Visualization in Medicine (eBook)

Front Cover 1
Visualization in Medicine 6
Copyright Page 7
Table of Contents 11
Foreword 21
Preface 22
Chapter 1. Introduction 26
1.1 Visualization in Medicine as a Specialty of Scientific Visualization 26
1.2 Computerized Medical Imaging 28
1.3 2D and 3D Visualizations 31
1.4 Organization 32
Part I: Acquisition, Analysis, and Interpretation of Medical Volume Data 36
Chapter 2. Medical Image Data and Visual Perception 38
2.1 Medical Image Data 38
2.2 Data Artifacts 42
2.3 Sensitivity and Specificity 51
2.4 Visual Perception 52
2.5 Summary 59
Chapter 3. Acquisition of Medical Image Data 60
3.1 X-ray Imaging 61
3.2 Computed Tomography 66
3.3 Magnetic Resonance Imaging 73
3.4 Ultrasound 82
3.5 Positron Emission Tomography (PET) 85
3.6 Single-Photon Emission Computed Tomography (SPECT) 86
3.7 Summary 88
Chapter 4. Medical Volume Data in Clinical Practice 90
4.1 Storage of Medical Image Data 90
4.2 Conventional Film-based Diagnosis 92
4.3 Soft-Copy Reading 94
4.4 Summary 105
Chapter 5. Image Analysis for Medical Visualization 108
5.1 Requirements 109
5.2 Preprocessing and Filtering 110
5.3 General Segmentation Approaches 120
5.4 Model-based Segmentation Methods 134
5.5 Interaction Techniques 141
5.6 Postprocessing of Segmentation Results 144
5.7 Skeletonization 147
5.8 Validation of Segmentation Methods 149
5.9 Registration and Fusion of Medical Image Data 151
5.10 Summary 156
Part II: Volume Visualization 160
Chapter 6. Fundamentals of Volume Visualization 162
6.1 The Volume Visualization Pipeline 162
6.2 Histograms and Volume Classification 162
6.3 Illumination in Scalar Volume Datasets 170
6.4 Summary 177
Chapter 7. Indirect Volume Visualization 180
7.1 Plane-Based Volume Rendering 180
7.2 Surface-Based Volume Rendering 181
7.3 Surface Postprocessing 198
7.4 Summary 205
Chapter 8. Direct Volume Visualization 208
8.1 Theoretical Models for Direct Volume Rendering 208
8.2 The Volume Rendering Pipeline 212
8.3 Compositing 214
8.4 Summary 220
Chapter 9. Algorithms for Direct Volume Visualization 222
9.1 Ray Casting 222
9.2 Shear Warp 228
9.3 Splatting 231
9.4 Texture-Mapping 237
9.5 Other Direct Volume Rendering Approaches 244
9.6 Direct Volume Rendering of Segmented Volume Data 246
9.7 Hybrid Volume Rendering 248
9.8 Validation of Volume Visualization Algorithms 253
9.9 Summary 260
Chapter 10. Exploration of Dynamic Medical Volume Data 262
10.1 Introduction 262
10.2 Medical Background 263
10.3 Basic Visualization Techniques 266
10.4 Data Processing 267
10.5 Advanced Visualization Techniques 269
10.6 Case Study: Tumor Perfusion 273
10.7 Case Study: Brain Perfusion 278
10.8 Summary 281
Part III: Exploration of Medical Volume Data 284
Chapter 11. Transfer Function Specification 286
11.1 Strategies for One-Dimensional Transfer Functions 287
11.2 Multidimensional Transfer Functions 295
11.3 Gradient-based Transfer Functions 300
11.4 Distance-based Transfer functions 305
11.5 Local and Spatialized Transfer Functions 311
11.6 Summary 313
Chapter 12. Clipping, Cutting, and Virtual Resection 316
12.1 Clipping 316
12.2 Virtual Resection 319
12.3 Virtual Resection with a Deformable Cutting Plane 322
12.4 Cutting Medical Volume Data 332
12.5 Summary 335
Chapter 13. Measurements in Medical Visualization 338
13.1 General Design Issues 340
13.2 3D Distance Measurements 342
13.3 Angular Measurements 346
