The Resource Visualization in medicine : theory, algorithms, and applications, Bernhard Preim, Dirk Bartz, (electronic resource)

Visualization in medicine : theory, algorithms, and applications, Bernhard Preim, Dirk Bartz, (electronic resource)

Label
Visualization in medicine : theory, algorithms, and applications
Title
Visualization in medicine
Title remainder
theory, algorithms, and applications
Statement of responsibility
Bernhard Preim, Dirk Bartz
Creator
Contributor
Subject
Genre
Language
  • eng
  • eng
Summary
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
Member of
Cataloging source
MiAaPQ
http://library.link/vocab/creatorName
Preim, Bernhard
Dewey number
616.0754
Illustrations
illustrations
Index
index present
Language note
English
LC call number
R857.O6
LC item number
P7 2007
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Bartz, D.
Series statement
Morgan Kaufmann series in computer graphics and geometric modeling
http://library.link/vocab/subjectName
  • Imaging systems in medicine
  • Diagnostic imaging
  • Medicine
  • Radiology, Medical
Label
Visualization in medicine : theory, algorithms, and applications, Bernhard Preim, Dirk Bartz, (electronic resource)
Instantiates
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references (p. 589-640) and index
Carrier category
online resource
Carrier category code
  • cr
Content category
text
Content type code
  • txt
Contents
  • Front Cover; Visualization in Medicine; Copyright Page; Table of Contents; Foreword; Preface; Chapter 1. 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 Organization; Part I: Acquisition, Analysis, and Interpretation of Medical Volume Data; Chapter 2. Medical Image Data and Visual Perception; 2.1 Medical Image Data; 2.2 Data Artifacts; 2.3 Sensitivity and Specificity; 2.4 Visual Perception; 2.5 Summary; Chapter 3. Acquisition of Medical Image Data; 3.1 X-ray Imaging
  • 3.2 Computed Tomography3.3 Magnetic Resonance Imaging; 3.4 Ultrasound; 3.5 Positron Emission Tomography (PET); 3.6 Single-Photon Emission Computed Tomography (SPECT); 3.7 Summary; Chapter 4. Medical Volume Data in Clinical Practice; 4.1 Storage of Medical Image Data; 4.2 Conventional Film-based Diagnosis; 4.3 Soft-Copy Reading; 4.4 Summary; Chapter 5. Image Analysis for Medical Visualization; 5.1 Requirements; 5.2 Preprocessing and Filtering; 5.3 General Segmentation Approaches; 5.4 Model-based Segmentation Methods; 5.5 Interaction Techniques; 5.6 Postprocessing of Segmentation Results
  • 5.7 Skeletonization5.8 Validation of Segmentation Methods; 5.9 Registration and Fusion of Medical Image Data; 5.10 Summary; Part II: Volume Visualization; Chapter 6. Fundamentals of Volume Visualization; 6.1 The Volume Visualization Pipeline; 6.2 Histograms and Volume Classification; 6.3 Illumination in Scalar Volume Datasets; 6.4 Summary; Chapter 7. Indirect Volume Visualization; 7.1 Plane-Based Volume Rendering; 7.2 Surface-Based Volume Rendering; 7.3 Surface Postprocessing; 7.4 Summary; Chapter 8. Direct Volume Visualization; 8.1 Theoretical Models for Direct Volume Rendering
  • 8.2 The Volume Rendering Pipeline8.3 Compositing; 8.4 Summary; Chapter 9. Algorithms for Direct Volume Visualization; 9.1 Ray Casting; 9.2 Shear Warp; 9.3 Splatting; 9.4 Texture-Mapping; 9.5 Other Direct Volume Rendering Approaches; 9.6 Direct Volume Rendering of Segmented Volume Data; 9.7 Hybrid Volume Rendering; 9.8 Validation of Volume Visualization Algorithms; 9.9 Summary; Chapter 10. Exploration of Dynamic Medical Volume Data; 10.1 Introduction; 10.2 Medical Background; 10.3 Basic Visualization Techniques; 10.4 Data Processing; 10.5 Advanced Visualization Techniques
  • 10.6 Case Study: Tumor Perfusion10.7 Case Study: Brain Perfusion; 10.8 Summary; Part III: Exploration of Medical Volume Data; Chapter 11. Transfer Function Specification; 11.1 Strategies for One-Dimensional Transfer Functions; 11.2 Multidimensional Transfer Functions; 11.3 Gradient-based Transfer Functions; 11.4 Distance-based Transfer functions; 11.5 Local and Spatialized Transfer Functions; 11.6 Summary; Chapter 12. Clipping, Cutting, and Virtual Resection; 12.1 Clipping; 12.2 Virtual Resection; 12.3 Virtual Resection with a Deformable Cutting Plane; 12.4 Cutting Medical Volume Data
