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Издательство Morgan & Claypool, 2008, -181 pp.
It is well-known that speckle is a multiplicative noise that degrades image quality and the visual evaluation in ultrasound imaging. This necessitates the need for robust despeckling techniques for both routine clinical practice and teleconsultation. The goal for this book is to introduce the theoretical background (equations), the algorithmic steps, and the MATLAB code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering and wavelet filtering. The book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts, in the assessment of cardiovascular ultrasound images recorded from the carotid artery. The results of our work presented in this book, suggest that the linear local statistics filter DsFlsmv, gave the best performance, followed by the nonlinear geometric filter DsFgf4d, and the linear homogeneous mask area filter DsFlsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes (of ultrasound images recorded from the carotid artery for the assessment of stroke) based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by two medical experts. A despeckle filtering analysis and evaluation framework is proposed for selecting the most appropriate filter or filters for the images under investigation. These filters can be further developed and evaluated at a larger scale and in clinical practice in the automated image and video segmentation, texture analysis, and classification not only for medical ultrasound but for other modalities as well, such as synthetic aperture radar (SAR) images.Introduction to Ultrasound Imaging and Speckle Noise Despeckle Filtering Algorithms Evaluation Methodology Applications of Despeckle Filtering in Ultrasound Imaging Comparison and Discussion of Despeckle Filtering Algorithms Summary and Future Directions
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Despeckle Filtering Algorithms and Software for Ultrasound Imaging
Copyright © 2008 by Morgan & Claypool All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher. Despeckle Filtering Algorithms and Software for Ultrasound Imaging Christos P. Loizou and Constantinos S. Pattichis www.morganclaypool.com ISBN: 9781598296204 paperback ISBN: 9781598296211 ebook DOI: 10.2200/S00116ED1V01Y200805ASE001 A Publication in the Morgan & Claypool Publishers series SYNTHESIS LECTURES ON Algorithms and Software in ENGINEERING #1 Lecture #1 Series Editor: Andreas Spanias, Arizona State University Series ISSN pending with U.S. Library of Congress
Despeckle Filtering Algorithms and Software for Ultrasound Imaging Christos P. Loizou Intercollege, Cyprus
Constantinos S. Pattichis University of Cyprus
SYNTHESIS LECTURES ON ALGORITHMS AND SOFTWARE IN ENGINEERING #1
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Abstract It is well-known that speckle is a multiplicative noise that degrades image quality and the visual evaluation in ultrasound imaging. This necessitates the need for robust despeckling techniques for both routine clinical practice and teleconsultation. The goal for this book is to introduce the theoretical background (equations), the algorithmic steps, and the MATLAB™ code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering and wavelet filt