Visual computing for medicine [electronic resource] : theory, algorithms, and applications / by Bernhard Preim, Charl P. Botha.

By: Preim, Bernhard [author.]
Contributor(s): Botha, Charl [author.]
Material type: TextTextSeries: Morgan Kaufmann series in computer graphics: Publisher: Amsterdam : Morgan Kaufmann, 2014Edition: 2nd editionDescription: 1 online resourceContent type: text | still image Media type: computer Carrier type: online resourceISBN: 9780124158733 (electronic bk.); 0124158730 (electronic bk.); 9780124159792 (electronic bk.); 0124159796 (electronic bk.)Subject(s): Diagnostic imaging | Information visualization | HEALTH & FITNESS / Diseases / General | MEDICAL / Clinical Medicine | MEDICAL / Diseases | MEDICAL / Evidence-Based Medicine | MEDICAL / Internal Medicine | Diagnostic imaging | VisualizationGenre/Form: Electronic books. | Electronic books.Additional physical formats: Print version:: No titleDDC classification: 616.0754 LOC classification: RC78.7.D53Online resources: Click here to access online
Contents:
Machine generated contents note: 01.Introduction -- 1.1.Visualization in Medicine as a Specialty of Scientific Visualization -- 1.2.Computerized Medical Imaging -- 1.3.2D and 3D Visualizations -- 1.4.Further Information -- 1.5.Organization -- pt. I ACQUISITION, ANALYSIS, AND INTERPRETATION OF MEDICAL VOLUME DATA -- 02.Acquisition Of Medical Image Data -- 2.1.Introduction -- 2.2.Medical Image Data -- 2.3.Data Artifacts and Signal Processing -- 2.3.1.Sampling Theorem -- 2.3.2.Undersampling and Aliasing -- 2.3.3.Interpolation Artifacts -- 2.4.X-Ray Imaging -- 2.4.1.Angiography -- 2.4.2.Rotational X-Ray -- 2.4.3.Discussion -- 2.4.4.Current and Future Developments of X-Ray Imaging -- 2.5.Computed Tomography -- 2.5.1.Computed Tomography Compared to X-Ray Imaging -- 2.5.2.Principle of CT Data Generation -- 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 -- 2.6.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 -- 2.7.Ultrasound -- 2.8.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 -- SPECT -- 2.9.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 -- 3.6.3.Digital Hanging Protocol -- 3.6.4.Computer-Aided Detection -- 3.6.5.Diagnosis with 3D Visualizations -- 3.6.6.Guidelines for Soft-Copy Reading -- 3.7.Medical Visualization in Nuclear Medicine -- 3.8.Medical Image Data in Radiation Treatment Planning -- 3.8.1.Conformant and Intensity-Modulated Radiation Treatment -- 3.8.2.Brachytherapy -- 3.9.Medical Team Meetings -- 3.10.Concluding Remarks -- 04.Image Analysis For Medical Visualization -- 4.1.Introduction -- 4.2.Preprocessing and Filtering -- 4.2.1.ROI Selection -- 4.2.2.Resampling -- 4.2.3.Histogram and Histogram Transformation -- 4.2.4.General Noise Reduction Techniques -- 4.2.5.Inhomogeneity Correction -- 4.2.6.Gradient Filtering -- 4.3.An Introduction to Image Segmentation -- 4.3.1.Requirements -- 4.3.2.Manual Segmentation -- 4.3.3.Threshold-Based Segmentation -- 4.3.4.Region Growing -- 4.3.5.Watershed Segmentation -- 4.4.Graph-Based Segmentation Techniques -- 4.4.1.Livewire Segmentation -- 4.4.2.Contour-Based Segmentation with Variational Interpolation -- 4.4.3.Graph Cuts -- 4.4.4.Random Walker Segmentation -- 4.5.Advanced and Model-Based Segmentation Methods -- 4.5.1.Active Contour Models -- 4.5.2.Level Sets and Fast Marching Methods -- 4.5.3.Statistical Shape Models -- 4.5.4.Active Appearance Models -- 4.5.5.Incorporating Model Assumptions in Region Growing Segmentation -- 4.5.6.Application: Tumor Segmentation -- 4.5.7.Verification and Representation of Segmentation Results -- 4.6.Interaction for Segmentation -- 4.6.1.General Techniques for Correcting Pre-Segmentations -- 4.6.2.Mesh-Based Correction of Segmentation Results -- 4.6.3.Interactive Morphological Image Processing -- 4.6.4.Interaction Techniques for Semi-Automatic Segmentation -- 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 -- 05.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 -- pt.
