Biosignal and Medical Image Processing

3rd Edition

John L. Semmlow, Benjamin Griffel

CRC Press
Published February 25, 2014
Textbook - 630 Pages - 333 B/W Illustrations
ISBN 9781466567368 - CAT# K16329

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Summary

Written specifically for biomedical engineers, Biosignal and Medical Image Processing, Third Edition provides a complete set of signal and image processing tools, including diagnostic decision-making tools, and classification methods. Thoroughly revised and updated, it supplies important new material on nonlinear methods for describing and classifying signals, including entropy-based methods and scaling methods. A full set of PowerPoint slides covering the material in each chapter and problem solutions is available to instructors for download.

 

See What’s New in the Third Edition:

  • Two new chapters on nonlinear methods for describing and classifying signals.
  • Additional examples with biological data such as EEG, ECG, respiration and heart rate variability
  • Nearly double the number of end-of-chapter problems
  • MATLAB® incorporated throughout the text
  • Data "cleaning" methods commonly used in such areas as heart rate variability studies
  •  

The text provides a general understanding of image processing sufficient to allow intelligent application of the concepts, including a description of the underlying mathematical principals when needed. Throughout this textbook, signal and image processing concepts are implemented using the MATLAB® software package and several of its toolboxes.

The challenge of covering a broad range of topics at a useful, working depth is motivated by current trends in biomedical engineering education, particularly at the graduate level where a comprehensive education must be attained with a minimum number of courses. This has led to the development of "core" courses to be taken by all students. This text was written for just such a core course. It is also suitable for an upper-level undergraduate course and would also be of value for students in other disciplines that would benefit from a working knowledge of signal and image processing.

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