eprintid: 4065
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/40/65
datestamp: 2023-11-09 15:52:21
lastmod: 2023-11-09 15:52:21
status_changed: 2023-11-09 15:48:15
type: article
metadata_visibility: show
creators_name: Elamvazuthi, I.
creators_name: Muhd Zain, M.L.B.
creators_name: Begam, K.M.
title: Despeckling of ultrasound images of bone fracture using multiple filtering algorithms
ispublished: pub
keywords: Anisotropic Diffusion; Average; Median; PSNR; Ultrasound imaging; Wavelet; Wiener, Optical anisotropy; Speckle; Ultrasonic imaging; Ultrasonics, Signal filtering and prediction
note: cited By 39
abstract: 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
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866181811&doi=10.1016%2fj.mcm.2011.07.021&partnerID=40&md5=d94afc1f875d1e0b48604235e70c8887
id_number: 10.1016/j.mcm.2011.07.021
full_text_status: none
publication: Mathematical and Computer Modelling
volume: 57
number: 1-2
pagerange: 152-168
refereed: TRUE
issn: 08957177
citation:   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