Advanced Biomedical Image Analysis

This book covers the four major areas of image processing: Image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. Image registration, storage, and compression are also covered.  The text focuses on recently developed image processing and analysis operators and covers topical research.

Spis treści:
PREFACE.
ACKNOWLEDGMENTS.
CHAPTER 1: Image Analysis – A Perspective.
1.1. Introduction.
1.2. Main Biomedical Imaging Modalities.
1.3. Biomedical Image Analysis.
1.4. Current Trends in Biomedical Imaging.
1.5. About this Book.
1.6. Chapter References.
CHAPTER 2: Survey of Fundamental Image Processing Operators.
2.1. Statistical Image Description.
2.2. Brightness and Contrast Manipulation.
2.3. Image enhancement and restoration.
2.4. Intensity–based segmentation (thresholding).
2.5. Multidimensional thresholding.
2.6. Image calculations.
2.7. Binary image processing.
2.8. Biomedical Examples.
2.9. Chapter References.
CHAPTER 3: Image Processing in the Frequency Domain.
3.1. The Fourier Transform.
3.2. Fourier–based filtering.
3.3. Other integral transforms: the discrete cosine transform and the Hartley transform.
3.4. Biomedical examples.
3.5. Chapter References.
CHAPTER 4: Wavelet–Based Filtering.
4.1. Introduction to the wavelet transform and multiscale decomposition.
4.2. Wavelet–based filtering.
4.3. Comparison of frequency–domain analysis to wavelet analysis.
4.4. Biomedical examples.
4.5. Chapter References.
CHAPTER 5: Adaptive Filtering.
5.1. Adaptive Filter Principles.
5.2. Adaptive Noise Reduction.
5.3. Adaptive filters in the frequency domain, adaptive Wiener filters.
5.4. Segmentation with local adaptive thresholds and related methods.
5.5. Biomedical examples.
5.6. Chapter References.
CHAPTER 6: Deformable Models and Ac tive Contours.
6.1. The Principle of Deformable Models.
6.2. Two–dimensional active contours (Snakes).
6.3. Three–dimensional active contours.
6.4. Live Wire techniques.
6.5. Biomedical Examples.
6.6. Chapter References.
CHAPTER 7: The Hough Transform.
7.1. Detecting lines and edges with the Hough transform.
7.2. Detection of circles and ellipses with the Hough transform.
7.3. The Generalized Hough Transform.
7.4. The Randomized Hough Transform.
7.5. Biomedical Examples.
7.6. Chapter References.
CHAPTER 8: Texture Analysis.
8.1. Statistical texture classification.
8.2. Texture classification with local neighborhood methods.
8.3. Frequency–Domain Methods for Texture classification.
8.4. Run–Lengths.
8.5. Other Classification Methods.
8.6. Biomedical Examples.
8.7. Chapter References.
CHAPTER 9: Shape Analysis.
9.1. Cluster Labeling.
9.2. Spatial–Domain Shape Metrics.
9.3. Statistical Moment Invariants.
9.4. Chain Codes.
9.5. Fourier descriptors.
9.6. Topological Analysis.
9.7. Biomedical Examples.
9.8. Chapter References.
CHAPTER 10: Fractal approaches to image analysis.
10.1. Self–similarity and the fractal dimension.
10.2. Estimation techniques for the fractal dimension in binary images.
10.3. Estimation techniques for the fractal dimension in grayscale images.
10.4. Fractal dimension in the frequency domain.
10.5. The local Hölder exponent.
10.6. Biomedical Examples.
10.7. Chapter References.
CHAPTER 11: Image Registration.
11.1. Linear Spatial Transformations.
11.2. Nonlinear Transformations.
11.3. Registration Quality Metrics.
11.4. Interpolation Methods for Image Registration.
11.5. Biomedical Examples.
11.6. Chapter References.
CHAPTER 12: Image storage, transport, and compression.
12.1. Image size, resolution, and depth.
12.2. Image Archiving, DICOM, and PACS.
12.3. Lossles s Image Compression.
12.4. Lossy Image Compression.
12.5. Biomedical Examples.
12.6. Chapter References.
CHAPTER 13: Image Visualization.
13.1. Grayscale image visualization.
13.2. Color representation of grayscale images.
13.3. Contour Lines.
13.4. Surface rendering.
13.5. Volume visualization.
13.6. Interactive 3D rendering and Animation.
13.7. Biomedical Examples.
13.8. Chapter References.
CHAPTER 14: Image Analysis and Visualization Software.
14.1. Image Processing Software – an Overview.
14.2. ImageJ.
14.3. Examples for image processing programs.
14.4. Crystal Image.
14.5. OpenDX.
14.6. Wavelet–related software.
14.7. Algorithm Implementation.
14.8. Chapter References.
APPENDIX A: Image Analysis with Crystal Image.
APPENDIX B: Software provided on DVD.