Biomedical image analysis 1st Edition by Rangaraj Rangayyan ISBN 9780849396953 0849396956

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ISBN 10: 0849396956

ISBN 13: 9780849396953

Author: Rangaraj M. Rangayyan

Computers have become an integral part of medical imaging systems and are used for everything from data acquisition and image generation to image display and analysis. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges.

Biomedical Image Analysis demonstrates the benefits reaped from the application of digital image processing, computer vision, and pattern analysis techniques to biomedical images, such as adding objective strength and improving diagnostic confidence through quantitative analysis. The book focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis, rather than on the imaging equipment and imaging techniques. Each chapter addresses several problems associated with imaging or image analysis, outlining the typical processes, then detailing more sophisticated methods directed to the specific problems of interest.

Biomedical Image Analysis is useful for senior undergraduate and graduate biomedical engineering students, practicing engineers, and computer scientists working in diverse areas such as telecommunications, biomedical applications, and hospital information systems.

Table of contents: 

The Nature of Biomedical Images

1. Body Temperature as an Image

2. Transillumination

3. Light Microscopy

4. Electron Microscopy

5. X-ray Imaging

6. Tomography

7. Nuclear Medicine Imaging

8. Ultrasonography

9. Magnetic Resonance Imaging

10. Objectives of Biomedical Image Analysis

11. Computer-aided Diagnosis

12. Remarks

13. Study Questions and Problems

14. Laboratory Exercises and Projects

Image Quality and Information Content

1. Difficulties in Image Acquisition and Analysis

2. Characterization of Image Quality

3. Digitization of Images

4. Optical Density

5. Dynamic Range

6. Contrast

7. Histogram

8. Entropy

9. Blur and Spread Functions

10. Resolution

11. The Fourier Transform and Spectral Content

12. Modulation Transfer Function

13. Signal-to-Noise Ratio

14. Error-based Measures

15. Application: Image Sharpness and Acutance

16. Remarks

17. Study Questions and Problems

18. Laboratory Exercises and Projects

Removal of Artifacts

1. Characterization of Artifacts

2. Synchronized or Multiframe Averaging

3. Space-domain Local-statistics-based Filters

4. Frequency-domain Filters

5. Matrix Representation of Image Processing

6. Optimal Filtering

7. Adaptive Filters

8. Comparative Analysis of Filters for Noise Removal

9. Application: Multiframe Averaging in Confocal Microscopy

10. Application: Noise Reduction in Nuclear Medicine Imaging

11. Remarks

12. Study Questions and Problems

13. Laboratory Exercises and Projects

Image Enhancement

1. Digital Subtraction Angiography

2. Dual-energy and Energy-subtraction X-ray Imaging

3. Temporal Subtraction

4. Gray-scale Transforms

5. Histogram Transformation

6. Convolution Mask Operators

7. High-frequency Emphasis

8. Homomorphic Filtering for Enhancement

9. Adaptive Contrast Enhancement

10. Objective Assessment of Contrast Enhancement

11. Application: Contrast Enhancement of Mammograms

12. Remarks

13. Study Questions and Problems

14. Laboratory Exercises and Projects

Detection of Regions of Interest

1. Thresholding and Binarization

2. Detection of Isolated Points and Lines

3. Edge Detection

4. Segmentation and Region Growing

5. Fuzzy-set-based Region Growing to Detect Breast Tumors

6. Detection of Objects of Known Geometry

7. Methods for the Improvement of Contour or Region Estimates

8. Application: Detection of the Spinal Canal

9. Application: Detection of the Breast Boundary in Mammograms

10. Application: Detection of the Pectoral Muscle in Mammograms

11. Application: Improved Segmentation of Breast Masses by Fuzzy-set-based Fusion

12. Remarks

13. Study Questions and Problems

14. Laboratory Exercises and Projects

Analysis of Shape

1. Representation of Shapes and Contours

2. Shape Factors

3. Fourier Descriptors

4. Fractional Concavity

5. Analysis of Spicularity

6. Application: Shape Analysis of Calcifications

7. Application: Shape Analysis of Breast Masses and Tumors

8. Remarks

9. Study Questions and Problems

10. Laboratory Exercises and Projects

Analysis of Texture

1. Texture in Biomedical Images

2. Models for the Generation of Texture

3. Statistical Analysis of Texture

4. Laws’ Measures of Texture Energy

5. Fractal Analysis

6. Fourier-domain Analysis of Texture

7. Segmentation and Structural Analysis of Texture

8. Audification and Sonification of Texture in Images

9. Application: Analysis of Breast Masses Using Texture and Gradient Measures

10. Remarks

11. Study Questions and Problems

12. Laboratory Exercises and Projects

Analysis of Oriented Patterns

1. Oriented Patterns in Images

2. Measures of Directional Distribution

3. Directional Filtering

4. Gabor Filters

5. Directional Analysis via Multiscale Edge Detection

6. Hough-Radon Transform Analysis

7. Application: Analysis of Ligament Healing

8. Application: Detection of Breast Tumors

9. Application: Bilateral Asymmetry in Mammograms

10. Application: Architectural Distortion in Mammograms

11. Remarks

12. Study Questions and Problems

13. Laboratory Exercises and Projects

Image Reconstruction from Projections

1. Projection Geometry

2. The Fourier Slice Theorem

3. Backprojection

4. Algebraic Reconstruction Techniques

5. Imaging with Diffracting Sources

6. Display of CT Images

7. Agricultural and Forestry Applications

8. Microtomography

9. Application: Analysis of the Tumor in Neuroblastoma

10. Remarks

11. Study Questions and Problems

12. Laboratory Exercises and Projects

Deconvolution, Deblurring, and Restoration

1. Linear Space-invariant Restoration Filters

2. Blind Deblurring

3. Homomorphic Deconvolution

4. Space-variant Restoration

5. Application: Restoration of Nuclear Medicine Images

6. Remarks

7. Study Questions and Problems

8. Laboratory Exercises and Projects

Image Coding and Data Compression

1. Considerations Based on Information Theory

2. Fundamental Concepts of Coding

3. Direct Source Coding

4. Application: Source Coding of Digitized Mammograms

5. The Need for Decorrelation

6. Transform Coding

7. Interpolative Coding

8. Predictive Coding

9. Image Scanning Using the Peano-Hilbert Curve

10. Image Coding and Compression Standards

11. Segmentation-based Adaptive Scanning

12. Enhanced JBIG Coding

13. Lower-limit Analysis of Lossless Data Compression

14. Application: Teleradiology

15. Remarks

16. Study Questions and Problems

17. Laboratory Exercises and Projects

Pattern Classification and Diagnostic Decision

1. Pattern Classification

2. Supervised Pattern Classification

3. Unsupervised Pattern Classification

4. Probabilistic Models and Statistical Decision

5. Logistic Regression

6. The Training and Test Steps

7. Neural Networks

8. Measures of Diagnostic Accuracy

9. Reliability of Features, Classifiers, and Decisions

10. Application: Image Enhancement for Breast Cancer Screening

11. Application: Classification of Breast Masses and Tumors via Shape Analysis

12. Application: Content-based Retrieval and Analysis of Breast Masses

13. Remarks

14. Study Questions and Problems

15. Laboratory Exercises and Projects

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Tags: Rangaraj Rangayyan, Biomedical image