Assessing application possibilities of biomedical signal processing methods in treatment and diagnostic purposes. In numerous instances, primarily imaging modalities, students should perceive the importance of signal processing in the progress and development of medical diagnostics.The theoretical basis and examples of basic methods of signal processing and its biomedical application will be introduced. The students will gain understanding of basic biomedical signals and understanding of the importance of the principles of modeling and analysis of biological systems

Students will be introduced to basic principles of digital signal processing with application in biomedical signals. Application of the theory of probability and statistics in signal processing. Stochastic perception of biomedical signals through the prism of random processes, their characteristics and principles of their analysis. The principles of image reconstruction from projections in medical imaging modalities.

Introduction: Fourier transform, discrete Fourier transform, Z transform, convolution and correlation. - The statistical basis of the theory of probability with applications in signal processing (Bayes' theorem, random variables, moments, correlation and independence of random variables, the most important types of probability distributions, the central limit theorem) - Random processes (ergodicity, stationarity) - Description of the main characteristics of biomedical signals, biosignals physiological origins, principles and basic signal generation preprocessing procedure to display and further analysis. Types and examples of biomedical signals: action potentials, EKG, EMG, EEG, ERP, speech signal, EGG, elimination of artifacts, analysis of waveforms and estimates of their complexity, the filtering in the time and frequency domain - The basic methods of imaging diagnostics, imaging principles, image reconstruction from projections (Radon transform), the application of Radon transform and characteristic artifacts in the image reconstruction of different modalities (CT, SPECT, PET, NMR, ultrasound). - Modeling biomedical systems, point processes, parametric modeling, and application

Lectures and lab excersices