BIOMEDICAL IMAGING, VISUALIZATION, AND ANALYSIS
RICHARD A. ROBB, Ph.D.
WILEY-LISS
A John Wiley & Sons, Inc., Publication
2000
CONTENTS
PREFACE
ACKNOWLEDGEMENTS
1 INTRODUCTION TO IMAGING SCIENCE
1.1 Introduction / 1
1.2 Historical Perspectives / 2
1.3 Some Definitions and Fundamental Issues / 8
1.4 Ancillary Issues / 12
References / 13
2 IMAGE ACQUISITION SYSTEMS
2.1 Introduction / 17
2.2 Fundamentals of Image Acquisition / 18
2.2.1 Image Formation / 18
2.2.2 Image Characteristics / 18
2.2.2.1 Spatial Resolution / 18
2.2.2.2 Contrast Resolution / 19
2.2.2.3 Temporal Resolution / 19
2.3 Biomedical Image Acquisition Systems / 19
2.3.1 Conventional Radiography / 20
2.3.1.1 Signal Acquisition / 20
2.3.1.2 Iamge Characteristics / 20
2.3.1.3 Three-Dimensional Superposition in Radiographs / 21
2.3.2 Conventional Axial Tomography / 21
2.3.2.1 Signal Acquisition / 21
2.3.3 X-Ray Computed Tomography (CT) / 22
2.3.3.1 Signal Acquisition / 25
2.3.3.2 Image Formation and Reconstruction / 28
2.3.3.3 Image Characteristics / 32
2.3.4 Magnetic Resonance Imaging (MRI) / 34
2.3.4.1 Signal Acquisition / 36
2.3.4.2 Image Formation and Reconstruction / 38
2.3.4.3 Image Characteristics / 40
2.3.4.4 MR Elastography / 41
2.3.5 Nuclear Medicine Imaging / 42
2.3.5.1 Signal Photon Emission CT (SPECT) / 42
2.3.5.2 Positron Emission Tomography (PET) / 44
2.3.6 Ultrasound / 46
2.3.6.1 Signal Acquisition / 46
2.3.7 Biomagnetic Imaging / 49
2.3.7.1 Signal Acquisition / 49
2.3.7.2 Image Formation and Reconstruction / 50
2.3.8 Microscopy Imaging / 50
2.3.8.1 Signal Acquisition / 51
References / 54
3 IMAGE REPRESENTATIONS, DISPLAYS, COMMUNICATIONS AND DATABASES
3.1 Introduction / 59
3.2 Volume Image Representation / 60
3.2.1 Volume Image Data Organization / 61
3.2.2 Coordinate Systems and Object Orientation / 62
3.2.3 Value Representation / 64
3.2.4 Interpolation and Transformation / 64
3.3 Computers and Computer Storage / 65
3.3.1 Data Representation / 66
3.3.2 Computer Storage / 67
3.4 Implications of Computer Storage for Image Processing / 68
3.5 Display Types and Devices / 71
3.5.1 Converting Numerical Data into Sensory Perception / 72
3.5.2 Color Sensitivity / 73
3.5.3 Two-Dimensional Displays / 73
3.5.3.1 Presentation Formats / 73
3.5.3.2 Ergonomics / 76
3.5.3.3 Printing Biomedical Images / 77
3.5.4 Three-Dimensional Displays / 78
3.5.4.1 Three-Dimensional Graphics Accelerators / 78
3.5.4.2 Stereoscopic Visualization / 79
3.5.4.3 Vibrating Mirror / 81
3.5.4.4 Dextroscope / 82
3.5.4.5 Other Senses / 82
3.5.5 Limitations of Display Systems / 84
3.5.5.1 Spatial Resolution / 84
3.5.5.2 Pixel "Depth" / 85
3.5.5.3 Temporal Resolution / 87
3.5.5.4 Gamma Correction / 87
3.5.6 Implications of Display Systems for Image Processing and
Analysis / 88
3.6 Image Transmission Between Computers / 88
3.6.1 General Types of Digital Networks / 89
3.6.1.1 Point to Point / 89
3.6.1.2 Wide Area Networks / 89
3.6.1.3 Local Area Networks / 89
3.6.1.4 Clusters / 90
3.6.2 Network Languages (Protocols) / 90
3.6.2.1 TCP1P / 91
3.6.2.2 File Sharing Protocols: NFS and SMB / 91
3.6.2.3 Image Transmission Protocols / 91
3.6.3 Utilizing Networks / 92
3.6.3.1 Distributed Processing / 92
3.6.3.2 Broadcasting / 94
3.6.4 Implications of Networks on Image Processing / 95
3.7 Digital Image Formats / 95
3.7.1 Raw Images: Pixel Order, Channels, and Dimensions / 96
3.7.2 Metadata: The Image Header / 96
3.7.3 Pixel/Voxel Packing / 97
3.7.4 Image Compression / 100
3.7.4.1 Lossless Image Compression / 100
3.7.4.2 Lossy Compression / 101
3.7.4.3 Compression Hardware / 103
3.8 Image Databases / 103
References / 107
4 IMAGE VISUALIZATION
4.1 Introduction / 109
4.2 Visualization Methods / 111