II VISUALIZATION AND EXPLORATION OF MEDICAL VOLUME DATA -- 06.Surface Rendering -- 6.1.Introduction -- 6.2.Reconstruction of Surfaces from Contours -- 6.2.1.Topological Problems -- 6.2.2.Neighborhood Relations in Surface Meshes -- 6.2.3.Representation of Surface Meshes -- 6.3.Marching Cubes -- 6.3.1.Marching Squares -- 6.3.2.Basic Algorithm -- 6.3.3.Discussion -- 6.3.4.Advanced Surface Extraction Methods -- 6.3.5.Hardware-Accelerated Isosurface Extraction -- 6.4.Surface Rendering of Unsegmented Volume Data -- 6.4.1.Preprocessing Volume Data for Visualization -- 6.4.2.Selection of Isovalues -- 6.4.3.Multiple and Nested Isosurfaces -- 6.4.4.Isosurface Topology Simplification -- 6.5.Surface Rendering of Segmented Volume Data -- 6.5.1.Preprocessing -- 6.5.2.Basic Mesh Smoothing -- 6.5.3.Interactive Real-Time Mesh Smoothing -- 6.5.4.Evaluation of Smoothing Approaches -- 6.6.Advanced Mesh Smoothing -- 6.6.1.Constrained Mesh Smoothing -- 6.6.2.Context-Aware Smoothing -- 6.6.3.Extracting Surfaces from Label Volumes -- 6.6.4.Evaluation of Advanced Mesh Smoothing -- 6.7.Mesh Simplification and Web-Based Surface Rendering -- 6.7.1.Mesh Simplification -- 6.7.2.Web-Based Surgical Planning -- 6.7.3.Web-Based Medical Education -- 6.8.Concluding Remarks -- 07.Direct Volume Visualization -- 7.1.Theoretical Models -- 7.1.1.Emission -- 7.1.2.Absorption -- 7.1.3.Volume Rendering Equation -- 7.2.The Volume Rendering Pipeline -- 7.2.1.Preclassified Volume Rendering Pipeline -- 7.3.Compositing -- 7.3.1.Compositing Variations: Pseudo X-Ray, MIP, CVP, and MIDA -- 7.3.2.Thin Slab Volume Rendering -- 7.3.3.Pre-Integrated Volume 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.Raytracing-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-Based Transfer 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 -- 9.5.2.Local Transfer Functions -- 9.6.Advanced Picking -- 9.6.1.Contextual Picking -- 9.6.2.Visibility-Based Picking -- 9.7.Clipping -- 9.8.Virtual Resection -- 9.8.1.Virtual Resections by Drawing on Slices -- 9.8.2.Virtual Resection with a Deformable Cutting Plane -- 9.9.Cutting Medical Volume Data -- 9.9.1.High-Quality Representation of Cut Surfaces -- 9.9.2.Virtual Resection and Surgery Simulation -- 9.10.Summary -- 10.Labeling And Measurements In Medical Visualization -- 10.1.Introduction -- 10.2.General Design Issues -- 10.3.Interactive Measurement of Distances and Volumes -- 10.3.1.Interactive Distance Measurement -- 10.3.2.Estimation of Quantitative Values -- 10.4.Automatic Distance Measures -- 10.4.1.Bounding Volumes and Spatial Trees for Distance Computation -- 10.4.2.Efficient and Flexible Distance Computation -- 10.4.3.Clinical Examples -- 10.4.4.Measuring the Extents of Objects -- 10.5.Angular Measurements -- 10.5.1.Measurement of Angles Between Elongated Objects -- 10.5.2.Medical Applications -- 10.6.Measurements in Virtual Reality -- 10.7.Labeling 2D and 3D Medical Visualizations -- 10.7.1.Internal Labeling of 3D Medical Surface Models -- 10.7.2.External Labeling -- 10.7.3.Labeling Slice-Based Visualizations -- 10.8.Summary -- pt. III ADVANCED MEDICAL VISUALIZATION TECHNIQUES -- 11.Visualization Of Vascular Structures -- 11.1.Introduction -- 11.2.Enhancing Vascular Structures -- 11.2.1.Emphasis of Elongated Structures -- 11.2.2.Bone Removal --
Note continued: 11.3.Projection-Based Visualization -- 11.3.1.Maximum Intensity and Closest Vessel Projection -- 11.3.2.Maximum Intensity Difference Accumulation -- 11.3.3.Curved Planar Reformation -- 11.4.Vessel Analysis -- 11.4.1.Vessel Segmentation -- 11.4.2.Skeletonization and Graph Analysis -- 11.4.3.Diameter Estimation -- 11.5.Model-Based Surface Visualization -- 11.5.1.Reconstruction with Cylinders and Truncated Cones -- 11.5.2.Visualization with Parametric and Subdivision Surfaces -- 11.5.3.Implicit Reconstruction of Vascular Trees -- 11.6.Model-Free Surface Visualization -- 11.6.1.Smoothing Surface Visualizations -- 11.6.2.Visualization with MPU Implicits -- 11.6.3.Implicit Reconstruction with Sweeping -- 11.7.Vessel Visualization for Diagnosis -- 11.7.1.Diagnosis of Cerebral Aneurysms and Arterio-Venous Malformations -- 11.7.2.Diagnosis of the Coronary Heart Disease -- 11.7.3.Multiple Coordinated Views -- 11.8.Summary -- 12.Illustrative Medical Visualization -- 12.1.Introduction -- 12.2.Medical Applications -- 12.3.Curvature Approximation -- 12.3.1.Curvature-Related Measures -- 12.3.2.Curvature Estimation for Illustrative Visualization -- 12.4.An Introduction to Feature Lines -- 12.4.1.An Overview of Feature Lines -- 12.4.2.General Aspects of Feature Line Rendering -- 12.5.Geometry-Dependent Feature Lines -- 12.5.1.Silhouette Generation -- 12.5.2.Crease Lines -- 12.5.3.Ridge and Valley Lines -- 12.5.4.Suggestive Contours -- 12.5.5.Apparent Ridges -- 12.5.6.Streamline-Based Illustrative Rendering -- 12.6.Light-Dependent Feature Lines -- 12.6.1.Laplacian Lines -- 12.6.2.Photic Extremum Lines -- 12.6.3.Highlight Lines -- 12.6.4.Discussion -- 12.7.Stippling -- 12.7.1.Essential Parameters of Stippling -- 12.7.2.Frame-Coherent Stippling -- 12.8.Hatching -- 12.8.1.Curvature-Guided Hatching -- 12.8.2.Model-Based Hatching of Muscles and Vascular Structures -- 12.8.3.Combination of Curvature and Preferential Direction -- 12.8.4.Hatching Volume Models -- 12.9.Illustrative Shading -- 12.9.1.Shading in Medical Textbooks -- 12.9.2.Realization of the Extended Shading -- 12.9.3.Illustrative Visualization of Vascular Trees -- 12.10.Smart Visibility -- 12.10.1.Cutaways -- 12.10.2.Ghosted Views -- 12.11.Conclusion -- 13.Virtual Endoscopy -- 13.1.Introduction -- 13.2.Medical and Technical Background -- 13.3.Preprocessing -- 13.3.1.Preprocessing Workflow -- 13.3.2.Path Planning -- 13.4.Rendering for Virtual Endoscopy -- 13.4.1.Indirect Volume Rendering -- 13.4.2.Direct Volume Rendering -- 13.4.3.Hybrid Rendering -- 13.4.4.Advanced Rendering -- 13.4.5.Geometry Culling -- 13.5.User Interfaces for Virtual Endoscopy -- 13.5.1.Camera Control and Navigation -- 13.5.2.Views for Interactive Virtual Endoscopy -- 13.5.3.Graphical User Interface -- 13.5.4.Input Devices -- 13.6.Applications -- 13.6.1.Virtual Colonoscopy -- 13.6.2.Virtual Bronchoscopy -- 13.6.3.Virtual Angioscopy -- 13.6.4.Virtual Endoscopy for Minimally-Invasive Neurosurgery -- 13.7.Concluding Remarks -- 14.Projections And Reformations (Online Chapter) -- pt. IV VISUALIZATION OF HIGH-DIMENSIONAL MEDICAL IMAGE DATA -- 15.Visualization Of Brain Connectivity -- 15.1.Introduction -- 15.2.Acquisition of Connectivity Data -- 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 -- 15.3.1.Scalar Reduction -- 15.3.2.Glyphs -- 15.3.3.Global Multifield -- 15.4.Visualization of Connectivity Matrices -- 15.4.1.Non-Spatial Methods -- 15.4.2.Spatial Methods -- 15.5.Summary -- 16.Visual Exploration And Analysis Of Perfusion Data (Online Chapter) -- pt. V TREATMENT PLANNING, GUIDANCE AND TRAINING -- 17.Computer-Assisted Surgery -- 