Compression of Biomedical Images and Signals E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 489

Veröffentlichungsjahr: 2013

Beschreibung

During the last decade, image and signal compression for storage and transmission purpose has seen a great expansion. But what about medical data compression? Should a medical image or a physiological signal be processed and compressed like any other data? The progress made in imaging systems, storing systems and telemedicine makes compression in this field particularly interesting. However, this compression has to be adapted to the specificities of biomedical data which contain diagnosis information. As such, this book offers an overview of compression techniques applied to medical data, including: physiological signals, MRI, X-ray, ultrasound images, static and dynamic volumetric images. Researchers, clinicians, engineers and professionals in this area, along with postgraduate students in the signal and image processing field, will find this book to be of great interest.

Leseprobe

Table of Contents

Preface

Chapter 1. Relevance of Biomedical Data Compression

1.1. Introduction

1.2. The management of digital data using PACS

1.3. The increasing quantities of digital data

1.4. Legal and practical matters

1.5. The role of data compression

1.6. Diagnostic quality

1.7. Conclusion

1.8. Bibliography

Chapter 2. State of the Art of Compression Methods

2.1. Introduction

2.2. Outline of a generic compression technique

2.3. Compression of still images

2.4. The compression of image sequences

2.5. Compressing 1D signals

2.6. The compression of 3D objects

2.7. Conclusion and future developments

2.8. Bibliography

Chapter 3. Specificities of Physiological Signals and Medical Images

3.1. Introduction

3.2. Characteristics of physiological signals

3.3. Specificities of medical images

3.4. Conclusion

3.5. Bibliography

Chapter 4. Standards in Medical Image Compression

4.1. Introduction

4.2. Standards for communicating medical data

4.3. Existing standards for image compression

4.4. Conclusion

4.5. Bibliography

Chapter 5. Quality Assessment of Lossy Compressed Medical Images

5.1. Introduction

5.2. Degradations generated by compression norms and their consequences in medical imaging

5.3. Subjective quality assessment

5.4. Objective quality assessment

5.5. Conclusion

5.6. Bibliography

Chapter 6. Compression of Physiological Signals

6.1. Introduction

6.2. Standards for coding physiological signals

6.3. EEG compression

6.4. ECG compression

6.5. Conclusion

6.6. Bibliography

Chapter 7. Compression of 2D Biomedical Images

7.1. Introduction

7.2. Reversible compression of medical images

7.3. Lossy compression of medical images

7.4. Progressive compression of medical images

7.5. Conclusion

7.6. Bibliography

Chapter 8. Compression of Dynamic and Volumetric Medical Sequences

8.1. Introduction

8.2. Reversible compression of (2D+t) and 3D medical data sets

8.3. Irreversible compression of (2D+t) medical sequences

8.4. Irreversible compression of volumetric medical data sets

8.5. Conclusion

8.6. Bibliography

Chapter 9. Compression of Static and Dynamic 3D Surface Meshes

9.1. Introduction

9.2. Definitions and properties of triangular meshes

9.3. Compression of static meshes

9.4. Compression of dynamic meshes

9.5. Conclusion

9.6. Appendices

9.7. Bibliography

Chapter 10. Hybrid Coding: Encryption-Watermarking-Compression for Medical Information Security

10.1. Introduction

10.2. Protection of medical imagery and data

10.3. Basics of encryption algorithms

10.4. Medical image encryption

10.5. Medical image watermarking and encryption

10.6. Conclusion

10.7. Bibliography

Chapter 11. Transmission of Compressed Medical Data on Fixed and Mobile Networks

11.1. Introduction

11.2. Brief overview of the existing applications

11.3. The fixed and mobile networks

11.4. Transmission of medical images

11.5. Conclusion

11.6. Bibliography

Conclusion

List of Authors

Index

First published in France in 2007 by Hermes Science/Lavoisier entitled “Compression des images et des signaux médicaux”

First published in Great Britain and the United States in 2008 by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd6 Fitzroy SquareLondon W1T 5DXUKwww.iste.co.ukJohn Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USAwww.wiley.com

© ISTE Ltd, 2008

© LAVOISIER, 2007

The rights of Amine Naït-Ali and Christine Cavaro-Ménard to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Cataloging-in-Publication Data

Compression des images et des signaux médicaux. English.

