You are in:Home/Publications/Ben Abdallah M, Malek J, Belmabrouk H, Azar AT, Montreal JE and Krissian K (2015) Performance Evaluation of several Anisotropic Diffusion Filters for Fundus Imaging. International Journal of Intelligent Engineering Informatics, 3(1): 66 - 90.

Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Ben Abdallah M, Malek J, Belmabrouk H, Azar AT, Montreal JE and Krissian K (2015) Performance Evaluation of several Anisotropic Diffusion Filters for Fundus Imaging. International Journal of Intelligent Engineering Informatics, 3(1): 66 - 90.
Authors: Not Available
Year: 2015
Keywords: anisotropic diffusion filters; filtering; retinal images; performance evaluation; fundus imaging; image processing; partial differential equations; PDEs; nonlinear models; retinal vascular networks; medical diagnosis; image enhancement parameters; mean preservation; variance reduction; edge preservation.
Journal: International Journal of Intelligent Engineering Informatics
Volume: 3
Issue: 1
Pages: 66 - 90
Publisher: Inderscience Enterprises Ltd.
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

In image processing by partial differential equations, the first and simplest models to have and use are based on linear diffusion. The common difficulty of linear filters is the excessive smoothing that makes track edges difficult. Therefore, we can affirm that any improvement of these linear models must be carried out inside the diffusion operator, thus sacrificing their linearity. The work achieved in this context will make the subject of the following paper. We will see how these difficulties can be overcome by the use of the nonlinear models. This document treats the automatic preprocessing of a retinal vascular network in fundus images, using various anisotropic diffusion filters, in order to improve the interpretation of the images for the doctor's diagnosis. To evaluate the chosen methods, we have performed image enhancement parameters, mean preservation and variance reduction, and edge preservation.

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus