Visual computing for medicine: theory, algorithms, and applications
Gespeichert in:
Hauptverfasser: | , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Amsterdam [u.a.]
Elsevier [u.a.]
2014
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Ausgabe: | 2. ed. |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
Beschreibung: | 1. Aufl. u.d.T.: Preim, Bernhard: Visualization in medicine |
Beschreibung: | XXIII, , 812 S. Illustrationen, Diagramme |
ISBN: | 9780124158733 |
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Datensatz im Suchindex
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adam_text | VISUAL COMPUTING FOR MEDICINE
/ PREIM, BERNHARD [AUTHOR.]
: 2014
TABLE OF CONTENTS / INHALTSVERZEICHNIS
ACQUISITION OF MEDICAL IMAGE DATA
AN INTRODUCTION TO MEDICAL VISUALIZATION IN CLINICAL PRACTICE
IMAGE ANALYSIS FOR MEDICAL VISUALIZATION
HUMAN-COMPUTER INTERACTION FOR MEDICAL VISUALIZATION
SURFACE RENDERING
DIRECT VOLUME VISUALIZATION
ADVANCED DIRECT VOLUME VISUALIZATION
VOLUME INTERACTION
LABELING AND MEASUREMENTS IN MEDICAL VISUALIZATION
VISUALIZATION OF VASCULAR STRUCTURES
ILLUSTRATIVE MEDICAL VISUALIZATION
VIRTUAL ENDOSCOPY
PROJECTIONS AND REFORMATIONS
VISUALIZATION OF BRAIN CONNECTIVITY
VISUAL EXPLORATION AND ANALYSIS OF PERFUSION DATA
COMPUTER-ASSISTED SURGERY
IMAGE-GUIDED SURGERY AND AUGMENTED REALITY
VISUAL EXPLORATION OF SIMULATED AND MEASURED FLOW DATA
VISUAL COMPUTING FOR ENT SURGERY PLANNING
VISUALIZATION FOR MEDICAL EDUCATION
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
Titel: Visual computing for medicine
Autor: Preim, Bernhard
Jahr: 2014
Contents
ACKNOWLEDGMENTS xvii
FOREWORD TO THE SECOND EDITION xix
PREFACE TO THE SECOND EDITION xxi
AUTHOR BIOGRAPHY xxiii
01 INTRODUCTION 1
1.1 Visualization in Medicine as a Specialty of Scientific Visualization 1
1.2 Computerized Medical Imaging 3
1.3 2D and 3D Visualizations 2
1.4 Further Information ^
1.5 Organization 9
PART I ACQUISITION,ANALYSIS,AND INTERPRETATION
OF MEDICAL VOLUME DATA
02 ACQUISITION OF MEDICAL IMAGE DATA 15
2.1 Introduction ^
2.2 Medical Image Data ^
2.3 Data Artifacts and Signal Processing *9
2.3.1 Sampling Theorem ^9
2.3.2 Undersampling and Aliasing 2 ^
2.3.3 Interpolation Artifacts 22
2.4 X-Ray Imaging 24
2.4.1 Angiography 2^
2.4.2 Rotational X-Ray 26
2.4.3 Discussion 2^
2.4.4 Current and Future Developments of X-Ray Imaging 28
2.5 Computed Tomography 29
2.5.1 Computed Tomography Compared to X-Ray Imaging 30
2.5.2 Principle of CT Data Generation 30
v
vi
2.5.3 Standardization with Hounsfield Units
2.5.4 Parameters of CT Scanning
2.5.5 Artifacts in CT Image Acquisition
2.5.6 Current and Future Developments of CT Scanners
2.5.7 Discussion
Magnetic Resonance Imaging
2.6.1 Principles of MRI
2.6.2 Parameters of MR Scanning
2.6.3 Artifacts in MRI Data
2.6.4 Functional MRI
2.6.5 Ultra-High-Field MRI
2.6.6 Diffusion Tensor Imaging
2.6.7 Discussion
Ultrasound
Imaging in Nuclear Medicine
2.8.1 Positron Emission Tomography—PET
2.8.2 Hybrid PET/CT and PET/MRI Scanners
2.8.3 Single Photon Emission Computed Tomography—
Intraoperative Imaging
2.9.1 CT- and MR-Guided Interventions
2.9.2 Fluoroscopy
2.9.3 Intraoperative Ultrasound
2.9.4 Intraoperative MRI
2.10 Summary
03 AN INTRODUCTION TO MEDICAL VISUALIZATION
IN CLINICAL PRACTICE
3.1 Introduction
3.2 Diagnostic Accuracy
3.3 Visual Perception
3.3.1 Gray Value Perception
3.3.2 Color Spaces, Color Scales, and Color Perception
3.3.3 Visual Perception and Attention in the Diagnosis Of
Medical Volume Data
3.4 Storage of Medical Image Data
3.4.1 Scope of Dicom
3.4.2 Structure of Dicom Data
3.5 Conventional Film-Based Diagnosis
3.5.1 Cooperation of Radiologists and Radiology Technicians
3.5.2 Tasks in Conventional Film-Based Diagnosis
3.6 Soft-Copy Reading
3.6.1 Digital Radiology Departments
3-6.2 Tasks in Soft-Copy Reading
CONTENTS
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CONTENTS
vii
3.6.3 Digital Hanging Protocol 92
3.6.4 Computer-Aided Detection 93
3.6.5 Diagnosis with 3D Visualizations 97
3.6.6 Guidelines for Soft-Copy Reading 100
3.7 Medical Visualization in Nuclear Medicine 101
3.8 Medical Image Data in Radiation Treatment Planning 102
3.8.1 Conformant and Intensity-Modulated Radiation Treatment 10 5
3.8.2 Brachy therapy 107
3.9 Medical Team Meetings 10 7
3.10 Concluding Remarks 109
04 IMAGE ANALYSIS FOR MEDICAL VISUALIZATION 111
4.1 Introduction 111
4.2 Preprocessing and Filtering 112
4.2.1 ROI Selection 113
4.2.2 Resampling 113
4.2.3 Histogram and Histogram Transformation 114
4.2.4 General Noise Reduction Techniques 116
4.2.5 Inhomogeneity Correction 12 2
4.2.6 Gradient Filtering 123
4.3 An Introduction to Image Segmentation 124
4.3.1 Requirements 125
4.3.2 Manual Segmentation 125
4.3.3 Threshold-Based Segmentation 126
4.3.4 Region Growing 128
4.3.5 Watershed Segmentation 12 9
4.4 Graph-Based Segmentation Techniques 132
4.4.1 Livewire Segmentation 132
4.4.2 Contour-Based Segmentation with Variational Interpolation 136
4.4.3 Graph Cuts 137
4.4.4 Random Walker Segmentation 138
4.5 Advanced and Model-Based Segmentation Methods 139
4.5.1 Active Contour Models 140
4.5.2 Level Sets and Fast Marching Methods 141
4.5.3 Statistical Shape Models 143
4.5.4 Active Appearance Models 146
4.5.5 Incorporating Model Assumptions in Region Growing Segmentation 148
4.5.6 Application:Tumor Segmentation 148
4.5.7 Verification and Representation of Segmentation Results 152
4.6 Interaction for Segmentation 153
4.6.1 General Techniques for Correcting Pre-Segmentations 15 5
4.6.2 Mesh-Based Correction of Segmentation Results 155
4.6.3 Interactive Morphological Image Processing 159
4.6.4 Interaction Techniques for Semi-Automatic Segmental
4.7 Validation of Segmentation Methods
4.7.1 Phantom Studies Versus Clinical Data
4.7.2 Validation Metrics
4.7.3 Validation with Public Databases
4.8 Registration and Fusion of Medical Image Data
4.8.1 Transformation
4.8.2 Fitting
4.8.3 Model-Based Registration
4.8.4 Efficient Registration
4.8.5 Visualization
4.9 Summary
HUMAN-COMPUTER INTERACTION FOR
MEDICAL VISUALIZATION
5.1 Introduction
5.2 User and Task Analysis
5.2.1 Task Analysis Methods
5.2.2 What has to be Analyzed?
5.2.3 Representations of Task Analysis
5.2.4 Understanding the User
5.2.5 Case Study: Task Analysis for Medical Team Meetings
5.3 Metaphors
5.4 Prototyping
5.5 User Interface Principles and User Experience
5.5.1 General User Interface Principles
5.5.2 User Interface Principles for Medical Applications
5.5.3 User Experience
5.6 3D Interaction Techniques
5.6.1 Selection Tasks
5.6.2 3D Rotation
5.6.3 Object Placement
5.6.4 Navigation
5.7 Input Devices
5.7.1 6 Dof Input Devices
5.7.2 Tactile Input Devices
5.8 HCI in the Operating Room
5.9 Mobile Computing
5.10 Evaluation
5.10.1 Formative and Summative Evaluations