17.1.Introduction -- 17.2.General Tasks -- 17.3.Visualization Techniques -- 17.3.1.Visual Representation -- 17.3.2.Interaction -- 17.3.3.Simulation -- 17.3.4.Quantitative Visualization -- 17.4.Guidance Approaches -- 17.4.1.Mental Model -- 17.4.2.Documentation -- 17.4.3.Image-Based Guidance -- 17.4.4.Mechanical Guidance -- 17.5.Application Areas -- 17.5.1.Oral and Maxillofacial Surgery -- 17.5.2.Orthopedic Surgery -- 17.5.3.Neurosurgery -- 17.5.4.Hepatic Surgery -- 17.6.Conclusions -- 18.Image-Guided Surgery And Augmented Reality -- 18.1.Introduction -- 18.2.Image-Guided Surgery -- 18.2.1.Overview of IGS Applications -- 18.2.2.Medical Augmented Reality -- 18.3.Registration -- 18.3.1.Tissue Deformation and Brain Shift -- 18.3.2.Fiducial-Based Registration -- 18.3.3.Point-Based Registration -- 18.4.Calibration and Tracking -- 18.4.1.Calibrating Instruments -- 18.4.2.Camera Calibration -- 18.4.3.Optical Tracking -- 18.4.4.Electro-Magnetic Tracking -- 18.4.5.Summary -- 18.5.Navigated Control -- 18.6.Display Modes -- 18.6.1.Brief History of Medical AR -- 18.6.2.Optical See-Through Displays -- 18.6.3.Video See-Through Displays -- 18.6.4.Augmented Microscope Displays -- 18.6.5.Augmented Reality Windows -- 18.6.6.Projection-Based Medical Augmented Reality -- 18.7.Visualization Techniques for Medical Augmented Reality -- 18.7.1.The Occlusion Problem of Augmented Reality -- 18.7.2.Depth Cues in Augmented Reality -- 18.7.3.Basic Visualization in AR -- 18.7.4.Smart Visibility in AR -- 18.7.5.Illustrative Visualization in AR -- 18.7.6.Interaction in the OR -- 18.7.7.Calibrated Augmented Reality Endoscope -- 18.8.Applications -- 18.8.1.Workflow Analysis for Medical Augmented Reality -- 18.8.2.Neurosurgery -- 18.8.3.Liver Surgery -- 18.8.4.Validation and Clinical Evaluation -- 18.9.Summary -- 19.Visual Exploration Of Simulated And Measured Flow Data -- 19.1.Introduction -- 19.2.Basic Flow Visualization Techniques -- 19.2.1.Direct Flow Visualization Techniques -- 19.2.2.Feature-Based Flow Visualization Techniques -- 19.2.3.Texture-Based Flow Visualization -- 19.2.4.Geometry-Based Flow Visualization Methods -- 19.2.5.Partition-Based Flow Visualization Techniques -- 19.2.6.Evaluation of Flow Visualization Techniques -- 19.3.From Medical Image Data to Simulation Models -- 19.3.1.Segmentation and Meshing for Simulation -- 19.3.2.Requirements for Surface Meshes -- 19.3.3.Generation of Surface Meshes -- 19.3.4.Generation of Volume Grids -- 19.4.Visual Exploration of Measured Cardiac Blood Flow -- 19.4.1.Medical Background -- 19.4.2.Image Acquisition -- 19.4.3.Preprocessing Cardiac Blood Flow Data -- 19.4.4.Quantitative Analysis -- 19.4.5.Visual Exploration -- 19.4.6.Illustrative Visualization Techniques -- 19.4.7.Uncertainty Visualization -- 19.5.Exploration of Simulated Cerebral Blood Flow -- 19.5.1.Blood Flow Simulations -- 19.5.2.Extraction of Landmarks -- 19.5.3.Anatomy-Guided Flow Exploration -- 19.5.4.Lens-Based Interaction -- 19.5.5.Visualization of Vasculature and Embedded Flow -- 19.5.6.Virtual Stenting -- 19.5.7.Software Assistant -- 19.5.8.Validation -- 19.5.9.Discussion -- 19.6.Biomedical Simulation and Modeling -- 19.6.1.Biomechanical Simulation in Orthopedics -- 19.6.2.Simulation and Visualization for Planning Radio-Frequency Ablation -- 19.7.Concluding Remarks -- 20.Visual Computing For Ent Surgery Planning (Online Chapter) -- 21.Computer-Assisted Medical Education (Online Chapter) -- 22.Outlook (Online Chapter).
