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 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Retina fundus image mask generation using pseudo parametric modeling technique.pdf | Article full-text | 267.92 kB | Adobe PDF | View/Open |
Items in EUSpace are protected by copyright, with all rights reserved, unless otherwise indicated.