5.10.2 Inspection-Based and Empirical Evaluations
5.10.3 Evaluation of Interactive Segmentation Techniques
5.10.4 Post Market Clinical Follow Up
5.11 Conclusion
CONTENTS
ix
PART II VISUALIZATION AND EXPLORATION OF MEDICAL VOLUME DATA
06 SURFACE RENDERING 229
6.1 Introduction 229
6.2 Reconstruction of Surfaces from Contours 230
6.2.1 Topological Problems 230
6.2.2 Neighborhood Relations in Surface Meshes 231
6.2.3 Representation of Surface Meshes 232
6.3 Marching Cubes 233
6.3.1 Marching Squares 234
6.3.2 Basic Algorithm 234
6.3.3 Discussion 237
6.3.4 Advanced Surface Extraction Methods 240
6.3.5 Hardware-Accelerated Isosurface Extraction 241
6.4 Surface Rendering of Unsegmented Volume Data 241
6.4.1 Preprocessing Volume Data for Visualization 242
6.4.2 Selection of Isovalues 244
6.4.3 Multiple and Nested Isosurfaces 245
6.4.4 Isosurface Topology Simplification 246
6.5 Surface Rendering of Segmented Volume Data 247
6.5.1 Preprocessing 248
6.5.2 Basic Mesh Smoothing 250
6.5.3 Interactive Real-Time Mesh Smoothing 254
6.5.4 Evaluation of Smoothing Approaches 257
6.6 Advanced Mesh Smoothing 258
6.6.1 Constrained Mesh Smoothing 258
6.6.2 Context-Aware Smoothing 259
6.6.3 Extracting Surfaces from Label Volumes 261
6.6.4 Evaluation of Advanced Mesh Smoothing 262
6.7 Mesh Simplification and Web-Based Surface Rendering 262
6.7.1 Mesh Simplification 263
6.7.2 Web-Based Surgical Planning 264
6.7.3 Web-Based Medical Education 265
6.8 Concluding Remarks 266
07 DIRECT VOLUME VISUALIZATION 269
7.1 Theoretical Models 269
7.1.1 Emission 270
7.1.2 Absorption 271
7.1.3 Volume Rendering Equation 2 71
7.2 The Volume Rendering Pipeline 273
7.2.1 Preclassified Volume Rendering Pipeline 274
7.3 Compositing 275
7.3.1 Compositing Variations: Pseudo X-Ray, MIP, CVP, and MIDA 277
X
7.3.2 Thin Slab Volume Rendering
7.3.3 Pre-IntegratedVolume Rendering
7.4 Volume Raycasting
7.5 Efficient Volume Rendering
7.6 Direct Volume Rendering on the GPU
7.7 Summary
08 ADVANCED DIRECT VOLUME VISUALIZATION
8.1 Introduction
8.2 Volumetric Illumination
8.2.1 Volumetric Illumination Model
8.2.2 Algorithm Classification
8.2.3 Local Region-Based Techniques
8.2.4 Slice-Based Techniques
8.2.5 Light Space-Based Techniques
8.2.6 Lattice-Based Techniques
8.2.7 Basis Function-Based Techniques
8.2.8 Ray tracing-Based Techniques
8.2.9 Perceptual Impact
8.2.10 Technical Considerations
8.3 Artificial Depth Enhancements
8.3.1 Color-Coding
8.3.2 Halos
8.3.3 Depth of Field
8.4 Concluding Remarks
09 VOLUME INTERACTION
9.1 Introduction
9.2 One-Dimensional Transfer Functions
9.2.1 Unassisted Techniques
9.2.2 Data-Driven Transfer Functions
9.2.3 Image-Driven Transfer Functions
9.3 Multidimensional Transfer Functions
9.3.1 Histograms for 2D Transfer Functions
9.3.2 2D Component Functions
9.3.3 Representation of 2D Transfer Functions
9.3.4 Size-Based Transfer Functions
9.4 Gradient-Based and LH-BasedTransfer Functions
9.4.1 Gradient-Based Transfer Functions
9.4.2 Gradient Estimation and Storage
9.4.3 User Interfaces for Gradient-Based Transfer Functions
9.4.4 2D Transfer Functions Based on LH Histograms
9.5 Local and Distance-Based Transfer Functions
9.5.1 Distance-Based Transfer Functions
CONTENTS
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CONTENTS
xi
9.5.2 Local Transfer Functions 352
9.6 Advanced Picking 353
9.6.1 Contextual Picking 354
9.6.2 Visibility-Based Picking 355
9.7 Clipping 356
