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E-grāmata: Visualization in Medicine: Theory, Algorithms, and Applications

(Professor of Visualization, Computer Science Department, Otto-von-Guericke-University of Magdeburg, Germany), (Visual Computing for Medicine Group, University of Tübingen, Germany)
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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
Foreword xix
Preface xxi
Introduction
1(10)
Visualization in Medicine
1(2)
Computerized Medical Imaging
3(3)
2D and 3D Visualizations
6(1)
Organization
7(4)
PART I ACQUSITION, ANALYSIS, AND INTERPRETATION
11(124)
Medical Image Data and Visual Perception
13(22)
Medical Image Data
13(4)
Data Artifacts
17(9)
Sampling Theorem
18(1)
Under Sampling and Aliasing
19(2)
Partial Volume Effect
21(1)
Interpolation Artifacts
22(3)
Signal Artifacts
25(1)
Sensitivity and Specificity
26(1)
Visual Perception
27(7)
Gray Value Perception
27(3)
Color Spaces, Color Scales, and Color Perception
30(4)
Summary
34(1)
Acquisition of Medical Image Data
35(30)
X-ray Imaging
36(5)
Angiography
39(1)
Rotational X-ray
39(2)
Discussion
41(1)
Computed Tomography
41(7)
Computed Tomography Compared with X-ray Imaging
41(1)
Principle of CT Data Generation
42(3)
Parameters of CT Scanning
45(2)
Standardization with Hounsfield units
47(1)
Magnetic Resonance Imaging
48(9)
Parameters of MRI Scanning
50(4)
Intraoperative MRI Data
54(1)
Functional MRI
54(1)
Diffusion Tensor Imaging
55(1)
Historic Remarks
56(1)
CT versus MRI Data
56(1)
Ultrasound
57(3)
Position Emission Tomography (PET)
60(1)
Single-Photon Emission Computed Tomography (SPECT)
61(2)
Summary
63(2)
Medical Volume Data in Clinical Practice
65(18)
Storage of Medical Image Data
65(2)
Scope of DICOM
65(1)
Structure of DICOM Data
66(1)
Conventional Film-based Diagnosis
67(2)
Cooperation of Radiologists and Radiology Technician
67(1)
Tasks in Conventional Film-based Diagnosis
68(1)
Soft-copy Reading
69(11)
Integration of Soft-copy Reading in Digital Radiology Departments
69(2)
Tasks in Soft-copy Reading
71(2)
Quantitative Image Analysis
73(3)
Digital Hanging Protocol
76(1)
Guidelines for Software Assistants to Support Soft-copy Reading
76(1)
Diagnosis with 3D Visualizations
77(3)
Summary
80(3)
Image Analysis for Medical Visualization
83(52)
Requirements
84(1)
Preprocessing and Filtering
85(10)
ROI Selection
85(1)
Resampling
86(1)
Histogram and Histogram Equalization
87(1)
General Noise Reduction Techniques
88(5)
Inhomogeneity Correction
93(1)
Gradient Filtering
93(1)
Enhancement of Relevant Structures
94(1)
General Segmentation Approaches
95(14)
Manual Segmentation
96(1)
Threshold-based Segmentation
96(2)
Region Growing
98(2)
Watershed Segmentation
100(4)
Live Wire Segmentation
104(5)
Model-based Segmentation Methods
109(7)
Active Contour Models
109(2)
Level Sets and Fast Marching Methods
111(1)
Active Shape Models
111(3)
Active Appearance Models
114(1)
Incorporating Model Assumptions in Region-Growing Segmentation
115(1)
Interaction Techniques
116(3)
Interaction Techniques for Region Growing
117(1)
Interaction Techniques for Watershed Segmentation
118(1)
Interaction Techniques for LiveWire
118(1)
Postprocessing of Segmentation Results
119(3)
Morphological Image Analysis
119(1)
Smoothing Segmentation Results for Visualization
120(2)
Skeletonization
122(2)
Validation of Segmentation Methods
