relation: https://khub.utp.edu.my/scholars/4065/
title: Despeckling of ultrasound images of bone fracture using multiple filtering algorithms
creator: Elamvazuthi, I.
creator: Muhd Zain, M.L.B.
creator: Begam, K.M.
description: Ultrasound images are popularly known to contain speckle noise that degrades the quality of the images for good and fast interpretation in many areas of medicine, especially for bone fracture detection. This necessitates the need for robust despeckling techniques for clinical practice. Therefore, a study was carried out to reduce speckle using filtering algorithms such as Wiener, Average, Median, Anisotropic Diffusion and Wavelets. This paper discusses the level of improvement obtained through these filtering algorithms using the peak signal-to-noise ratio (PSNR) as a measurement tool. The results of our work presented in this paper suggest that the combination of Daubechies-Wiener which we call as a hybrid technique with Anisotropic Diffusion, gave the best performance, which is a new contribution in this field. This despeckling algorithm can be further developed and evaluated at a larger scale. © 2011 Elsevier Ltd.
date: 2013
type: Article
type: PeerReviewed
identifier:   Elamvazuthi, I. and Muhd Zain, M.L.B. and Begam, K.M.  (2013) Despeckling of ultrasound images of bone fracture using multiple filtering algorithms.  Mathematical and Computer Modelling, 57 (1-2).  pp. 152-168.  ISSN 08957177     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866181811&doi=10.1016%2fj.mcm.2011.07.021&partnerID=40&md5=d94afc1f875d1e0b48604235e70c8887
relation: 10.1016/j.mcm.2011.07.021
identifier: 10.1016/j.mcm.2011.07.021