9.8 Virtual Resection 358
9.8.1 Virtual Resections by Drawing on Slices 359
9.8.2 Virtual Resection with a Deformable Cutting Plane 359
9.9 Cutting Medical Volume Data 365
9.9.1 High-Quality Representation of Cut Surfaces 366
9.9.2 Virtual Resection and Surgery Simulation 366
9.10 Summary 366
1D LABELING AND MEASUREMENTS IN MEDICAL VISUALIZATION 369
10.1 Introduction 369
10.2 General Design Issues 3 70
10.3 Interactive Measurement of Distances and Volumes 3 71
10.3.1 Interactive Distance Measurement 371
10.3.2 Estimation of Quantitative Values 373
1 0.4 Automatic Distance Measures 376
10.4.1 Bounding Volumes and Spatial Trees for Distance Computation 376
10.4.2 Efficient and Flexible Distance Computation 378
10.4.3 Clinical Examples 381
10.4.4 Measuring the Extents of Objects 381
10.5 Angular Measurements 384
10.5.1 Measurement of Angles Between Elongated Objects 384
10.5.2 Medical Applications 385
10.6 Measurements in Virtual Reality 387
10.7 Labeling 2D and 3D Medical Visualizations 387
10.7.1 Internal Labeling of 3D Medical Surface Models 390
10.7.2 External Labeling 391
10.7.3 Labeling Slice-Based Visualizations 394
10.8 Summary 397
PART III ADVANCED MEDICAL VISUALIZATION TECHNIQUES
11 VISUALIZATION OF VASCULAR STRUCTURES 401
11.1 Introduction 401
11.2 Enhancing Vascular Structures 402
11.2.1 Emphasis of Elongated Structures 402
11.2.2 Bone Removal 403
11.3 Projection-Based Visualization 405
11.3.1 Maximum Intensity and Closest Vessel Projection 405
11.3.2 Maximum Intensity Difference Accumulation 407
XII
CONTENTS
11.3.3 Curved Planar Reformation 408
11.4 Vessel Analysis 41 ^
1 1.4.1 Vessel Segmentation 4 1 ^
11.4.2 Skeletonization and Graph Analysis 4,4
11.4.3 Diameter Estimation 418
11.5 Model-Based Surface Visualization 41 9
11.5.1 Reconstruction with Cylinders and Truncated Cones 420
11.5.2 Visualization with Parametric and Subdivision Surfaces 424
11.5.3 Implicit Reconstruction of Vascular Trees 425
11.6 Model-Free Surface Visualization 43 2
11.6.1 Smoothing Surface Visualizations 432
11.6.2 Visualization with MPU Implicits 432
11.6.3 Implicit Reconstruction with Sweeping 436
11.7 Vessel Visualization for Diagnosis 438
11.7.1 Diagnosis of Cerebral Aneurysms and Arterio-Venous Malformations 440
11.7.2 Diagnosis of the Coronary Heart Disease 445
11.7.3 Multiple Coordinated Views 448
11.8 Summary 448
12 ILLUSTRATIVE MEDICAL VISUALIZATION 451
12.1 Introduction 451
12.2 Medical Applications 453
12.3 Curvature Approximation 454
12.3.1 Curvature-Related Measures 455
12.3.2 Curvature Estimation for Illustrative Visualization 456
12.4 An Introduction to Feature Lines 457
12.4.1 An Overview of Feature Lines 453
1 2.4.2 General Aspects of Feature Line Rendering 459
12.5 Geometry-Dependent Feature Lines 462
12.5.1 Silhouette Generation 462
12.5.2 Crease Lines 467
12.5.3 Ridge and Valley Lines 46g
12.5.4 Suggestive Contours 4 7 j
12.5.5 Apparent Ridges 472
12.5.6 Streamline-Based Illustrative Rendering - 474
12.6 Light-Dependent Feature Lines 476
12.6.1 Laplacian Lines
12.6.2 Photic Extremum Lines 477
12.6.3 Highlight Lines „
12.6.4 Discussion
12.7 Stippling ^
1 2.7.1 Essential Parameters of Stippling 482
12.7.2 Frame-Coherent Stippling
12.8 Hatching * 483
485
12.8.1 Curvature-Guided Hatching 4g?
CONTENTS
xiii
12.8.2 Model-Based Hatching of Muscles and Vascular Structures 48 8
12.8.3 Combination of Curvature and Preferential Direction 490