124(2)
Phantom studies versus Clinical Data
125(1)
Validation Metrics
125(1)
Discussion
126(1)
Registration and Fusion of Medical Image Data
126(5)
Summary
131(4)
PART II VOLUME VISUALIZATION
135(124)
Fundamentals of Volume Visualization
137(18)
The Volume Visualization Pipeline
137(1)
Histograms and Volume Classification
137(8)
Histograms
139(3)
Transfer Function Specification
142(3)
Selection of Isovalues
145(1)
Illumination in Scalar Volume Datasets
145(7)
Phong's Illumination Model
146(2)
Approximation of Normal Vectors
148(4)
Summary
152(3)
Indirect Volume Visualization
155(28)
Plane-based Volume Rendering
155(1)
Surface-based Volume Rendering
156(17)
Contour Tracing
158(1)
Cuberille Voxel Representation
158(1)
Polygonal Isosurface Extraction
159(9)
Other Isosurface Extraction Algorithms
168(1)
Data Structures for Accelerating Isosurface Extraction
169(4)
Surface Postprocessing
173(7)
Geometry Culling
173(2)
Mesh Reduction
175(1)
Mesh Smoothing
176(3)
Voxelization
179(1)
Summary
180(3)
Direct Volume Visualization
183(14)
Theoretical Models for Direct Volume Rendering
183(4)
Emission
184(1)
Absorption
184(1)
Volume Rendering Equation
185(2)
The Volume Rendering Pipeline
187(2)
Compositing
189(6)
Compositing Variations: Pseudo X-ray, MIP, and CVP
190(3)
Thin Slab Volume Rendering
193(1)
Pre-Integrated Volume Rendering
194(1)
Summary
195(2)
Algorithms for Direct Volume Visualization
197(40)
Ray Casting
197(6)
Quality
199(1)
Acceleration Methods
200(3)
Shear Warp
203(3)
Quality
205(1)
Splatting
206(6)
Quality
208(2)
Acceleration Methods
210(2)
Texture-Mapping
212(7)
Quality
215(3)
Dataset Management
218(1)
Other Direct Volume Rendering Approaches
219(2)
Shell Rendering
220(1)
Direct Volume Rendering of Segmented Volume Data
221(2)
Hybrid Volume Rendering
223(5)
Validation of Volume Visualization Algorithms
228(7)
Validation Criteria
229(1)
Geometric Models for Validation
230(2)
Image and Datalevel Comparisons
232(1)
Presentation of Results
232(3)
Summary
235(2)
Exploration of Dynamic Medical Volume Data
237(22)
Introduction
237(1)
Medical Background
238(3)
Basic Visualization Techniques
241(1)
Data Processing
242(2)
Advanced Visualization Techniques
244(4)
Multiparameter Visualization
245(3)
Integrating Dynamic Information and Morphology
248(1)
Case Study: Tumor Perfusion
248(5)
Imaging
250(1)
Computer Support
250(1)
Visualization Techniques
251(2)
Case Study: Brain Perfusion
253(3)
Imaging
254(1)
Computer Support
255(1)
Visualization Techniques
255(1)
Summary
256(3)
PART III EXPLORATION OF MEDICAL VOLUME DATA
259(82)
Transfer Function Specification
261(30)
Strategies for One-dimensional Transfer Functions
262(8)
Data-Driven TF Specification
263(3)
Employing Reference Transfer Functions
266(1)
Image-Driven TF Specification
267(3)
Multidimensional Transfer Functions
270(5)
Histograms for 2D TF Specification
271(1)
2D Component Functions
272(2)
Representation of 2D Transfer Functions
274(1)
Gradient-based Transfer Functions
275(5)
Gradient Estimation and Storage
275(1)
User Interfaces for Gradient-based Transfer Functions
276(4)
Distance-based transfer functions
280(6)
Distance Calculation and Storage
281(1)
Applications
282(3)
Discussion
285(1)
Local and Spatialized Transfer Functions
286(2)
Summary
288(3)
Clipping, Cutting, and Virtual Resection
291(22)
Clipping
291(3)
Selective Clipping
