This book presents and describes imaging technologies that can be used to study chemical processes and structural interactions in dynamic systems, principally in biomedical systems. The imaging technologies, largely biomedical imaging technologies such as MRT, Fluorescence mapping, raman mapping, nanoESCA, and CARS microscopy, have been selected according to their application range and to the chemical information content of their data. These technologies allow for the analysis and evaluation of delicate biological samples, which must not be disturbed during the profess. Ultimately, this may mean fewer animal lab tests and clinical trials.

REINER SALZER, PHD, is a professor at the Institute for Analytical Chemistry at Technische Universität in Dresden, Germany.

Klappentext

A WALK THROUGH THE EXCITING FIELD OF MULTIMODALITY IMAGING AND ITS CLINICAL APPLICATIONS

This book offers a unique approach to biomedical imaging. Unlike other books on the market that cover just one or several modalities, Biomedical Imaging: Principles and Applications describes all important biomedical imaging modalities, showing how to capitalize on their combined strengths when investigating processes and interactions in dynamic systems.

Geared to non-experts looking for quick guidance on what modalities to choose for their work without getting bogged down in technical details, the book discusses technical fundamentals, molecular background, evaluation procedures, and case studies of clinical applications. With an emphasis on technologies known for their application range and the chemical information content of their data, the book covers such established modalities as X-ray, CT, MRI, and tracer imaging, as well as technologies using light or sound, including fluorescence and Raman imaging, CARS microscopy, sonography, and acoustic microscopy.

Including more than 200 figures (many in color) to help clarify the text, Biomedical Imaging:

• Reviews the current state of image-based diagnostic medicine as well as methods and tools for visualization
• Covers for each modality the basics of how it works, information parameters, instrumentation, and applications
• Compares the strengths and weaknesses of different imaging technologies
• Focuses on current and emerging applications for chemical analysis in extremely delicate samples
• Explains the utility of multimodality imaging in the rapidly expanding field of biophotonics

An excellent startup guide for researchers and clinicians wishing to combine different imaging technologies for a true multimodality approach to problem solving, Biomedical Imaging is also a useful reference for engineers who need to understand the biomedical basis of the measured data.

Inhalt

Preface xv

Contributors xvii

1 Evaluation of Spectroscopic Images 1
Patrick W.T. Krooshof, Geert J. Postma, Willem J. Melssen, and Lutgarde M.C. Buydens

1.1 Introduction 1

1.2 Data Analysis 2

1.2.1 Similarity Measures 3

1.2.2 Unsupervised Pattern Recognition 4

1.2.2.1 Partitional Clustering 4

1.2.2.2 Hierarchical Clustering 6

1.2.2.3 Density-Based Clustering 7

1.2.3 Supervised Pattern Recognition 9

1.2.3.1 Probability of Class Membership 9

1.3 Applications 11

1.3.1 Brain Tumor Diagnosis 11

1.3.2 MRS Data Processing 12

1.3.2.1 Removing MRS Artifacts 12

1.3.2.2 MRS Data Quantitation 13

1.3.3 MRI Data Processing 14

1.3.3.1 Image Registration 15

1.3.4 Combining MRI and MRS Data 16

1.3.4.1 Reference Data Set 16

1.3.5 Probability of Class Memberships 17

1.3.6 Class Membership of Individual Voxels 18

1.3.7 Classification of Individual Voxels 20

1.3.8 Clustering into Segments 22

1.3.9 Classification of Segments 23

1.3.10 Future Directions 24

References 25

2 Evaluation of Tomographic Data 30
Jorg van den Hoff

2.1 Introduction 30

2.2 Image Reconstruction 33

2.3 Image Data Representation: Pixel Size and Image Resolution 34

2.4 Consequences of Limited Spatial Resolution 39

2.5 Tomographic Data Evaluation: Tasks 46

2.5.1 Software Tools 46

2.5.2 Data Access 47

2.5.3 Image Processing 47

2.5.3.1 Slice Averaging 48

2.5.3.2 Image Smoothing 48

2.5.3.3 Coregistration and Resampling 51

2.5.4 Visualization 52

2.5.4.1 Maximum Intensity Projection (MIP) 52

2.5.4.2 Volume Rendering and Segmentation 54

2.5.5 Dynamic Tomographic Data 56

2.5.5.1 Parametric Imaging 57

2.5.5.2 Compartment Modeling of Tomographic Data 57

2.6 Summary 61

References 61

3 X-Ray Imaging 63
Volker Hietschold

3.1 Basics 63

3.1.1 History 63

3.1.2 Basic Physics 64

3.2 Instrumentation 66

3.2.1 Components 66

3.2.1.1 Beam Generation 66

3.2.1.2 Reduction of Scattered Radiation 67

3.2.1.3 Image Detection 69

3.3 Clinical Applications 76

3.3.1 Diagnostic Devices 76

3.3.1.1 Projection Radiography 76

3.3.1.2 Mammography 78

3.3.1.3 Fluoroscopy 81

3.3.1.4 Angiography 82

3.3.1.5 Portable Devices 84

3.3.2 High Voltage and Image Quality 85

3.3.3 Tomography/Tomosynthesis 87

3.3.4 Dual Energy Imaging 87

3.3.5 Computer Applications 88

3.3.6 Interventional Radiology 92

3.4 Radiation Exposure to Patients and Employees 92

References 95

4 Computed Tomography 97
Stefan Ulzheimer and Thomas Flohr

4.1 Basics 97

4.1.1 History 97

4.1.2 Basic Physics and Image Reconstruction 100

4.2 Instrumentation 102

4.2.1 Gantry 102

4.2.2 X-ray Tube and Generator 103

4.2.3 MDCT Detector Design and Slice Collimation 103

4.2.4 Data Rates and Data Transmission 107

4.2.5 Dual Source CT 107

4.3 Measurement Techniques 109

4.3.1 MDCT Sequential (Axial) Scanning 109

4.3.2 MDCT Spiral (Helical) Scanning 109

4.3.2.1 Pitch 110

4.3.2.2 Collimated and Effe...