Mathematics of Medical Imaging
Published on 14. April 2003
Book
Hardback
739 pages
978-0-13-067548-4 (ISBN)
Description
For advanced undergraduate courses in the mathematics of medical imaging.
The goal of this text is to prepare students to read and understand the research literature in the mathematical aspects of medical imaging connected to measurement and image reconstruction including data collection, signal processing and noise analysis. The text should be suitable for self study by a motivated student with a solid mathematical background.
The goal of this text is to prepare students to read and understand the research literature in the mathematical aspects of medical imaging connected to measurement and image reconstruction including data collection, signal processing and noise analysis. The text should be suitable for self study by a motivated student with a solid mathematical background.
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 240 mm
Width: 183 mm
Thickness: 30 mm
Weight
1282 gr
ISBN-13
978-0-13-067548-4 (9780130675484)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
1. Measurements and Modeling.
2. Linear Models and Linear Equations.
3. A Basic Model for Tomography.
4. Introduction to the Fourier Transform.
5. Convolution.
6. The Radon Transform.
7. Introduction to Fourier Series.
8. Sampling.
9. Filters.
10. Implementing Shift Invariant Filters.
11. Reconstruction in x-ray Tomography.
12. Imaging Artifacts in x-ray Tomography.
13. Algebraic Reconstruction Techniques.
14. Probability and Random Variables.
15. Applications of Probability in Medical Imaging.
16. Random Processes.
Appendix A. Background Material.
Appendix B. Basic Analysis.
2. Linear Models and Linear Equations.
3. A Basic Model for Tomography.
4. Introduction to the Fourier Transform.
5. Convolution.
6. The Radon Transform.
7. Introduction to Fourier Series.
8. Sampling.
9. Filters.
10. Implementing Shift Invariant Filters.
11. Reconstruction in x-ray Tomography.
12. Imaging Artifacts in x-ray Tomography.
13. Algebraic Reconstruction Techniques.
14. Probability and Random Variables.
15. Applications of Probability in Medical Imaging.
16. Random Processes.
Appendix A. Background Material.
Appendix B. Basic Analysis.