13.4 Interactive Volume Measurements 348
13.5 Interactive Volume Measurements 349
13.6 Minimal Distance Computation 354
13.7 Further Automatic Measurements 361
13.8 Summary 362
Part IV: Advanced Visualization Techniques 366
Chapter 14. Visualization of Anatomic Tree Structures 368
14.1 Vessel Analysis 370
14.2 Overview of Vessel Visualization 375
14.3 Explicit Surface Reconstruction 377
14.4 Modeling Tree Structures with Implicit Surfaces 382
14.5 Visualization with Convolution Surfaces 386
14.6 Validation and Evaluation 390
14.7 Examples 396
14.8 Exploration of Vasculature 397
14.9 Vessel Visualization for Diagnosis 399
14.10 Summary 402
Chapter 15. Virtual Endoscopy 406
15.1 Application Scenarios for Virtual Endoscopy 407
15.2 Technical Issues 409
15.3 Virtual Colonoscopy 412
15.4 Virtual Bronchoscopy 414
15.5 Virtual Neuroendoscopy 416
15.6 Virtual Angioscopy 422
15.7 Summary 425
Chapter 16. Image-Guided Surgery and Virtual Reality 428
16.1 Prerequisites for Intraoperative Visualization 428
16.2 Image-Guided Surgery 432
16.3 Virtual and Mixed Reality in the OR 436
16.4 Summary 441
Chapter 17. Emphasis Techniques and Illustrative Rendering 444
17.1 Illustrative Surface and Volume Rendering 445
17.2 Combining Line, Surface, and Volume Visualization 459
17.3 Visibility Analysis 464
17.4 Local Emphasis Techniques 465
17.5 Regional and Global Emphasis Techniques 468
17.6 Dynamic Emphasis Techniques 471
17.7 Synchronized Emphasis 472
17.8 Classification of Emphasis Techniques 474
17.9 Summary 476
Chapter 18. Exploration of MRI Diffusion Tensor Images 480
18.1 Medical Background and Image Acquisition 482
18.2 Image Analysis of DTI Data 489
18.3 Quantitative Characterization of Diffusion Tensors 492
18.4 Slice-based Visualizations of Tensor Data 495
18.5 Visualization with Tensor Glyphs 498
18.6 Direct Volume Rendering of Diffusion Tensor Fields 502
18.7 Fiber Tract Modeling 502
18.8 Exploration of Fiber Tracts Through Clustering 511
18.9 Software Tools for the Exploration of DTI Data 518
18.10 Summary 518
Part V: Application Areas and Case Studies 522
Chapter 19. Image Analysis and Visualization for Liver Surgery Planning 524
19.1 Medical Background 525
19.2 Image Analysis for Liver Surgery Planning 530
19.3 Risk Analysis for Oncologic Liver Surgery Planning 533
19.4 Risk Analysis for Live Donor Liver Transplantation 536
19.5 Simulation and Visualization for Planning of Thermoablations 539
19.6 Software Assistants for Liver Surgery Planning 541
19.7 Clinical Application 544
19.8 Planning Pancreatic and Renal Surgery 545
19.9 Summary 546
Chapter 20. Visualization for Medical Education 550
20.1 Datasets and Knowledge Representation for Medical Education 551
20.2 Labeling Medical Visualizations 555
20.3 Animating Medical Visualizations 566
20.4 Basics of Computer-based Training 570
20.5 Anatomy Education 571
20.6 Surgery Education and Simulation 577
20.7 Summary 591
Chapter 21. Outlook 594
21.1 Integrating Simulation and Visualization 595
21.2 Integrated Visualization of Preoperative and Intraoperative Visualization 596
21.3 Integrated Visualization of Morphologic and Functional Image Data 597
21.4 Model-based Visualization 597
Appendix A. Systems for Visualization in Medicine 600
A.1 Concepts of General Purpose Visualization Software 601
A.2 Toolkits and Other Software Systems for Visualization in Medicine 602
A.3 Summary 612
Bibliography 614
Index 666