Summary: This book offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment. It includes algorithms, applications, and ideas on achieving reliability of results and clinical evaluation of the techniques covered, and treatment planning, guidance, and training.
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Machine generated contents note: 01.Introduction -- 1.1.Visualization in Medicine as a Specialty of Scientific Visualization -- 1.2.Computerized Medical Imaging -- 1.3.2D and 3D Visualizations -- 1.4.Further Information -- 1.5.Organization -- pt. I ACQUISITION, ANALYSIS, AND INTERPRETATION OF MEDICAL VOLUME DATA -- 02.Acquisition Of Medical Image Data -- 2.1.Introduction -- 2.2.Medical Image Data -- 2.3.Data Artifacts and Signal Processing -- 2.3.1.Sampling Theorem -- 2.3.2.Undersampling and Aliasing -- 2.3.3.Interpolation Artifacts -- 2.4.X-Ray Imaging -- 2.4.1.Angiography -- 2.4.2.Rotational X-Ray -- 2.4.3.Discussion -- 2.4.4.Current and Future Developments of X-Ray Imaging -- 2.5.Computed Tomography -- 2.5.1.Computed Tomography Compared to X-Ray Imaging -- 2.5.2.Principle of CT Data Generation -- 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 -- 2.6.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 -- 2.7.Ultrasound -- 2.8.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 -- SPECT -- 2.9.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 -- 3.6.3.Digital Hanging Protocol -- 3.6.4.Computer-Aided Detection -- 3.6.5.Diagnosis with 3D Visualizations -- 3.6.6.Guidelines for Soft-Copy Reading -- 3.7.Medical Visualization in Nuclear Medicine -- 3.8.Medical Image Data in Radiation Treatment Planning -- 3.8.1.Conformant and Intensity-Modulated Radiation Treatment -- 3.8.2.Brachytherapy -- 3.9.Medical Team Meetings -- 3.10.Concluding Remarks -- 04.Image Analysis For Medical Visualization -- 4.1.Introduction -- 4.2.Preprocessing and Filtering -- 4.2.1.ROI Selection -- 4.2.2.Resampling -- 4.2.3.Histogram and Histogram Transformation -- 4.2.4.General Noise Reduction Techniques -- 4.2.5.Inhomogeneity Correction -- 4.2.6.Gradient Filtering -- 4.3.An Introduction to Image Segmentation -- 4.3.1.Requirements -- 4.3.2.Manual Segmentation -- 4.3.3.Threshold-Based Segmentation -- 4.3.4.Region Growing -- 4.3.5.Watershed Segmentation -- 4.4.Graph-Based Segmentation Techniques -- 4.4.1.Livewire Segmentation -- 4.4.2.Contour-Based Segmentation with Variational Interpolation -- 4.4.3.Graph Cuts -- 4.4.4.Random Walker Segmentation -- 4.5.Advanced and Model-Based Segmentation Methods -- 4.5.1.Active Contour Models -- 4.5.2.Level Sets and Fast Marching Methods -- 4.5.3.Statistical Shape Models -- 4.5.4.Active Appearance Models -- 4.5.5.Incorporating Model Assumptions in Region Growing Segmentation -- 4.5.6.Application: Tumor Segmentation -- 4.5.7.Verification and Representation of Segmentation Results -- 4.6.Interaction for Segmentation -- 4.6.1.General Techniques for Correcting Pre-Segmentations -- 4.6.2.Mesh-Based Correction of Segmentation Results -- 4.6.3.Interactive Morphological Image Processing -- 4.6.4.Interaction Techniques for Semi-Automatic Segmentation -- 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 -- 05.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 -- pt.