12.8.4 Hatching Volume Models 491
12.9 Illustrative Shading 492
12.9.1 Shading in Medical Textbooks 493
12.9.2 Realization of the Extended Shading 494
12.9.3 Illustrative Visualization of Vascular Trees 497
12.10 Smart Visibility 500
12.10.1 Cutaways 501
12.10.2 Ghosted Views 505
12.11 Conclusion 507
13 VIRTUAL ENDOSCOPY 509
13.1 Introduction 509
13.2 Medical and Technical Background 510
13.3 Preprocessing 513
13.3.1 Preprocessing Workflow 513
13.3.2 Path Planning 513
13.4 Rendering for Virtual Endoscopy 515
13.4.1 Indirect Volume Rendering 515
13.4.2 Direct Volume Rendering 517
13.4.3 Hybrid Rendering 518
13.4.4 Advanced Rendering 518
13.4.5 Geometry Culling 518
13.5 User Interfaces for Virtual Endoscopy 521
13.5.1 Camera Control and Navigation 522
13.5.2 Views for Interactive Virtual Endoscopy 523
13.5.3 Graphical User Interface 524
13.5.4 Input Devices 524
13.6 Applications 525
13.6.1 Virtual Colonoscopy 525
13.6.2 Virtual Bronchoscopy 529
13.6.3 Virtual Angioscopy 531
13.6.4 Virtual Endoscopy for Minimally-Invasive Neurosurgery 533
13.7 Concluding Remarks 536
14 PROJECTIONS AND REFORMATIONS (Online Chapter] 537
PART IV VISUALIZATION OF HIGH-DIMENSIONAL MEDICAL IMAGE DATA
15 VISUALIZATION OF BRAIN CONNECTIVITY 541
15.1 Introduction 541
15.2 Acquisition of Connectivity Data 543
CONTENTS
15.2.1 EEG and MEG
15.2.2 Magnetic Resonance Imaging
15.2.3 Diffusion MRI
15.2.4 Functional MRI
15.3 Visualization of Structural Connectivity
543
543
545
547
547
15.3.1
Scalar Reduction
5 54
15.4
15.3.2 Glyphs
15.3.3 Global Multifield 559
Visualization of Connectivity Matrices 579
15.4.1 Non-Spatial Methods 580
15.4.2 Spatial Methods 583
15.5 Summary 587
16 VISUAL EXPLORATION AND ANALYSIS OF PERFUSION DATA
(Online Chapter] 589
PART V TREATMENT PLANNING, GUIDANCE AND TRAINING
17 COMPUTER-ASSISTED SURGERY 593
17.1 Introduction 593
17.2 General Tasks 594
17.3 Visualization Techniques 595
17.3.1 Visual Representation 596
17.3.2 Interaction 598
17.3.3 Simulation 598
1 7.3.4 Quantitative Visualization 601
17.4 Guidance Approaches 607
17.4.1 Mental Model 608
17.4.2 Documentation 609
17.4.3 Image-Based Guidance 610
17.4.4 Mechanical Guidance 610
17.5 Application Areas ^12
17.5.1 Oral and Maxillofacial Surgery 612
17.5.2 Orthopedic Surgery 614
17.5.3 Neurosurgery 616
17.5.4 Hepatic Surgery ^21
17.6 Conclusions
18 IMAGE-GUIDED SURGERY AND AUGMENTED REALITY
18.1 Introduction
18.2 Image-Guided Surgery
I 8.2.1 Overview of IGS Applications
18.2.2 Medical Augmented Reality
623
625
625
627
627
628
CONTENTS xv
18.3 Registration 630
18.3.1 Tissue Deformation and Brain Shift 63 1
18.3.2 Fiducial-Based Registration 631
18.3.3 Point-Based Registration 633
18.4 Calibration and Tracking 634
18.4.1 Calibrating Instruments 634
18.4.2 Camera Calibration 637
18.4.3 Optical Tracking 639
18.4.4 Electro-Magnetic Tracking 640
18.4.5 Summary 641
18.5 Navigated Control 641
18.6 Display Modes 642
18.6.1 Brief History of Medical AR 643
18.6.2 Optical See-Through Displays 644
18.6.3 Video See-Through Displays 645
18.6.4 Augmented Microscope Displays 645
18.6.5 Augmented Reality Windows 646
18.6.6 Projection-Based Medical Augmented Reality 647
18.7 Visualization Techniques for Medical Augmented Reality 648
18.7.1 The Occlusion Problem of Augmented Reality 648
18.7.2 Depth Cues in Augmented Reality 649
18.7.3 Basic Visualization in AR 650
18.7.4 Smart Visibility in AR 651
