Computer processing and analysis of medical images, as well as experimental data analysis of physiological signals, have evolved since the late 1980s from a variety of directions, ranging from signal and imaging acquisition equipment to areas such as digital signal and image processing, computer vision, and pattern recognition. The most important physiological signals, such as electrocardiograms (ECG), electromyograms (EMG), electroencephalograms (EEG), and magnetoencephalograms (MEG), represent analog signals that are digitized for the purposes of storage and data analysis. The nature of medical images is very broad; it is as simple as an chest X-ray or as sophisticated as noninvasive brain imaging, such as functional magnetic resonance imaging (fMRI). While medical imaging is concerned with the interaction of all forms of radiation with tissue and the clinical extraction of relevant information, its analysis encompasses the measurement of anatomical and physiological parameters from images, image processing, and motion and change detection from image sequences. This chapter gives an overview of biological signal and image analysis, and describes the basic model for computer-aided systems as a commonbasis enabling the study of several problems of medical-imagingbased diagnostics.
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Computer processing and analysis of medical images, as well as experimental data analysis of physiological signals, have evolved since the late 1980s from a variety of directions, ranging from signal and imaging acquisition equipment to areas such as digital signal and image processing, computer vision, and pattern recognition. The most important physiological signals, such as electrocardiograms (ECG), electromyograms (EMG), electroencephalograms (EEG), and magnetoencephalograms (MEG), represent...
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