4.2.1 Two-Dimensional Image Generation and Display / 112
4.2.1.1 Multiplanar Reformatting / 112
4.2.1.2 Oblique Sectioning / 112
4.2.1.3 Curved Sectioning / 115
4.2.2 Three-Dimensional Image Generation and Display / 115
4.2.2.1 Surface Rendering / 118
4.2.2.2 Volume Rendering / 119
4.2.2.3 Volume Modeling / 125
4.3 Examples of 3-D Visualization / 133
4.3.1 Virtual Endoscopy / 135
4.3.2 Surgery Planning and Rehearsal / 138
4.3.3 Dynamic (4-D) and Parametric Visualizations / 142
4.3.4 Visualization Across Scale Space / 149
References / 150
5 IMAGE PROCESSING AND ANALYSIS
5.1 Introduction / 157
5.2 Image Enhancement and Restoration / 158
5.2.1 Histogram Operations / 158
5.2.2 Spatial Filtering / 161
5.2.3 Frequency Filtering / 163
5.2.4 Image Restoration / 164
5.2.4.1 Deconvolution / 166
5.3 Image Segmentation / 168
5.3.1 Introduction / 168
5.3.2 Manual Methods / 169
5.3.3 Thresholding / 170
5.3.4 Region Growing / 172
5.3.5 Mathematical Morphology / 174
5.3.5.1 An Automated Segmentation Algorithm / 176
5.3.6 Active Contours ("Snakes") / 177
5.3.7 Other Segmentation Approaches and Tools / 180
5.4 Image Registration / 181
5.4.1 Introduction / 181
5.4.2 Purposes and Applications / 182
5.4.2.1 Unimodal Applications / l82
5.4.2.2 Multimodal Applications / 185
5.4.3 Classification of Registration Methods / 188
5.4.3.1 Dimensionality of the Registration Task / 188
5.4.3.2 Nature of the Transformation / 189
5.4.3.3 Match Quality or Error Metric / 192
5.4.3.4 Search Strategy / 195
5.4.3.5 Confounding Factors / 197
5.4.4 Evaluating and Validating Image Registration / 197
5.5 Multispectral Class)fication / 198
5.5.1 Introduction / 198
5.5.1.1 An Example / 199
5.5.1.2 Sources of Data / 201
5.5.2 Methods / 202
5.5.2.1 Image Space and Preprocessing / 202
5.5.2.2 Unsupervised and Supervised Class)fication / 203
5.5.2.3 Multispectral Space / 203
5.5.2.4 Unsupervised Algorithms / 204
5.5.2.5 Supervised Algorithms / 208
5.5.2.6 Spatial and Feature Context / 210
5.5.2.7 Verification of Feature Maps / 210
5.5.3 Feature Space Applied / 212
5.6 Image Measurement and Meaning / 213
5.6.1 Introduction / 213
5.6.2 Region of Interest Measurements / 215
5.6.3 Stereological Measurement Techniques / 224
5.6.4 Measurement in the Frequency Domain / 227
5.6.5 Meaning of Measurements / 227
References / 230
6 IMAGE MODELING
6.1 Introduction / 237
6.2 Basic Concepts / 238
6.3 Volumetric Modeling Algorithms / 240
6.3.1 Surface Fitting-Local Measures / 240
6.3.2 Deformation Algorithms / 244
6.3.3 Hybrid Algorithms / 250
6.3.4 Decimation and Simplification / 253
6.3.4.1 Geometry Removal / 254
6.3.4.2 Sampling / 255
6.3.4.3 Adaptive Subdivision / 256
6.3.5 Incorporating Physical and Physiological Properties / 257
6.4 Use of Geometric Models in Immersive Environments / 262
References / 266
7 BIOMEDICAL APPLICATIONS
7.1 Introduction / 273
7.2 Neuronal Microanatomy and Function / 273
7.3 Corneal Cell Analysis / 277
7.4 Trabecular Tissue Analysis in Glaucoma / 279
7.5 Prostate Microvessels / 281
7.6 Prostate Surgery Planning / 283
7.7 Craniofacial Surgery Planning and Evaluation / 283
7.8 Orthognathic Surgery Evaluation / 285
7.9 Orthopedic Surgery Planning / 287
7.10 Neurosurgery Planning, Rehearsal, and Intraoperative Guidance / 289
7.11 Epilepsy Imaging Using SISCOM / 295
7.12 Radiation Treatment Planning and Assessment of Treatment / 298
7.13 Virtual Endoscopy / 300
7.14 Image-Guided Diagnosis and Treatment of Coronary Artery Disease / 306
7.15 Image-Guided Cardiac Ablation Therapy / 310
7.16 Cardiac Motion Analysis / 313
7.17 Anesthesia Simulator / 315
References / 318
8 THE FUTURE
References / 329
INDEX
PREFACE
"After a certain high level of technical skill is achieved, science and art