18.7.5 Illustrative Visualization in AR 653
18.7.6 Interaction in the OR 654
18.7.7 Calibrated Augmented Reality Endoscope 657
18.8 Applications 657
18.8.1 Workflow Analysis for Medical Augmented Reality 657
18.8.2 Neurosurgery 659
18.8.3 Liver Surgery 659
18.8.4 Validation and Clinical Evaluation 661
18.9 Summary 661
19 VISUAL EXPLORATION OF SIMULATED AND MEASURED
FLOW DATA 665
19.1 Introduction 665
19.2 Basic Flow Visualization Techniques 666
19.2.1 Direct Flow Visualization Techniques 666
19.2.2 Feature-Based Flow Visualization Techniques 667
19.2.3 Texture-Based Flow Visualization 670
19.2.4 Geometry-Based Flow Visualization Methods 670
19.2.5 Partition-Based Flow Visualization Techniques 673
19.2.6 Evaluation of Flow Visualization Techniques 674
CONTENTS
19.3 From Medical Image Data to Simulation Models 6
19.3.1 Segmentation and Meshing for Simulation 6
19.3.2 Requirements for Surface Meshes 676
19.3.3 Generation of Surface Meshes 678
19.3.4 Generation of Volume Grids 680
19.4 Visual Exploration of Measured Cardiac Blood Flow 684
19.4.1 Medical Background 684
19.4.2 Image Acquisition 68 5
19.4.3 Preprocessing Cardiac Blood Flow Data 687
19.4.4 Quantitative Analysis 688
19.4.5 Visual Exploration 689
19.4.6 Illustrative Visualization Techniques 690
19.4.7 Uncertainty Visualization 69 1
19.5 Exploration of Simulated Cerebral Blood Flow 692
19.5.1 Blood Flow Simulations 693
19.5.2 Extraction of Landmarks 695
19.5.3 Anatomy-Guided Flow Exploration 697
19.5.4 Lens-Based Interaction 700
19.5.5 Visualization ofVasculature and Embedded Flow 701
19.5.6 Virtual Stenting 702
19.5.7 Software Assistant 704
19.5.8 Validation 706
19.5.9 Discussion 70(,
19.6 Biomedical Simulation and Modeling 707
19.6.1 Biomechanical Simulation in Orthopedics 707
19.6.2 Simulation and Visualization for Planning Radio-Frequency Ablation 709
19.7 Concluding Remarks 7J2
20 VISUAL COMPUTING FOR ENT SURGERY PLANNING (Online Chapter] 71 5
21 COMPUTER-ASSISTED MEDICAL EDUCATION (Online Chapter] 717
22 OUTLOOK (Online Chapter]
REFERENCES
721
INDEX
801
|
any_adam_object | 1 |
author | Preim, Bernhard 1969- Botha, Charl |
author_GND | (DE-588)120116774 (DE-588)1046413724 |
author_facet | Preim, Bernhard 1969- Botha, Charl |
author_role | aut aut |
author_sort | Preim, Bernhard 1969- |
author_variant | b p bp c b cb |
building | Verbundindex |
bvnumber | BV041737008 |
callnumber-first | R - Medicine |
callnumber-label | R857 |
callnumber-raw | R857.O6 |
callnumber-search | R857.O6 |
callnumber-sort | R 3857 O6 |
callnumber-subject | R - General Medicine |
classification_rvk | ST 640 |
ctrlnum | (OCoLC)862928964 (DE-599)BVBBV041737008 |
dewey-full | 616.07/54 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 616 - Diseases |
dewey-raw | 616.07/54 |
dewey-search | 616.07/54 |
dewey-sort | 3616.07 254 |
dewey-tens | 610 - Medicine and health |
discipline | Informatik Medizin |
edition | 2. ed. |
format | Book |
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id | DE-604.BV041737008 |
illustrated | Illustrated |
indexdate | 2024-07-10T01:04:07Z |
institution | BVB |
isbn | 9780124158733 |
language | English |
lccn | 013044209 |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027183680 |
oclc_num | 862928964 |
open_access_boolean | |
owner | DE-29T DE-92 DE-739 |
owner_facet | DE-29T DE-92 DE-739 |
physical | XXIII, , 812 S. Illustrationen, Diagramme |