II VISUALIZATION AND EXPLORATION OF MEDICAL VOLUME DATA -- 06.Surface Rendering -- 6.1.Introduction -- 6.2.Reconstruction of Surfaces from Contours -- 6.2.1.Topological Problems -- 6.2.2.Neighborhood Relations in Surface Meshes -- 6.2.3.Representation of Surface Meshes -- 6.3.Marching Cubes -- 6.3.1.Marching Squares -- 6.3.2.Basic Algorithm -- 6.3.3.Discussion -- 6.3.4.Advanced Surface Extraction Methods -- 6.3.5.Hardware-Accelerated Isosurface Extraction -- 6.4.Surface Rendering of Unsegmented Volume Data -- 6.4.1.Preprocessing Volume Data for Visualization -- 6.4.2.Selection of Isovalues -- 6.4.3.Multiple and Nested Isosurfaces -- 6.4.4.Isosurface Topology Simplification -- 6.5.Surface Rendering of Segmented Volume Data -- 6.5.1.Preprocessing -- 6.5.2.Basic Mesh Smoothing -- 6.5.3.Interactive Real-Time Mesh Smoothing -- 6.5.4.Evaluation of Smoothing Approaches -- 6.6.Advanced Mesh Smoothing -- 6.6.1.Constrained Mesh Smoothing -- 6.6.2.Context-Aware Smoothing -- 6.6.3.Extracting Surfaces from Label Volumes -- 6.6.4.Evaluation of Advanced Mesh Smoothing -- 6.7.Mesh Simplification and Web-Based Surface Rendering -- 6.7.1.Mesh Simplification -- 6.7.2.Web-Based Surgical Planning -- 6.7.3.Web-Based Medical Education -- 6.8.Concluding Remarks -- 07.Direct Volume Visualization -- 7.1.Theoretical Models -- 7.1.1.Emission -- 7.1.2.Absorption -- 7.1.3.Volume Rendering Equation -- 7.2.The Volume Rendering Pipeline -- 7.2.1.Preclassified Volume Rendering Pipeline -- 7.3.Compositing -- 7.3.1.Compositing Variations: Pseudo X-Ray, MIP, CVP, and MIDA -- 7.3.2.Thin Slab Volume Rendering -- 7.3.3.Pre-Integrated Volume 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.Raytracing-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-Based Transfer 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 -- 9.5.2.Local Transfer Functions -- 9.6.Advanced Picking -- 9.6.1.Contextual Picking -- 9.6.2.Visibility-Based Picking -- 9.7.Clipping -- 9.8.Virtual Resection -- 9.8.1.Virtual Resections by Drawing on Slices -- 9.8.2.Virtual Resection with a Deformable Cutting Plane -- 9.9.Cutting Medical Volume Data -- 9.9.1.High-Quality Representation of Cut Surfaces -- 9.9.2.Virtual Resection and Surgery Simulation -- 9.10.Summary -- 10.Labeling And Measurements In Medical Visualization -- 10.1.Introduction -- 10.2.General Design Issues -- 10.3.Interactive Measurement of Distances and Volumes -- 10.3.1.Interactive Distance Measurement -- 10.3.2.Estimation of Quantitative Values -- 10.4.Automatic Distance Measures -- 10.4.1.Bounding Volumes and Spatial Trees for Distance Computation -- 10.4.2.Efficient and Flexible Distance Computation -- 10.4.3.Clinical Examples -- 10.4.4.Measuring the Extents of Objects -- 10.5.Angular Measurements -- 10.5.1.Measurement of Angles Between Elongated Objects -- 10.5.2.Medical Applications -- 10.6.Measurements in Virtual Reality -- 10.7.Labeling 2D and 3D Medical Visualizations -- 10.7.1.Internal Labeling of 3D Medical Surface Models -- 10.7.2.External Labeling -- 10.7.3.Labeling Slice-Based Visualizations -- 10.8.Summary -- pt. III ADVANCED MEDICAL VISUALIZATION TECHNIQUES -- 11.Visualization Of Vascular Structures -- 11.1.Introduction -- 11.2.Enhancing Vascular Structures -- 11.2.1.Emphasis of Elongated Structures -- 11.2.2.Bone Removal --

