LEADER 05678nam 2200709Ia 450 001 9910784654503321 005 20230120004627.0 010 $a1-281-11899-0 010 $a9786611118990 010 $a0-08-054905-5 035 $a(CKB)1000000000364095 035 $a(EBL)305682 035 $a(OCoLC)173483828 035 $a(SSID)ssj0000268106 035 $a(PQKBManifestationID)11193595 035 $a(PQKBTitleCode)TC0000268106 035 $a(PQKBWorkID)10214071 035 $a(PQKB)10355514 035 $a(MiAaPQ)EBC305682 035 $a(Au-PeEL)EBL305682 035 $a(CaPaEBR)ebr10188173 035 $a(CaONFJC)MIL111899 035 $a(EXLCZ)991000000000364095 100 $a20061206d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aVisualization in medicine$b[electronic resource] $etheory, algorithms, and applications /$fBernhard Preim, Dirk Bartz 210 $aAmsterdam ;$aBoston $cMorgan Kaufmann$d2007 215 $a1 online resource (677 p.) 225 1 $aMorgan Kaufmann series in computer graphics and geometric modeling 300 $aDescription based upon print version of record. 311 $a0-12-370596-7 320 $aIncludes bibliographical references (p. 589-640) and index. 327 $aFront 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 327 $a3.2 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 327 $a5.7 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 327 $a8.2 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 327 $a10.6 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 327 $a12.5 Summary 330 $aVisualization 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. 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