Biosignal and medical image processing / John L. Semmlow and Benjamin Griffel.
Material type: TextPublication details: Boca Raton : CRC Press, ©2014.Edition: 3rd edDescription: xxi, 607 p. : illustrations ; 27 cmISBN:- 9781466567368 (hardcover : alk. paper)
- 616.0754 23 Se472
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
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Books | ISI Library, Kolkata | 616.0754 Se472 (Browse shelf(Opens below)) | Available | 137094 |
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616.0754 Sa237 Medical imaging : artificial intelligence, image recognition, and machine learning techniques / | 616.0754 Se472 Biosignal and biomedical image processing | 616.0754 Se472 Biosignal and medical image processing/ | 616.0754 Se472 Biosignal and medical image processing / | 616.0754 Se472 Biosignal and medical image processing/ | 616.0754 Sh525 Molecular imaging | 616.0754 So698 Handbook of medical imaging |
Includes bibliographical references and index.
1. Introduction --
2. Biosignals measurements, noise and analysis --
3. Spectral analysis : classical methods --
4. Noise Reduction and Digital filters --
5. Modern Spectral analysis : The search for narrowband signals --
6. Time-frequency analysis --
7. Wavelet analysis --
8. Optimal and adaptive filters --
9. Multivariate analyses : principal component analysis and independent component analysis --
10. Chaos and nonlinear dynamics --
11. Nonlinearity detection: information-based methods --
12. Fundamentals of image processing: mThe MATLAB image processing toolbox --
13. Image processing: filters, transformations, and registration --
14. Image segmentation --
15. Image acquisition and reconstruction --
16. Classification I : linear discriminant analysis and support vector machines --
17. Classification II: adaptive Neural nets --
Appendices.
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.
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