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19M071IAG - Engineering aspects of magnetic resonance imaging

Course specification
Course title Engineering aspects of magnetic resonance imaging
Acronym 19M071IAG
Study programme Electrical Engineering and Computing
Module Applied Mathematics, Audio and Video Technologies, Biomedical and Environmental Engineering, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics and Digital Systems, Energy Efficiency, Information and Communication Technologies, Microwave Engineering, Nanoelectronics and Photonics, Power Systems - Networks and Systems, Power Systems - Renewable Energy Sources, Power Systems - Substations and Power Equipment, Signals and Systems, Software Engineering
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition None.
    The goal Familiarization with basic engineering problems in magnetic resonance imaging (MRI).
    The outcome Gain knowledge and understanding of theoretical backgrounds of nuclear magnetic resonance (NMR). Familiarization with basic designs of major components of an MRI imager. Acquire capability to model static and RF electromagnetic fields necessary for imaging. Gain understanding of principles of exciter signal genertion and detection of response.
    Contents
    Contents of lectures Physical concepts of nuclear magnetic resonance. Magnetic properties of materials. Bloch equation. Static magnetic field. Circularly polarized RF magnetic field. Basic and gradient coils. RF exciters. New generation high field imagers. Impulse excitations and code sequences. Voxel selection. Contrast, noise and signal to noise ratio. T1 and T2 measurements. 2-D and 3-D imaging. Angiography.
    Contents of exercises Practical computer-based asignements and student projects.
    Literature
    1. R. W. Brown, Y-C, Cheng, E. M. Haacke, M. R. Thompson, and R. Venkatesan, Magnetic Resonance Imaging - Physical Principles and Sequence Design, 2nd ed., New Jersey, Wiley Blackwell, 2014.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    2 2
    Methods of teaching Lectures and practical computional analysis assignements.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures Test paper
    Practical lessons 30 Oral examination 30
    Projects 40
    Colloquia
    Seminars