Statistical Analysis of Noise in MRI Modeling, Filtering and Estimat
This unique text/reference presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques dr
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atistical Analysis of Noise in MRI Modeling, Filtering and Estimation
Statistical Analysis of Noise in MRI
Santiago Aja-Fernández Gonzalo Vegas-Sánchez-Ferrero
Statistical Analysis of Noise in MRI Modeling, Filtering and Estimation
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Gonzalo Vegas-Sánchez-Ferrero Harvard Medical School Brigham and Women’s Hospital Boston, MA USA
Santiago Aja-Fernández ETSI Telecomunicación Universidad de Valladolid Valladolid Spain
ISBN 978-3-319-39933-1 DOI 10.1007/978-3-319-39934-8
ISBN 978-3-319-39934-8
(eBook)
Library of Congress Control Number: 2016941078 © Springer International Publishing Switzerland 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
“How do you peel a porcupine?”
Foreword
Medical imaging and the field of radiology have come a long way since Wilhelm Röntgen’s discovery of the X-ray in 1895. Medical imaging is today an integral part of modern medicine and includes a large number of modalities such as X-ray computed tomography (CT), ultrasound, positron emission tomography (PET), and magnetic resonance imaging (MRI). This book, “Statistical Analysis of Noise in MRI,” presents a modern signal processing approach for medical imaging with a focus on noise modeling and estimation for MRI. MRI scanners use strong magnetic fields, radio waves, and magnetic field gradients to form images of the body. MRI has seen a tremendous development during the past four decades and is now an indispensable part of diagnostic medicine. MRI is unparalleled in the investigation of soft tissues due to its superior contrast sensitivity and tissue discrimination. I met the lead author of this book Dr. Santiago Aja-Fernández for the first time in 2006 when he was a visiting Fulbright scholar in my laboratory, Laboratory of Mathematics in Imaging at Brigham and Women’s Hospital, Harvard Medical School, Boston. His goal was clear fr
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