  • 12.5 Summary
Dimensions
unknown
Extent
1 online resource (677 p.)
Form of item
online
Isbn
9781281118998
Media category
computer
Media type code
  • c
Specific material designation
remote
System control number
  • (EBL)305682
  • (OCoLC)173483828
  • (SSID)ssj0000268106
  • (PQKBManifestationID)11193595
  • (PQKBTitleCode)TC0000268106
  • (PQKBWorkID)10214071
  • (PQKB)10355514
  • (MiAaPQ)EBC305682
  • (EXLCZ)991000000000364095
Label
Visualization in medicine : theory, algorithms, and applications, Bernhard Preim, Dirk Bartz, (electronic resource)
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references (p. 589-640) and index
Carrier category
online resource
Carrier category code
  • cr
Content category
text
Content type code
  • txt
Contents
  • Front Cover; Visualization in Medicine; Copyright Page; Table of Contents; Foreword; Preface; Chapter 1. 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 Organization; Part I: Acquisition, Analysis, and Interpretation of Medical Volume Data; Chapter 2. Medical Image Data and Visual Perception; 2.1 Medical Image Data; 2.2 Data Artifacts; 2.3 Sensitivity and Specificity; 2.4 Visual Perception; 2.5 Summary; Chapter 3. Acquisition of Medical Image Data; 3.1 X-ray Imaging
  • 3.2 Computed Tomography3.3 Magnetic Resonance Imaging; 3.4 Ultrasound; 3.5 Positron Emission Tomography (PET); 3.6 Single-Photon Emission Computed Tomography (SPECT); 3.7 Summary; Chapter 4. Medical Volume Data in Clinical Practice; 4.1 Storage of Medical Image Data; 4.2 Conventional Film-based Diagnosis; 4.3 Soft-Copy Reading; 4.4 Summary; Chapter 5. Image Analysis for Medical Visualization; 5.1 Requirements; 5.2 Preprocessing and Filtering; 5.3 General Segmentation Approaches; 5.4 Model-based Segmentation Methods; 5.5 Interaction Techniques; 5.6 Postprocessing of Segmentation Results
  • 5.7 Skeletonization5.8 Validation of Segmentation Methods; 5.9 Registration and Fusion of Medical Image Data; 5.10 Summary; Part II: Volume Visualization; Chapter 6. Fundamentals of Volume Visualization; 6.1 The Volume Visualization Pipeline; 6.2 Histograms and Volume Classification; 6.3 Illumination in Scalar Volume Datasets; 6.4 Summary; Chapter 7. Indirect Volume Visualization; 7.1 Plane-Based Volume Rendering; 7.2 Surface-Based Volume Rendering; 7.3 Surface Postprocessing; 7.4 Summary; Chapter 8. Direct Volume Visualization; 8.1 Theoretical Models for Direct Volume Rendering
  • 8.2 The Volume Rendering Pipeline8.3 Compositing; 8.4 Summary; Chapter 9. Algorithms for Direct Volume Visualization; 9.1 Ray Casting; 9.2 Shear Warp; 9.3 Splatting; 9.4 Texture-Mapping; 9.5 Other Direct Volume Rendering Approaches; 9.6 Direct Volume Rendering of Segmented Volume Data; 9.7 Hybrid Volume Rendering; 9.8 Validation of Volume Visualization Algorithms; 9.9 Summary; Chapter 10. Exploration of Dynamic Medical Volume Data; 10.1 Introduction; 10.2 Medical Background; 10.3 Basic Visualization Techniques; 10.4 Data Processing; 10.5 Advanced Visualization Techniques
  • 10.6 Case Study: Tumor Perfusion10.7 Case Study: Brain Perfusion; 10.8 Summary; Part III: Exploration of Medical Volume Data; Chapter 11. Transfer Function Specification; 11.1 Strategies for One-Dimensional Transfer Functions; 11.2 Multidimensional Transfer Functions; 11.3 Gradient-based Transfer Functions; 11.4 Distance-based Transfer functions; 11.5 Local and Spatialized Transfer Functions; 11.6 Summary; Chapter 12. Clipping, Cutting, and Virtual Resection; 12.1 Clipping; 12.2 Virtual Resection; 12.3 Virtual Resection with a Deformable Cutting Plane; 12.4 Cutting Medical Volume Data
  • 12.5 Summary
Dimensions
unknown
Extent
1 online resource (677 p.)
Form of item
online
Isbn
9781281118998
Media category
computer
Media type code
  • c
Specific material designation
remote
System control number
  • (EBL)305682
  • (OCoLC)173483828
  • (SSID)ssj0000268106
  • (PQKBManifestationID)11193595
  • (PQKBTitleCode)TC0000268106
  • (PQKBWorkID)10214071
  • (PQKB)10355514
  • (MiAaPQ)EBC305682
  • (EXLCZ)991000000000364095

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