293(1)
Box Clipping
294(1)
Virtual Resection
294(3)
Specification of Virtual Resections by Erasing
296(1)
Specification of Virtual Resections by Drawing on Slices
296(1)
Virtual Resection with a Deformable Cutting Plane
297(10)
Defining Cutting Plane Boundaries
298(1)
Generation of the Initial Cutting Plane
298(4)
Modification of Virtual Resections
302(1)
Discussion
303(2)
Efficient Visualization of Virtual Resections
305(1)
Visualization Parameters
306(1)
Evaluation
306(1)
Combination of Resection Proposals and Virtual Resection
307(1)
Cutting Medical Volume Data
307(3)
High-quality Representation of Cut Surfaces
308(2)
Virtual Resection and Surgery Simulation
310(1)
Summary
310(3)
Measurements in Medical Visualization
313(28)
General Design Issues
315(2)
Usability
315(2)
Accuracy and Uncertainty
317(1)
3D Distance Measurements
317(4)
Distance Lines
317(2)
Interactive Rulers
319(1)
Path Measurement
320(1)
Angular Measurements
321(2)
Interactive Volume Measurements
323(1)
Interactive Volume Measurements
324(5)
Volume Selection
324(3)
Volume Approximation
327(1)
Validation
328(1)
Minimal Distance Computation
329(7)
Distance Calculation in Robotics and Medical Visualization
330(1)
Minimal Distance Computation based on Bounding Spheres
331(5)
Further Automatic Measurements
336(1)
Measuring the Extents of Objects
336(1)
Measurement of Angles between Elongated Objects
337(1)
Summary
337(4)
PART IV ADVANCED VISUALIZATION TECHNIQUES
341(156)
Visualization of Anatomic Tree Structures
343(38)
Vessel Analysis
345(5)
Preprocessing to Enhance Vessel-like Structures
345(1)
Vessel Segmentation
346(1)
Skeletonization
346(4)
Overview of Vessel Visualization
350(2)
Reconstruction of Vessels for Visualization
351(1)
Reconstruction of Vessels for Interaction
352(1)
Explicit and Implicit Surface Reconstruction
352(1)
Explicit Surface Reconstruction
352(5)
Visualization with Parametric Surfaces
353(1)
Visualization with Truncated Cones
353(2)
Visualization with Subdivision Surfaces
355(2)
Modeling Tree Structures with Implicit Surfaces
357(4)
Introduction
358(1)
Implicit Surfaces: a Brief Introduction
358(1)
Convolution Surfaces
358(2)
Blending
360(1)
Visualization with Convolution Surfaces
361(4)
Filter Modification
361(1)
Computational Complexity
362(2)
Construction of a Geometric Model
364(1)
Validation and Evaluation
365(6)
Qualitative Validation
365(1)
Quantitative Validation
366(3)
Determination of the Width Coefficient
369(1)
Evaluation
370(1)
Visualization of the Error
370(1)
Examples
371(1)
Exploration of Vasculature
372(2)
Vessel Visualization for Diagnosis
374(3)
Summary
377(4)
Virtual Endoscopy
381(22)
Application Scenarios for Virtual Endoscopy
382(2)
Technical Issues
384(3)
Rendering for Virtual Endoscopy
384(1)
Navigating through Body Cavities
385(2)
User Interface
387(1)
Virtual Colonoscopy
387(2)
Virtual Bronchoscopy
389(2)
Virtual Neuroendoscopy
391(6)
Cerebral Ventricular System
391(3)
Multimodal Visualization for Neuroendoscopic Interventions
394(1)
Minimally Invasive Surgery of the Pituitary Gland
395(2)
Virtual Angioscopy
397(3)
Angioscopy of Cerebral Blood Vessels
397(2)
Angioscopy of Coronary Blood Vessels
399(1)
Summary
400(3)
Image-Guided Surgery and Virtual Reality
403(16)
Prerequisites for Intraoperative Visualization
403(4)
Tissue Deformation and Brain Shift
404(1)
Registration
405(2)
