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13M054ABS - Medical image computing

Course specification
Course title Medical image computing
Acronym 13M054ABS
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 The objective of the course is to offer theoretical and practical knowledge in the field of advanced medical image processing and analysis from different medical image modalities.
    The outcome Students will be able to understand and apply advanced software tools for processing and analysis of medical images, as well as to develop new algorithms for quantitative medical imaging.
    Contents
    Contents of lectures Review of medical imaging modalities. Preprocessing methods. Application of preprocessing methods in nuclear medicine. Registration methods in mono-modal and multi-modal systems. Deformable image registration. Advanced segmentation methods (active contours, shape modeling, clustering). Application of segmentation methods in radiology. 3D visualization methods.
    Contents of exercises Application of SimpleITK tool for advanced processing, analysis and visualization of medical images. Application of commercially available software dedicated to quantitative medical imaging, in collaboration with clinical institutions.
    Literature
    1. M. M. Janković, Biomedical Image Analysis, University of Belgrade - School of Electrical Engineering, electronic book, 2025
    2. A.P.Dhawan: Medical Image Analysis. Wiley-IEEE Press, Second Ed., 2011. (Original title)
    3. J.L. Semmlow, B. Griffel, "Biosignal and Medical Image Processing", CRC Press, Taylor&Francis Group, LLC, Third Ed., 2014. (Original title)
    4. C. Ravishankar, S. Pudipeddi. Image processing and acquisition using Python. Chapman and Hall/CRC, 2020. (Original title)
    5. V.J. Schmid, A. Meyer-Baese, "Pattern Recognition in Medical Imaging", Academic Press, Second Ed., 2014. (Original title)
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 2
    Methods of teaching Lectures, computer exercises, scientific paper presentation and project.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures Test paper 30
    Practical lessons 10 Oral examination
    Projects 60
    Colloquia
    Seminars