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Lecturer(s)
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Mareš Jan, prof. Ing. Ph.D.
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Course content
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1) Advanced CT image analysis 2) Methods of NMR analysis 3) EEG data analysis 4) Biomedical signals modeling - overview 5) Adnaced biomedical signal visualisation in time and frequency domain 6) Chaos and dynamical analysis 7) Biomedical data formats 8) PWA model of EEG data 9) Modeling of neuron electrical activity 10) EEG synchronisation 11) EMG, detection, localisation and classification 12) Comunication models in biomedical objects 13) Biostaistics 14) Advanced modeling in biology and physiology
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Learning activities and teaching methods
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Methods of individual activities
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Learning outcomes
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The subject deals with modern methods and tool in biomedisal and medical field (CT, NMR,...). Students will solve several case studies including real applications. For the exam it is necessary to propose a draft of publication form the field of disertation thesis. Students will be able to: - model advanced biological processes, - proces 1D, 2D and 3D signals, - prepare the experiments for selected biomedical data acquisition
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral examination, Home assignment evaluation
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Recommended literature
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Caramenlla D., C. Bartolozzi, A.L.Baert. 3D Image Processing: Techniques and Clinical Applications. ISBN 978-3642639777.
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Dunn, S.M., A. Constantinides, P.V.Moghe. Numerical Methods in Biomedical Engineering. ISBN 978-0121860318.
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Gonzalez Rafael C., Steven L. Eddins. Digital Image Processing Using MATLAB. ISBN 978-8177588989.
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Narjarian, K., A. Splinter. Biomedical Signal and Image Processing. ISBN 978-1-4398-7034-1.
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