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Handbook of Medical Image Processing and Analysis. Edition No. 2

  • ID: 1762590
  • Book
  • December 2008
  • 1000 Pages
  • Elsevier Science and Technology
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The Handbook of Medical Image Processing and Analysis is a comprehensive compilation of concepts and techniques used for processing and analyzing medical images after they have been generated or digitized. The Handbook is organized into six sections that relate to the main functions: enhancement, segmentation, quantification, registration, visualization, and compression, storage and communication.

The second edition is extensively revised and updated throughout, reflecting new technology and research, and includes new chapters on: higher order statistics for tissue segmentation; tumor growth modeling in oncological image analysis; analysis of cell nuclear features in fluorescence microscopy images; imaging and communication in medical and public health informatics; and dynamic mammogram retrieval from web-based image libraries.

For those looking to explore advanced concepts and access essential information, this second edition of Handbook of Medical Image Processing and Analysis is an invaluable resource. It remains the most complete single volume reference for biomedical engineers, researchers, professionals and those working in medical imaging and medical image processing.

Dr. Isaac N. Bankman is the supervisor of a group that specializes on imaging, laser and sensor systems, modeling, algorithms and testing at the Johns Hopkins University Applied Physics Laboratory. He received his BSc degree in Electrical Engineering from Bogazici University, Turkey, in 1977, the MSc degree in Electronics from University of Wales, Britain, in 1979, and a PhD in Biomedical Engineering from the Israel Institute of Technology, Israel, in 1985. He is a member of SPIE.

- Includes contributions from internationally renowned authors from leading institutions- NEW! 35 of 56 chapters have been revised and updated. Additionally, five new chapters have been added on important topics incluling Nonlinear 3D Boundary Detection, Adaptive Algorithms for Cancer Cytological Diagnosis, Dynamic Mammogram Retrieval from Web-Based Image Libraries, Imaging and Communication in Health Informatics and Tumor Growth Modeling in Oncological Image Analysis.- Provides a complete collection of algorithms in computer processing of medical images- Contains over 60 pages of stunning, four-color images

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1. Fundamental Enhancement Techniques
2. Adaptive Image Filtering
3. Enhancement by Multiscale Nonlinear Operators
4. Medical Image Enhancement with Hybrid Filters

5. Overview and Fundamentals of Medical Image Segmentation
6. Image Segmentation by Fuzzy Clustering: Methods and Issues
7. Segmentation with Neural Networks
8. Deformable Models
9. Shape Information in Deformable Models
10. Gradient Vector Flow Deformable Models
11. Fully Automated Hybrid Segmentation of the Brain
12. Unsupervised Tissue Classification
13. Partial Volume Segmentation with Voxel Histograms
14. Higher Order Statistics for Tissue Segmentation

15. Two-dimensional Shape and Texture Quantification
16. Texture Analysis in Three Dimensions for Tissue Characterization
17. Computational Neuroanatomy Using Shape Transformations
18. Tumor Growth Modeling in Oncological Image Analysis
19. Arterial Tree Morphometry
20. Image-Based Computational Biomechanics of the Musculoskeletal System
21. Three-Dimensional Bone Angle Quantification
22. Database Selection and Feature Extraction for Neural Networks
23. Quantitative Image Analysis for Estimation of Breast Cancer Risk
24. Classification of Breast Lesions in Mammograms
25. Quantitative Analysis of Cardiac Function
26. Image Processing and Analysis in Tagged Cardiac MRI
27. Analysis of Cell Nuclear Features in Fluorescence Microscopy Images
28. Image Interpolation and Resampling

29. Physical Basis of Spatial Distortions in Magnetic Resonance Images
30. Physical and Biological Bases of Spatial Distortions in PET Images
31. Biological Underpinnings of Anatomic Consistency and Variability in the Human Brain
32. Spatial Transformation Models
33. Validation of Registration Accuracy
34. Landmark-based Registration Using Features Identified through Differential Geometry
35. Image Registration Using Chamfer Matching
36. Within-Modality Registration Using Intensity-Based Cost Functions
37. Across-Modality Registration Using Intensity-Based Cost Functions
38. Talairach Space as a Tool for Intersubject Standardization in the Brain
39. Warping Strategies for Intersubject Registration
40. Optimizing the Resampling of Registered Images
41. Clinical Applications of Image Registration
42. Registration for Image-Guided Surgery
43. Image Registration and the Construction of Multidimensional Brain Atlases

44. Visualization Pathways in Biomedicine
45. Three-Dimensional Visualization in Medicine and Biology
46. Volume Visualization in Medicine
47. Fast Isosurface Extraction Methods for Large Image Data Sets
48. Computer Processing Methods for Virtual Endoscopy

49. Fundamentals and Standards of Compression and Communication
50. Medical Image Archive and Retrieval
51. Image Standardization in PACS
52. Imaging and Communication in Medical and Public Health Informatics
53. Dynamic Mammogram Retrieval from Web-Based Image Libraries
54. Quality Evaluation for Compressed Medical Images: Fundamentals
55. Quality Evaluation for Compressed Medical Images: Diagnostic Accuracy
56. Quality Evaluation for Compressed Medical Images: Statistical Issues
57. Three-Dimensional Image Compression with Wavelet Transforms
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Bankman, Isaac
Isaac Bankman is affiliated with Johns Hopkins University
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