Image-Guided Surgery
407(4)
Tracking Systems
407(2)
Navigating Instruments in the OR
409(2)
Virtual and Mixed Reality in the OR
411(5)
The Occlusion Problem of Mixed Reality
412(1)
Alignment of the Mixed Reality Camera
413(1)
Interaction in the OR
414(2)
Summary
416(3)
Emphasis Techniques and Illustrative Rendering
419(36)
Illustrative Surface and Volume Rendering
420(14)
Emphasis and Illustrative Rendering
422(1)
Silhouette and Feature Lines from Polygonal Models
423(3)
Hatching Surface Models
426(1)
Illustrative Rendering of Medical Volume Data
427(2)
Hatching Volume Models
429(1)
Illustrative Shading Styles
430(3)
Style Specification for Illustrative Volume Rendering
433(1)
Combining Line, Surface, and Volume Visualization
434(5)
Hybrid Rendering with Object-based Methods
434(1)
Emphasis with Hybrid Visualizations
435(4)
Visibility Analysis
439(1)
Local Emphasis Techniques
440(3)
Emphasis Using Color
440(1)
Focus-and-Context-Views
440(1)
Emphasis with Arrows
441(1)
Emphasis with Shadow Volumes
442(1)
Regional and Global Emphasis Techniques
443(3)
Cutaway and Ghost Views
443(2)
Defining Contrasts for Emphasis
445(1)
Dynamic Emphasis Techniques
446(1)
Synchronized Emphasis
447(2)
Slice Selection
447(1)
Emphasis in 2D Slices
448(1)
Range Visualization
448(1)
Classification of Emphasis Techniques
449(2)
Summary
451(4)
Exploration of MRI Diffusion Tensor Images
455(42)
Medical Background And Image Acquisition
457(7)
Neuroanatomy
457(1)
Image Acquisition
458(5)
Clinical Applications
463(1)
Image Analysis of DTI Data
464(3)
Interpolation of DTI Data
465(1)
Filtering DTI Data
466(1)
Discussion
467(1)
Quantitative Characterization of Diffusion Tensors
467(3)
Diffusivity Metrics
467(1)
Anisotropy Metrics
467(2)
Coherence Metrics
469(1)
Discussion
470(1)
Slice-based Visualizations of Tensor Data
470(3)
Visualization with Tensor Glyphs
473(4)
Ellipsoids as Tensor Glyphs
474(1)
Superquadric Tensor Glyphs
474(1)
Visualization of Tensor Glyphs
475(1)
Color Schemes for Tensor Glyphs
476(1)
Direct Volume Rendering of Diffusion Tensor Fields
477(1)
Fiber Tract Modeling
477(9)
Streamline Computation and Visualization
478(5)
Hyperstreamlines and Streamsurfaces
483(3)
Exploration of Fiber Tracts through Clustering
486(7)
Proximity Metrics for Clustering
487(1)
Clustering Algorithms
488(1)
Visualization and Quantification of Fiber Bundles
489(3)
Validation of Fiber Clustering
492(1)
Software Tools for the Exploration of DTI Data
493(1)
Summary
493(4)
PART V APPLICATION AREAS AND CASE STUDIES
497(78)
Image Analysis and Visualization for Liver Surgery Planning
499(26)
Medical Background
500(5)
Liver Anatomy
500(2)
Preoperative Imaging
502(1)
Liver Surgery
503(2)
Image Analysis for Liver Surgery Planning
505(3)
Risk Analysis for Oncologic Liver Surgery Planning
508(3)
Risk Analysis for Live Donor Liver Transplantation
511(3)
Grafts with or without Middle Hepatic Vein
511(1)
Case Study
512(2)
Simulation and Visualization for Planning
514(2)
Applicator Positioning
514(1)
Physical Effects of Thermoablation
515(1)
Software Assistants for Liver Sufgery Planning
516(3)
Image Analysis with Hepa Vision
517(1)
Surgery Planning with the Intervention Planner
517(2)
Clinical Application
519(1)
Planning Pancreatic and Renal Surgery
520(1)
Summary
521(4)
Visualization for Medical Education
525(44)
Datasets and Knowledge Representation
