Computed Radiation Imaging: Physics and Mathematics of Forward and Inverse Problems by Esam M A Hussein

Computed Radiation Imaging: Physics and Mathematics of Forward and Inverse Problems

byEsam M A Hussein, Esam M A Hussein

Other | June 1, 2011

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Computer-assisted imaging with radiation (x- and gamma rays) is an integral part of modern medical-diagnostic practice. This imaging technology is also slowly finding its way into industrial applications. Although the technology is well developed, there is a need for further improvement to enhance image quality, reduce artifacts, minimize patient radiation exposure, compete with and complement other imaging methods (such as magnetic resonance imaging and ultrasonics), and accommodate dense and large objects encountered in industrial applications.

Scientists and engineers, attempting to progress this technology, are faced with an enormous amount of literature, addressing the imaging problem from various view points. This book provides a single source that addresses both the physical and mathematical aspects of the imaging problem in a consistent and comprehensive manner.

  • Discusses the inherent physical and numerical capabilities and limitations of the methods presented for both the forward and inverse problems
  • Provides information on available Internet resources and software
  • Written in a manner that makes it readable by physicists, mathematicians, engineers and computer scientists – avoids, as much as possible, the use of specialized terminology without clear introduction and definition

Details & Specs

Title:Computed Radiation Imaging: Physics and Mathematics of Forward and Inverse ProblemsFormat:OtherDimensions:302 pages, 1 × 1 × 1 inPublished:June 1, 2011Publisher:Elsevier ScienceLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0123877784

ISBN - 13:9780123877789

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Table of Contents

  1. Radiation Imaging
  2. PART I - The Forward Problem

  3. Radiation Transport
  4. Measurement Models
  5. Transmission
  6. Emission
  7. Scattering
  8. PART II - The Inverse Problem

  9. Features
  10. Formulation
  11. Preprocessing of Measurements
  12. Matrix-Based Methods
  13. Functional Optimization
  14. Analytic Methods
  15. Probabilistic Methods
  16. Incomplete Problems
  17. Testing
  18. Post-Processing: Image Enhancement