Biomedical Signal and Image Processing, Second Edition

Kayvan Najarian, Robert Splinter

May 4, 2012 by CRC Press
Textbook - 411 Pages - 265 B/W Illustrations
ISBN 9781439870334 - CAT# K13235

USD$129.95

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Features

  • Updates every chapter and includes many additional examples
  • Employs understandable descriptions of mathematical techniques and a simple approach to complicated concepts
  • Presents newly revised and expanded end-of-chapter problems

Solutions manual available with qualifying course adoption and figures for presentations are available from the book's web page.

Summary

First published in 2005, Biomedical Signal and Image Processing received wide and welcome reception from universities and industry research institutions alike, offering detailed, yet accessible information at the reference, upper undergraduate, and first year graduate level. Retaining all of the quality and precision of the first edition, Biomedical Signal and Image Processing, Second Edition offers a number of revisions and improvements to provide the most up-to-date reference available on the fundamental signal and image processing techniques that are used to process biomedical information.

Addressing the application of standard and novel processing techniques to some of today’s principle biomedical signals and images over three sections, the book begins with an introduction to digital signal and image processing, including Fourier transform, image filtering, edge detection, and wavelet transform. The second section investigates specifically biomedical signals, such as ECG, EEG, and EMG, while the third focuses on imaging using CT, X-Ray, MRI, ultrasound, positron, and other biomedical imaging techniques.

Updated and expanded, Biomedical Signal and Image Processing, Second Edition offers numerous additional, predominantly MATLAB, examples to all chapters to illustrate the concepts described in the text and ensure a complete understanding of the material. The author takes great care to clarify ambiguities in some mathematical equations and to further explain and justify the more complex signal and image processing concepts to offer a complete and understandable approach to complicated concepts.

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