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Description
This textbook is a concise introduction to medical imaging aimed at physical scientists and engineers, including budding biomedical engineers and biophysicists. The book introduces fundamental concepts related to how we "see" inside the body using medical imaging technology and what is needed to obtain useful images.
The text first considers the underlying physical principles by which information about tissues within the body can be extracted in the form of signals, examining the major principles used: transmission, reflection, emission, and resonance. It then explains how these signals can be converted into images, i.e., full 3D volumes, demonstrating how common methods of "reconstruction" are shared by some imaging techniques, despite relying on different physics to generate the "signals." Finally, it explores how medical imaging can be used to generate more than just pictures, but genuine quantitative measurements, and increasingly, measurements of physiological processes at every point within the 3D volume using methods such as tracers and advanced dynamic acquisitions.
Now in its second, fully updated and expanded edition, the textbook contains new sections on image analysis concepts, covers a wide range of techniques used to enhance and interpret medical imaging, and includes concise introductions to optimization and machine learning in their application to medical imaging . The second edition also includes expanded discussions on quantitative, functional, physiological, and metabolic imaging.
'Principles of Medical Imaging for Engineers’ second edition will be invaluable to students and graduate students in engineering and physical sciences with an interest in biomedical engineering, as well as to their professors.
Table of Contents
Part I: From Signals.- 1. Introduction.- 2. Transmission – X-rays.- 3. Reflection - Ultrasound.- 4. Emission – SPECT/PET.- 5. Resonance – Nuclear Magnetic Resonance.- Part II: To Images.- 6. Imaging.- 7. Timing-based Reconstruction - Ultrasound.- 8. Back-projection Reconstruction – X-ray and PET/SPECT.- 9. Fourier Reconstruction – MRI.- 10. Principles of Reconstruction.- Part III: And Beyond.- 11. Generating and Enhancing Contrast.- 12. Beyond Contrast: Quantitative, Physiological and Functional Imaging.-13. Image Analysis Concepts.- 14. Image Processing.- 15. Modelling.- Part IV: Reference.- 16: Optimization and Inference.- 17: Machine Learning.- Supplementary Material.- Exercise Solutions.
