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Cover image for product 0470648473
Salzer
ISBN: 978-0-470-64847-6
Hardcover
448 pages
June 2012
This is an out of stock title.
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A walk through the exciting field of multimodality imaging and its clinical applications

This book offers a unique approach to biomedical imaging. Unlike other books on the market that cover just one or several modalities, Biomedical Imaging: Principles and Applications describes all important biomedical imaging modalities, showing how to capitalize on their combined strengths when investigating processes and interactions in dynamic systems.

Geared to non-experts looking for quick guidance on what modalities to choose for their work without getting bogged down in technical details, the book discusses technical fundamentals, molecular background, evaluation procedures, and case studies of clinical applications. With an emphasis on technologies known for their application range and the chemical information content of their data, the book covers such established modalities as X-ray, CT, MRI, and tracer imaging, as well as technologies using light or sound, including fluorescence and Raman imaging, CARS microscopy, sonography, and acoustic microscopy.

Including more than 200 figures (many in color) to help clarify the text, Biomedical Imaging:

  • Reviews the current state of image-based diagnostic medicine as well as methods and tools for visualization

  • Covers for each modality the basics of how it works, information parameters, instrumentation, and applications

  • Compares the strengths and weaknesses of different imaging technologies

  • Focuses on current and emerging applications for chemical analysis in extremely delicate samples

  • Explains the utility of multimodality imaging in the rapidly expanding field of biophotonics

An excellent startup guide for researchers and clinicians wishing to combine different imaging technologies for a true multimodality approach to problem solving, Biomedical Imaging is also a useful reference for engineers who need to understand the biomedical basis of the measured data.

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