tend to coalesce in esthetics, plasticity, and form. The greatest
scientists are always artists as well."
-Albert Einstein, Einstein Archive 33-257
The development and applications of biomedical imaging continue to evolve
and expand at an accelerated pace. The high level of technology and
expertise achieved has spawned, as Einstein suggests, a plastic blend of
science and art. Some methods and applications have become rigorous and
routine; others are still forming and transforming, but hold sign)ficant
potential. Since the publication of Three Dimensional Biomedical Imaging:
Principles and Practice in 1995, several remarkable advances and
sign)ficant improvements have occurred in methodologies and technology that
extend and refine the discipline. Even more dramatically, these scientific
developments have been accompanied by a rush of new applications and a
maturation of others, achieving an important evolutionary transition from
principles to practice.
This sequel attempts to document some of these important methodological and
technological advances and growing applications. For completeness, a brief
review of fundamental principles and underlying theories addressed in the
earlier book is included, as is some of the more important durable material
from each chapter, but emphasis is mainly on new and refined methods for
visualization and analysis, and especially on a variety of emergent
successful applications. Both books together are more complementary than
redundant, and more complete than either alone, but this sequel, like the
original, can stand independent of any preceding work. New in this book are
descriptions of innovative imaging methods (e.g., spiral and multidetector
CT and MR elastography), novel visualization techniques (e.g., parametric
displays, virtual reality), new processing algorithms (e.g., joint entropy
registration and automatic classification), image modeling (e.g.,
algorithms that translate "pixels to polygons'' to obtain highly accurate
anatomic models), and many recent clinical and biological applications,
including uses in medical training.
The field of biomedical imaging advances so rapidly and sign)ficantly
that scientists, engineers, physicians, educators, and students working in
the field need relatively frequent documentation of progress in order to
stay abreast of developments. This is best provided by reputable journals
and periodicals. However, more extensive, integrated publications that
connect fundamental principles and new scientific advances to practical
applications and usage are also important. Such works are challenging, but
when realized they do not become obsolete; rather they form durable links
in the chain that faithfully connects the past to the present, and the
present to the future. This book attempts to meet that challenge and
provide an enduring bridge in the expanding field of biomedical imaging.
To accomplish this, emphasis in this treatise is on comprehensive
explanation, ample illustration, and copious references, rather than on
complex physics or detailed math. At the end of each chapter is a list of
references related to the subject matter in the chapter. These include many
historical and landmark papers, classic texts, and modern references to
some of the most advanced work. These myriad citations should be valuable
to the reader for pursuing in depth any topic introduced in this book. Most
chapters are also accompanied by a generous number of carefully selected
illustrations that support and enhance the text. Indeed the book is about
pictures-art as well as science!
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