Visualization in Medicine: Theory, Algorithms, and Applications
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Table of contents
- Table of Contentsx
- Forewordxx
- Prefacexxi
- Chapter 1. Introduction1
- 1.1 Visualization in Medicine as a Specialty of Scientific Visualization1
- 1.2 Computerized Medical Imaging3
- 1.3 2D and 3D Visualizations6
- 1.4 Organization7
- Part I: Acquisition, Analysis, and Interpretation of Medical Volume Data11
- Chapter 2. Medical Image Data and Visual Perception13
- 2.1 Medical Image Data13
- 2.2 Data Artifacts17
- 2.3 Sensitivity and Specificity26
- 2.4 Visual Perception27
- 2.5 Summary34
- Chapter 3. Acquisition of Medical Image Data35
- 3.1 X-ray Imaging36
- 3.2 Computed Tomography41
- 3.3 Magnetic Resonance Imaging48
- 3.4 Ultrasound57
- 3.5 Positron Emission Tomography (PET)60
- 3.6 Single-Photon Emission Computed Tomography (SPECT)61
- 3.7 Summary63
- Chapter 4. Medical Volume Data in Clinical Practice65
- 4.1 Storage of Medical Image Data65
- 4.2 Conventional Film-based Diagnosis67
- 4.3 Soft-Copy Reading69
- 4.4 Summary80
- Chapter 5. Image Analysis for Medical Visualization83
- 5.1 Requirements84
- 5.2 Preprocessing and Filtering85
- 5.3 General Segmentation Approaches95
- 5.4 Model-based Segmentation Methods109
- 5.5 Interaction Techniques116
- 5.6 Postprocessing of Segmentation Results119
- 5.7 Skeletonization122
- 5.8 Validation of Segmentation Methods124
- 5.9 Registration and Fusion of Medical Image Data126
- 5.10 Summary131
- Part II: Volume Visualization135
- Chapter 6. Fundamentals of Volume Visualization137
- 6.1 The Volume Visualization Pipeline137
- 6.2 Histograms and Volume Classification137
- 6.3 Illumination in Scalar Volume Datasets145
- 6.4 Summary152
- Chapter 7. Indirect Volume Visualization155
- 7.1 Plane-Based Volume Rendering155
- 7.2 Surface-Based Volume Rendering156
- 7.3 Surface Postprocessing173
- 7.4 Summary180
- Chapter 8. Direct Volume Visualization183
- 8.1 Theoretical Models for Direct Volume Rendering183
- 8.2 The Volume Rendering Pipeline187
- 8.3 Compositing189
- 8.4 Summary195
- Chapter 9. Algorithms for Direct Volume Visualization197
- 9.1 Ray Casting197
- 9.2 Shear Warp203
- 9.3 Splatting206
- 9.4 Texture-Mapping212
- 9.5 Other Direct Volume Rendering Approaches219
- 9.6 Direct Volume Rendering of Segmented Volume Data221
- 9.7 Hybrid Volume Rendering223
- 9.8 Validation of Volume Visualization Algorithms228
- 9.9 Summary235
- Chapter 10. Exploration of Dynamic Medical Volume Data237
- 10.1 Introduction237
- 10.2 Medical Background238
- 10.3 Basic Visualization Techniques241
- 10.4 Data Processing242
- 10.5 Advanced Visualization Techniques244
- 10.6 Case Study: Tumor Perfusion248
- 10.7 Case Study: Brain Perfusion253
- 10.8 Summary256
- Part III: Exploration of Medical Volume Data259
- Chapter 11. Transfer Function Specification261
- 11.1 Strategies for One-Dimensional Transfer Functions262
- 11.2 Multidimensional Transfer Functions270
- 11.3 Gradient-based Transfer Functions275
- 11.4 Distance-based Transfer functions280
- 11.5 Local and Spatialized Transfer Functions286
- 11.6 Summary288
- Chapter 12. Clipping, Cutting, and Virtual Resection291
- 12.1 Clipping291
- 12.2 Virtual Resection294
- 12.3 Virtual Resection with a Deformable Cutting Plane297
- 12.4 Cutting Medical Volume Data307
- 12.5 Summary310
- Chapter 13. Measurements in Medical Visualization313
- 13.1 General Design Issues315
- 13.2 3D Distance Measurements317
- 13.3 Angular Measurements321
- 13.4 Interactive Volume Measurements323
- 13.5 Interactive Volume Measurements324
- 13.6 Minimal Distance Computation329
- 13.7 Further Automatic Measurements336
- 13.8 Summary337
- Part IV: Advanced Visualization Techniques341
- Chapter 14. Visualization of Anatomic Tree Structures343
- 14.1 Vessel Analysis345
- 14.2 Overview of Vessel Visualization350
- 14.3 Explicit Surface Reconstruction352
- 14.4 Modeling Tree Structures with Implicit Surfaces357
- 14.5 Visualization with Convolution Surfaces361
- 14.6 Validation and Evaluation365
- 14.7 Examples371
- 14.8 Exploration of Vasculature372
- 14.9 Vessel Visualization for Diagnosis374
- 14.10 Summary377
- Chapter 15. Virtual Endoscopy381
- 15.1 Application Scenarios for Virtual Endoscopy382
- 15.2 Technical Issues384
- 15.3 Virtual Colonoscopy387
- 15.4 Virtual Bronchoscopy389
- 15.5 Virtual Neuroendoscopy391
- 15.6 Virtual Angioscopy397
