

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