publishDate | 2014 |
publishDateSearch | 2014 |
publishDateSort | 2014 |
publisher | Elsevier [u.a.] |
record_format | marc |
spelling | Preim, Bernhard 1969- Verfasser (DE-588)120116774 aut Visual computing for medicine theory, algorithms, and applications Bernhard Preim ; Charl Botha 2. ed. Amsterdam [u.a.] Elsevier [u.a.] 2014 XXIII, , 812 S. Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier 1. Aufl. u.d.T.: Preim, Bernhard: Visualization in medicine Medizintechnik, Verfahren, Systeme und Informationsverarbeitung (DE-588)1123820201 gnd rswk-swf Diagnostic Imaging Computer Graphics Image Processing, Computer-Assisted Surgery, Computer-Assisted User-Computer Interface Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Bildgebendes Verfahren (DE-588)4006617-4 gnd rswk-swf Bildgebendes Verfahren (DE-588)4006617-4 s Maschinelles Sehen (DE-588)4129594-8 s Medizintechnik, Verfahren, Systeme und Informationsverarbeitung (DE-588)1123820201 u DE-604 Botha, Charl Verfasser (DE-588)1046413724 aut LoC Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027183680&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027183680&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Preim, Bernhard 1969- Botha, Charl Visual computing for medicine theory, algorithms, and applications Medizintechnik, Verfahren, Systeme und Informationsverarbeitung (DE-588)1123820201 gnd Diagnostic Imaging Computer Graphics Image Processing, Computer-Assisted Surgery, Computer-Assisted User-Computer Interface Maschinelles Sehen (DE-588)4129594-8 gnd Bildgebendes Verfahren (DE-588)4006617-4 gnd |
subject_GND | (DE-588)1123820201 (DE-588)4129594-8 (DE-588)4006617-4 |
title | Visual computing for medicine theory, algorithms, and applications |
title_auth | Visual computing for medicine theory, algorithms, and applications |
title_exact_search | Visual computing for medicine theory, algorithms, and applications |
title_full | Visual computing for medicine theory, algorithms, and applications Bernhard Preim ; Charl Botha |
title_fullStr | Visual computing for medicine theory, algorithms, and applications Bernhard Preim ; Charl Botha |
title_full_unstemmed | Visual computing for medicine theory, algorithms, and applications Bernhard Preim ; Charl Botha |
title_short | Visual computing for medicine |
title_sort | visual computing for medicine theory algorithms and applications |
title_sub | theory, algorithms, and applications |
topic | Medizintechnik, Verfahren, Systeme und Informationsverarbeitung (DE-588)1123820201 gnd Diagnostic Imaging Computer Graphics Image Processing, Computer-Assisted Surgery, Computer-Assisted User-Computer Interface Maschinelles Sehen (DE-588)4129594-8 gnd Bildgebendes Verfahren (DE-588)4006617-4 gnd |
topic_facet | Medizintechnik, Verfahren, Systeme und Informationsverarbeitung Diagnostic Imaging Computer Graphics Image Processing, Computer-Assisted Surgery, Computer-Assisted User-Computer Interface Maschinelles Sehen Bildgebendes Verfahren |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027183680&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027183680&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT preimbernhard visualcomputingformedicinetheoryalgorithmsandapplications AT bothacharl visualcomputingformedicinetheoryalgorithmsandapplications |
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