- 15.7 Summary400
- Chapter 16. Image-Guided Surgery and Virtual Reality403
- 16.1 Prerequisites for Intraoperative Visualization403
- 16.2 Image-Guided Surgery407
- 16.3 Virtual and Mixed Reality in the OR411
- 16.4 Summary416
- Chapter 17. Emphasis Techniques and Illustrative Rendering419
- 17.1 Illustrative Surface and Volume Rendering420
- 17.2 Combining Line, Surface, and Volume Visualization434
- 17.3 Visibility Analysis439
- 17.4 Local Emphasis Techniques440
- 17.5 Regional and Global Emphasis Techniques443
- 17.6 Dynamic Emphasis Techniques446
- 17.7 Synchronized Emphasis447
- 17.8 Classification of Emphasis Techniques449
- 17.9 Summary451
- Chapter 18. Exploration of MRI Diffusion Tensor Images455
- 18.1 Medical Background and Image Acquisition457
- 18.2 Image Analysis of DTI Data464
- 18.3 Quantitative Characterization of Diffusion Tensors467
- 18.4 Slice-based Visualizations of Tensor Data470
- 18.5 Visualization with Tensor Glyphs473
- 18.6 Direct Volume Rendering of Diffusion Tensor Fields477
- 18.7 Fiber Tract Modeling477
- 18.8 Exploration of Fiber Tracts Through Clustering486
- 18.9 Software Tools for the Exploration of DTI Data493
- 18.10 Summary493
- Part V: Application Areas and Case Studies497
- Chapter 19. Image Analysis and Visualization for Liver Surgery Planning499
- 19.1 Medical Background500
- 19.2 Image Analysis for Liver Surgery Planning505
- 19.3 Risk Analysis for Oncologic Liver Surgery Planning508
- 19.4 Risk Analysis for Live Donor Liver Transplantation511
- 19.5 Simulation and Visualization for Planning of Thermoablations514
- 19.6 Software Assistants for Liver Surgery Planning516
- 19.7 Clinical Application519
- 19.8 Planning Pancreatic and Renal Surgery520
- 19.9 Summary521
- Chapter 20. Visualization for Medical Education525
- 20.1 Datasets and Knowledge Representation for Medical Education526
- 20.2 Labeling Medical Visualizations530
- 20.3 Animating Medical Visualizations541
- 20.4 Basics of Computer-based Training545
- 20.5 Anatomy Education546
- 20.6 Surgery Education and Simulation552
- 20.7 Summary566
- Chapter 21. Outlook569
- 21.1 Integrating Simulation and Visualization570
- 21.2 Integrated Visualization of Preoperative and Intraoperative Visualization571
- 21.3 Integrated Visualization of Morphologic and Functional Image Data572
- 21.4 Model-based Visualization572
- Appendix A. Systems for Visualization in MedicineA1
- A.1 Concepts of General Purpose Visualization SoftwareA2
- A.2 Toolkits and Other Software Systems for Visualization in MedicineA3
- A.3 SummaryA13
- Bibliography589
- Index641
Visualization in Medicine is the first book on visualization and its application to problems in medical diagnosis, education, and treatment. The book describes the algorithms, the applications and their validation (how reliable are the results?), and the clinical evaluation of the applications (are the techniques useful?). It discusses visualization techniques from research literature as well as the compromises required to solve practical clinical problems.
The book covers image acquisition, image analysis, and interaction techniques designed to explore and analyze the data. The final chapter shows how visualization is used for planning liver surgery, one of the most demanding surgical disciplines. The book is based on several years of the authors' teaching and research experience. Both authors have initiated and lead a variety of interdisciplinary projects involving computer scientists and medical doctors, primarily radiologists and surgeons.
* A core field of visualization and graphics missing a dedicated book until now
* Written by pioneers in the field and illustrated in full color
* Covers theory as well as practice
The book covers image acquisition, image analysis, and interaction techniques designed to explore and analyze the data. The final chapter shows how visualization is used for planning liver surgery, one of the most demanding surgical disciplines. The book is based on several years of the authors' teaching and research experience. Both authors have initiated and lead a variety of interdisciplinary projects involving computer scientists and medical doctors, primarily radiologists and surgeons.
* A core field of visualization and graphics missing a dedicated book until now
* Written by pioneers in the field and illustrated in full color
* Covers theory as well as practice