Compression of biomedical images and signals / edited by Amine Naït-Ali, Christine Cavaro-Menard.

p. ; cm.

Includes bibliographical references and index.

Translated from French.

ISBN 978-1-84821-028-8

1. Diagnosis--Data processing. 2. Data compression (Computer science) 3. Medical informatics. I. Naït-Ali, Amine. II. Cavaro-Menard, Christine. III. Title.

[DNLM: 1. Data Compression. 2. Diagnostic Imaging. WN 26.5 C7355c 2008a]

RC78.7.D35C63813 2008

RC78.7.D35C63813 2008

2008003130

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN: 978-1-84821-028-8

Preface

Although we might not be aware of this, compression methods are used on a daily basis to store or transmit data. We can find examples of this by looking at our computers (which compress large folders with a simple click of the mouse), our mobile phones (which integrate Codecs), our digital and video cameras (including post-compression recording on flash memory or others), our CD and MP3 players (which are capable of storing hundreds or thousands of songs), our High Definition digital televisions (using the MPEG-2/MPEG-4 compression standards) and our DVD players (which allow us to visualize data in various formats, such as the MPEG-4 format).

Consideration of these can lead us to ask the following question: how does this apply to the medical field?

Although some of the thousands of observations made by physicians are still recorded on paper using radiological film, much of the data acquired (signals, images) are now digital. In order to properly manage the huge amount of medical information, it is essential to exploit all of this digital data efficiently.

It is obvious that most doctors, wherever they are located, would appreciate efficient and fast access to the medical information pertaining to their patient. For instance, suppose that the doctor uses some type of mobile imaging system (for instance, an ultrasound system) for the purpose of analysis. As a consequence, the main clinical observations can be transmitted to a medical center for a preliminary check-up. Of course, in this case, secure data might be transmitted by telephone line or simply through the Internet. In fact, this acquisition/transmission protocol can be established so that the patient could be directed efficiently to the most appropriate clinical service in order to pursue the medical examination further.

For such changes to take place, data compression will be necessary both for the transmission as well as for the storage of all medical information. In fact, many authors have been interested in the medical compression field, and numerous techniques have been dedicated to this purpose. However, as the title Compression of Biomedical Images and Signals suggests, we have aimed to work collectively on this topic while giving detailed consideration to the use of recent technology in medicine, focusing particularly on compression.

This book will address questions such as the following: should bioelectric or physiological signals be compressed as audio signals? Should we compress a medical image as if it had been acquired by a simple camera? What about threedimensional images? In other words, should we directly apply common compression methods to medical data? Should we compress the images with or without losing any information at all? Is there a compression method specific to medical data? In order to answer questions on such a sensitive and delicate topic, we have gathered the skills of over 20 researchers from all corners of France and from various medical and scientific communities including: the signal and image community and the medical community. Such a topic cannot simply be seen from the perspective of a single community, in the sense that one community cannot provide objective judgment on the topic whilst at the same time being involved in its activity. Moreover, a multi-disciplinary reflection is enriching and produces more fruitful work. We therefore hope that this piece of work will serve as a starting point for all young researchers in scientific and medical communities wishing to engage in this particular field. It should thus be used as additional reading to any specialized course module at a Masters level (in science or in medicine).

This book is organized into 11 chapters and structured in the following way.

Chapter 1 describes how important the role of compression is in the medical field. It is built on the observations and points of view of medical experts in images and signals. Their experiences as doctors working in imaging poles have helped us outline the function of medical information compression. It is important to note however that the views upon which our argument is based are specifically relevant to the current state of technological developments (2006) and that innovations in this field are recognized and significant.

Chapter 2 deals with the state of compression methods, and more generally the different compression norms. Some of them can be used to compress medical data while others cannot. Throughout the following nine chapters we will be making constant references to this particular chapter, most notably when comparing the different methods applied to medical data.

Chapter 3 is an introduction to the subsequent chapters. It outlines important features of medical signals and images that are used throughout the discussion in the rest of the book and in various descriptions of certain specific compression methods.

Chapter 4 describes the role of compression norms applied to medical images. This chapter will introduce standardization committees present in the field of medical information exchange as well as the DICOM standard which encompasses almost all medical images. This standard is undergoing constant improvement and incorporates a variety of different compression methods.