Note continued: 11.3.Projection-Based Visualization -- 11.3.1.Maximum Intensity and Closest Vessel Projection -- 11.3.2.Maximum Intensity Difference Accumulation -- 11.3.3.Curved Planar Reformation -- 11.4.Vessel Analysis -- 11.4.1.Vessel Segmentation -- 11.4.2.Skeletonization and Graph Analysis -- 11.4.3.Diameter Estimation -- 11.5.Model-Based Surface Visualization -- 11.5.1.Reconstruction with Cylinders and Truncated Cones -- 11.5.2.Visualization with Parametric and Subdivision Surfaces -- 11.5.3.Implicit Reconstruction of Vascular Trees -- 11.6.Model-Free Surface Visualization -- 11.6.1.Smoothing Surface Visualizations -- 11.6.2.Visualization with MPU Implicits -- 11.6.3.Implicit Reconstruction with Sweeping -- 11.7.Vessel Visualization for Diagnosis -- 11.7.1.Diagnosis of Cerebral Aneurysms and Arterio-Venous Malformations -- 11.7.2.Diagnosis of the Coronary Heart Disease -- 11.7.3.Multiple Coordinated Views -- 11.8.Summary -- 12.Illustrative Medical Visualization -- 12.1.Introduction -- 12.2.Medical Applications -- 12.3.Curvature Approximation -- 12.3.1.Curvature-Related Measures -- 12.3.2.Curvature Estimation for Illustrative Visualization -- 12.4.An Introduction to Feature Lines -- 12.4.1.An Overview of Feature Lines -- 12.4.2.General Aspects of Feature Line Rendering -- 12.5.Geometry-Dependent Feature Lines -- 12.5.1.Silhouette Generation -- 12.5.2.Crease Lines -- 12.5.3.Ridge and Valley Lines -- 12.5.4.Suggestive Contours -- 12.5.5.Apparent Ridges -- 12.5.6.Streamline-Based Illustrative Rendering -- 12.6.Light-Dependent Feature Lines -- 12.6.1.Laplacian Lines -- 12.6.2.Photic Extremum Lines -- 12.6.3.Highlight Lines -- 12.6.4.Discussion -- 12.7.Stippling -- 12.7.1.Essential Parameters of Stippling -- 12.7.2.Frame-Coherent Stippling -- 12.8.Hatching -- 12.8.1.Curvature-Guided Hatching -- 12.8.2.Model-Based Hatching of Muscles and Vascular Structures -- 12.8.3.Combination of Curvature and Preferential Direction -- 12.8.4.Hatching Volume Models -- 12.9.Illustrative Shading -- 12.9.1.Shading in Medical Textbooks -- 12.9.2.Realization of the Extended Shading -- 12.9.3.Illustrative Visualization of Vascular Trees -- 12.10.Smart Visibility -- 12.10.1.Cutaways -- 12.10.2.Ghosted Views -- 12.11.Conclusion -- 13.Virtual Endoscopy -- 13.1.Introduction -- 13.2.Medical and Technical Background -- 13.3.Preprocessing -- 13.3.1.Preprocessing Workflow -- 13.3.2.Path Planning -- 13.4.Rendering for Virtual Endoscopy -- 13.4.1.Indirect Volume Rendering -- 13.4.2.Direct Volume Rendering -- 13.4.3.Hybrid Rendering -- 13.4.4.Advanced Rendering -- 13.4.5.Geometry Culling -- 13.5.User Interfaces for Virtual Endoscopy -- 13.5.1.Camera Control and Navigation -- 13.5.2.Views for Interactive Virtual Endoscopy -- 13.5.3.Graphical User Interface -- 13.5.4.Input Devices -- 13.6.Applications -- 13.6.1.Virtual Colonoscopy -- 13.6.2.Virtual Bronchoscopy -- 13.6.3.Virtual Angioscopy -- 13.6.4.Virtual Endoscopy for Minimally-Invasive Neurosurgery -- 13.7.Concluding Remarks -- 14.Projections And Reformations (Online Chapter) -- pt. IV VISUALIZATION OF HIGH-DIMENSIONAL MEDICAL IMAGE DATA -- 15.Visualization Of Brain Connectivity -- 15.1.Introduction -- 15.2.Acquisition of Connectivity Data -- 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 -- 15.3.1.Scalar Reduction -- 15.3.2.Glyphs -- 15.3.3.Global Multifield -- 15.4.Visualization of Connectivity Matrices -- 15.4.1.Non-Spatial Methods -- 15.4.2.Spatial Methods -- 15.5.Summary -- 16.Visual Exploration And Analysis Of Perfusion Data (Online Chapter) -- pt. V TREATMENT PLANNING, GUIDANCE AND TRAINING -- 17.Computer-Assisted Surgery -- 17.1.Introduction -- 17.2.General Tasks -- 17.3.Visualization Techniques -- 17.3.1.Visual Representation -- 17.3.2.Interaction -- 17.3.3.Simulation -- 17.3.4.Quantitative Visualization -- 17.4.Guidance Approaches -- 17.4.1.Mental Model -- 17.4.2.Documentation -- 