Please use this identifier to cite or link to this item:
|Title:||Retina fundus image mask generation using pseudo parametric modeling technique|
|Authors:||Aibinu, Musa A.|
Salami, Momoh-Jimoh E.
Shafie, A. A.
Parametric Modeling Technique
Real-Valued Neural Network (RVNN)
Retina Fundus Image
|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|
|Appears in Collections:||Research Articles|
Files in This Item:
|Retina fundus image mask generation using pseudo parametric modeling technique.pdf||Article full-text||267.92 kB||Adobe PDF|
Items in EUSpace are protected by copyright, with all rights reserved, unless otherwise indicated.