Biosignal and Medical Image Processing

This third edition of a bestseller offers comprehensive coverage of the major approaches in biomedical signal and image processing. It provides a complete set of signal 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. This edition covers data "cleaning" methods commonly used in such areas as heart rate variability studies, along with actual examples. It also includes new end-of-chapter problems.

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.

"An excellent review of the actual trendiest techniques in signal processing with a very clear (and simplified) description of their capabilities in signal and image analysis. Matlab examples are an excellent addition to provide students with capabilities to understand better how the techniques work"Enrique Nava Baro, PhD, University of MÁlaga, Spain"The book is a welcome addition to the teaching literature for biomedical engineering, building on the previous edition's friendly approach to introducing the material. This makes it particularly suitable for biomedical engineering, a field in which students come from a variety of backgrounds, and where familiarity of the fundamentals of electrical engineering cannot be assumed."David A. Clifton, University of Oxford, UK

Autorentext
John L. Semmlow (Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA) (Author) , Benjamin Griffel (Author)

Zusammenfassung

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.

Inhalt

Introduction. Basic Concepts. Spectral Analysis: Classical Methods. Digital Filters. Spectral Analysis: Modern Techniques. TimeFrequency Analysis. Wavelet Analysis. Advanced Signal Processing Techniques: Optimal and Adaptive Filters. Multivariate Analyses: Principal Component Analysis and Independent Component Analysis. Fundamentals of Imaging Processing: MATLAB Image Processing Toolbox. Spectral Analysis: The Fourier Transform. Image Segmentation. Image Reconstruction. Classification I: Linear Discriminant Analysis and Support Vector Machines. Adaptive Neural Nets.