17.4.3.Image-Based Guidance -- 17.4.4.Mechanical Guidance -- 17.5.Application Areas -- 17.5.1.Oral and Maxillofacial Surgery -- 17.5.2.Orthopedic Surgery -- 17.5.3.Neurosurgery -- 17.5.4.Hepatic Surgery -- 17.6.Conclusions -- 18.Image-Guided Surgery And Augmented Reality -- 18.1.Introduction -- 18.2.Image-Guided Surgery -- 18.2.1.Overview of IGS Applications -- 18.2.2.Medical Augmented Reality -- 18.3.Registration -- 18.3.1.Tissue Deformation and Brain Shift -- 18.3.2.Fiducial-Based Registration -- 18.3.3.Point-Based Registration -- 18.4.Calibration and Tracking -- 18.4.1.Calibrating Instruments -- 18.4.2.Camera Calibration -- 18.4.3.Optical Tracking -- 18.4.4.Electro-Magnetic Tracking -- 18.4.5.Summary -- 18.5.Navigated Control -- 18.6.Display Modes -- 18.6.1.Brief History of Medical AR -- 18.6.2.Optical See-Through Displays -- 18.6.3.Video See-Through Displays -- 18.6.4.Augmented Microscope Displays -- 18.6.5.Augmented Reality Windows -- 18.6.6.Projection-Based Medical Augmented Reality -- 18.7.Visualization Techniques for Medical Augmented Reality -- 18.7.1.The Occlusion Problem of Augmented Reality -- 18.7.2.Depth Cues in Augmented Reality -- 18.7.3.Basic Visualization in AR -- 18.7.4.Smart Visibility in AR -- 18.7.5.Illustrative Visualization in AR -- 18.7.6.Interaction in the OR -- 18.7.7.Calibrated Augmented Reality Endoscope -- 18.8.Applications -- 18.8.1.Workflow Analysis for Medical Augmented Reality -- 18.8.2.Neurosurgery -- 18.8.3.Liver Surgery -- 18.8.4.Validation and Clinical Evaluation -- 18.9.Summary -- 19.Visual Exploration Of Simulated And Measured Flow Data -- 19.1.Introduction -- 19.2.Basic Flow Visualization Techniques -- 19.2.1.Direct Flow Visualization Techniques -- 19.2.2.Feature-Based Flow Visualization Techniques -- 19.2.3.Texture-Based Flow Visualization -- 19.2.4.Geometry-Based Flow Visualization Methods -- 19.2.5.Partition-Based Flow Visualization Techniques -- 19.2.6.Evaluation of Flow Visualization Techniques -- 19.3.From Medical Image Data to Simulation Models -- 19.3.1.Segmentation and Meshing for Simulation -- 19.3.2.Requirements for Surface Meshes -- 19.3.3.Generation of Surface Meshes -- 19.3.4.Generation of Volume Grids -- 19.4.Visual Exploration of Measured Cardiac Blood Flow -- 19.4.1.Medical Background -- 19.4.2.Image Acquisition -- 19.4.3.Preprocessing Cardiac Blood Flow Data -- 19.4.4.Quantitative Analysis -- 19.4.5.Visual Exploration -- 19.4.6.Illustrative Visualization Techniques -- 19.4.7.Uncertainty Visualization -- 19.5.Exploration of Simulated Cerebral Blood Flow -- 19.5.1.Blood Flow Simulations -- 19.5.2.Extraction of Landmarks -- 19.5.3.Anatomy-Guided Flow Exploration -- 19.5.4.Lens-Based Interaction -- 19.5.5.Visualization of Vasculature and Embedded Flow -- 19.5.6.Virtual Stenting -- 19.5.7.Software Assistant -- 19.5.8.Validation -- 19.5.9.Discussion -- 19.6.Biomedical Simulation and Modeling -- 19.6.1.Biomechanical Simulation in Orthopedics -- 19.6.2.Simulation and Visualization for Planning Radio-Frequency Ablation -- 19.7.Concluding Remarks -- 20.Visual Computing For Ent Surgery Planning (Online Chapter) -- 21.Computer-Assisted Medical Education (Online Chapter) -- 22.Outlook (Online Chapter).

Includes bibliographical references and index.

This book offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment. It includes algorithms, applications, and ideas on achieving reliability of results and clinical evaluation of the techniques covered, and treatment planning, guidance, and training.

Elsevier ScienceDirect All Books

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