โ Scribed by Fabian J. Theis, Anke Meyer-Bรคse
No coin nor oath required. For personal study only.
Biomedical signal analysis has become one of the most important visualization and interpretation methods in biology and medicine. Many new and powerful instruments for detecting, storing, transmitting, analyzing, and displaying images have been developed in recent years, allowing scientists and physicians to obtain quantitative measurements to support scientific hypotheses and medical diagnoses. This book offers an overview of a range of proven and new methods, discussing both theoretical and practical aspects of biomedical signal analysis and interpretation.After an introduction to the topic and a survey of several processing and imaging techniques, the book describes a broad range of methods, including continuous and discrete Fourier transforms, independent component analysis (ICA), dependent component analysis, neural networks, and fuzzy logic methods. The book then discusses applications of these theoretical tools to practical problems in everyday biosignal processing, considering such subjects as exploratory data analysis and low-frequency connectivity analysis in fMRI, MRI signal processing including lesion detection in breast MRI, dynamic cerebral contrast-enhanced perfusion MRI, skin lesion classification, and microscopic slice image processing and automatic labeling. Biomedical Signal Analysis can be used as a text or professional reference. Part I, on methods, forms a self-contained text, with exercises and other learning aids, for upper-level undergraduate or graduate-level students. Researchers or graduate students in systems biology, genomic signal processing, and computer-assisted radiology will find both parts I and II (on applications) a valuable handbook.
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A comprehensive introduction to innovative methods in the field of biomedical signal analysis, covering both theory and practice.
<span>Advanced Methods in Biomedical Signal Processing and Analysis</span><span> presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms
Content: <br>Preface</span></a></h3>, <i>Pages xiii-xiv</i><br>Acknowledgments</span></a></h3>, <i>Page xvii</i><br>List of symbols</span></a></h3>, <i>Pages xix-xxii</i><br>1 - Introduction and terminology</span></a></h3>, <i>Pages 1-13</i><br>2 - Empirical modeling and approximation</span></a></h3