526(4)
Datasets for Medical Education
526(2)
Knowledge Representation
528(2)
Labeling Medical Visualizations
530(11)
Placement of External Labels
531(4)
Placement of Internal Labels
535(2)
Labeling Branching and Partially Visible Objects
537(2)
Labeling Cross-sectional Images
539(1)
Presentation Variables for Labeling
539(2)
Animating Medical Visualizations
541(4)
Script-based Specification of Animations
542(3)
Changing the Object Focus with Animations
545(1)
Basics of Computer-based Training
545(1)
Anatomy Education
546(6)
Voxel Man
547(1)
Digital Anatomist
547(2)
Anatomy Browser
549(1)
ZoomIllustrator and 3D Puzzle
549(3)
Surgery Education and Simulation
552(14)
CBT Systems for Studying Clinical Surgery
553(1)
Tasks and Concepts for Surgery Simulation
553(9)
CBT Systems for Studying Operative Techniques
562(4)
Summary
566(3)
Outlook
569(6)
Integrating Simulation and Visualization
570(1)
Integrated Visualization of Preoperative and Intraoperative Visualization
571(1)
Integrated Visualization of Morphologic and Functional Image Data
572(1)
Model-based Visualization
572(3)
Appendix 575(14)
Bibliography 589(52)
Index 641


Bernhard Preim was born in 1969 in Magdeburg, Germany. He received the diploma in computer science in 1994 (minor in mathematics) and a Ph.D. in 1998 for a thesis on interactive visualization for anatomy education from the Otto-von-Guericke University of Magdeburg. In 1999 he moved to Bremen where he joined the staff of MEVIS and directed the computer-aided planning in liver surgery” group. Since Mars 2003 he is full professor for Visualization at the computer science department at the Otto-von-Guericke-University of Magdeburg, heading a research group focussed on medical visualization. His research interests include vessel visualization, exploration of blood flow, visual analytics in public health, virtual reality in medical education and since recently narrative visualization. He authored Visualization in Medicine” (Co-author Dirk Bartz, 2007) and Visual Computing in Medicine” (Co-author: C. Botha, 2013). Bernhard Preim founded the working group Medical Visualization in the German Society for Computer Science and served as speaker from 2003-2012. He was president of the German Society for Computer- and Robot-Assisted Surgery (www.curac.org). He was Co-Chair and Co-Organizer of the first and second Eurographics Workshop on Visual Computing in Biology and Medicine (VCBM) in 2008 and 2010 and lead the steering committee of that workshop until 2019. He is the chair of the scientific advisory board of ICCAS (International Competence Center on Computer-Assisted Surgery Leipzig, since 2010). From 2011-2018 he was an associate editor of IEEE Transactions on Medical Imaging and and IEEE Transactions on Visualization and Graphics (2017-2022). Currently he serves in the editorial board of Computers & Graphics (since 2019). He was also regularly a Visiting Professor at the University of Bremen where he closely collaborates with Fraunhofer MEVIS (2003-2012) and was Visiting Professor at TU Vienna (2016). Dirk Barz was Professor for Computer-Aided Surgery at the U of Leipzig. He was also member of the executive committee of the IEEE Visualization and Graphics Technical Committee. He received the NDI Young Investigator Award for his work on virtual endoscopy and intra-operative navigation.