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Medical Imaging has become one of the most important visualization and interpretation methods in biology and medecine over the past decade. This time has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying medical images. This has led to a huge growth in the application of digital processing techniques for solving medical problems. Design, implementation, and validation of complex medical systems requires a tight interdisciplinary collaboration between physicians and engineers because poor image quality leads to proble
Mathematics --- Physical methods for diagnosis --- Computer. Automation --- Imaging systems in medicine. --- Diagnostic imaging --- Image processing --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Clinical imaging --- Imaging, Diagnostic --- Medical diagnostic imaging --- Medical imaging --- Noninvasive medical imaging --- Diagnosis, Noninvasive --- Imaging systems in medicine --- Medical imaging systems --- Medical instruments and apparatus --- Mathematics. --- Diagnostic Imaging --- Pattern Recognition --- Image Processing, Computer-Assisted. --- Mathematical Computing. --- Pattern recognition systems --- Imagerie médicale --- Traitement d'images --- Reconnaissance des formes (Informatique) --- methods. --- Mathématiques --- ELSEVIER-B EPUB-LIV-FT
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"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."--Jacket.
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