Strong compressions with a high risk of information loss are not used in clinical routine for the simple reason that such possible degradations may thwart the medical diagnosis. Chapter 5 outlines the different approaches commonly used to evaluate the quality of reconstructed medical images following lossy compression.

Chapter 6 specifically concerns the compression of physiological signals. Specific attention will be given to electrocardiogram (ECG) compression.

Chapter 7 reviews the different techniques applied (and often adapted) to medical images. It will look at lossless, lossy and progressive compression methods.

Chapter 8 will look into the compression methods of image sequences, represented as videos (2D+t) or as a non-geometrical volume (3D). The use and popularity of this type of imaging is growing rapidly.

Chapter 9 deals more particularly with geometrical (3D) and (3D+t) compression methods. These techniques are particularly interesting today as they have become the main subjects of various studies and practices on organs such as the heart and lungs. This chapter will conclude with a look at potential prospects and opportunities for the use of such methods.

The security aspects of medical imageries will be looked at in Chapter 10. This chapter will also address encrypting techniques.

The final chapter, Chapter 11, looks at wireless transmission of medical images as well as the potential problems that may arise linked to transmission channels. Various solutions will then be suggested as a possible answer to such problems.

Various medical images used as illustrations throughout this work have been taken from the MeDEISA1 database Medical Database for the Evaluation of Image and Signal Processing, created in 2006. This evolving database can be accessed freely through the Internet and gathers a number of images obtained by different acquisition methods (based on recent acquisition systems). Researchers are encouraged to use this database in order to evaluate their own algorithms.

We would like to thank everyone who has participated in the creation of this work. Special thanks go to Christian Olivier and William Puech for their precious help with planning the structure of the book. We would also like to thank Marie Lamy and Helen Bird for the translation and Sophie Fuggle and Amitava Chattejee for their corrections. Thank you all.

Written by Amine NAÏT-ALI and Christine CAVARO-MÉNARD.

1 Accessible at http://www.medeisa.net.

Chapter 11

Relevance of Biomedical Data Compression

1.1. Introduction

Medical information, composed of clinical data, images and other physiological signals, has become an essential part of a patient‘s care, whether during screening, the diagnostic stage or the treatment phase. Data in the form of images and signals form part of each patient‘s medical file, and as such have to be stored and often transmitted from one place to another.

Over the past 30 years, information technology (IT) has facilitated the development of digital medical imaging. This development has mainly concerned Computed Tomography (CT), Magnetic Resonance Imaging (MRI), the different digital radiological processes for vascular, cardiovascular and contrast imaging, mammography, diagnostic ultrasound imaging, nuclear medical imaging with Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET). All these processes (which will be examined in Chapter 3) are producing ever-increasing quantities of images. The same is true for optical imaging: video-endoscopies, microscopy, etc.

The development of this digital imaging creates the obvious problem of the transmission of the images within healthcare centers, and from one establishment to another, as well as the problem of storage and archival. Compression techniques can therefore be extremely useful when we consider the large quantities of data in question.

Ten years ago, physicians were hostile towards the compression of data. The risk of losing a piece of diagnostic information does not sit well with medical ethics. Failing to identify a life-threatening illness in its early stages due to lost information is unthinkable, given the importance of early diagnosis in such cases. The evolution of digital imaging, retrieval systems and Picture Archiving and Communication Systems (PACS), alongside compression systems, has resulted in changing attitudes, and compression is now accepted and even desired by medical experts.

In this chapter, we will begin by presenting the IT systems which enable the safe archival and communication of medical data, their usefulness and their limitations (section 1.2). Next, with the help of three examples, we will look at the increase – which has been considerable over the past 30 years – in digital data collected in health centers (section 1.3). The problem of the archival and communication of data will then be examined in section 1.4 in relation to clinical practice and legal issues. Each of these areas of comment and debate will help to establish the advantages of compressing medical data, which is the key objective of this chapter. The concerns of the medical community regarding compression, and the ways to tackle these objections, are discussed in section 1.6. The conclusion aims to present possibilities for the foreseeable future, as enabled by compression.

1.2. The management of digital data using PACS

A PACS is composed of an archival system, a quantity (variable in size) of examinations available in real-time from a storage space reachable at high-speed, a system allowing these data to be accessed by those carrying out the examinations, and also a system for the communication of examination results, including images, within a healthcare center and also externally. This communication is generally carried out by a server, on demand, with Internet technology as its basis.