Biomedical Informatics

Course description

Biomedical data, information and databases; computer science and informatics in biomedicine; standards in biomedical informatics; biomedical data security, privacy and confidentiality; clinical informatics; public health informatics; imaging informatics; bioinformatics; biostatistics; radiomics; information-driven decision-support systems in biomedicine and healthcare.

Course is carried out on study programme

Elektrotehnika 2. stopnja

Objectives and competences

The course objective is to obtain knowledge in the field of biomedical informatics, which is extremely interdisciplinary, merging approaches from biomedical, electrical and computer engineering, informatics, medicine, pharmacy, biology, management, sociology and economy, and is primarily concerned with optimal storage, retrieval, protection, transport, standardization and usage of biomedical data and information. Practical laboratory work consists of implementing computerized and computer-assisted techniques that adhere to the existing standards and established techniques in biomedical informatics that are used for protection, storage, transport and retrieval of biomedical data and information.

Learning and teaching methods

During lectures, theoretical aspects of techniques, existing standards and established methods are given, which are additionally supported by descriptions of practical examples from different fields of application. During laboratory practice, techniques for computer-and information-based protection, storing, transport and retrieval of biomedical data and information are developed and implemented.

Intended learning outcomes

With successful course completion, the students should be able to:

  • define biomedical data, databases and standards, and established concepts for ensuring security, privacy and confidentiality of biomedical data and information;
  • compare the individual fields of biomedical informatics (public health informatics, clinical informatics, imaging informatics and bioinformatics);
  • differentiate among individual indicators and research study types for observing health in the given population;
  • differentiate among different biomedical image acquisition and analysis techniques;
  • differentiate among different topics of molecular biology;
  • choose an adequate method for statistical analysis of the given biomedical data;
  • develop simplified computer algorithms for problem solving in the field of biomedical informatics;
  • evaluate existing and new approaches for managing and handling biomedical data and information.

Reference nosilca

  1. Dejan Knez, Boštjan Likar, Franjo Pernuš in Tomaž Vrtovec. Computer-assisted screw size and insertion trajectory planning for pedicle screw placement surgery. IEEE Transactions on Medical Imaging, 35(6):1420-1430, 2016. [doi:10.1109/TMI.2016.2514530] [FV: 3.390 (2014); 18/249 engineering, electrical & electronic; četrtina]
  2. Robert Korez, Bulat Ibragimov, Boštjan Likar, Franjo Pernuš in Tomaž Vrtovec. A framework for automated spine and vertebrae interpolation-based detection and model-based segmentation. IEEE Transactions on Medical Imaging, 34(8):1649-1662, 2015. [doi:10.1109/TMI.2015.2389334] [FV: 3.390 (2014); 18/249 engineering, electrical & electronic; 1. četrtina]
  3. Bulat Ibragimov, Jerry L. Prince, Emi Z. Murano, Jonghye Woo, Maureen Stone, Boštjan Likar, Franjo Pernuš in Tomaž Vrtovec. Segmentation of tongue muscles from super-resolution magnetic resonance images. Medical Image Analysis, 20(1):198-207, 2015. [doi:10.1016/j.media.2014.11.006] [FV: 654 (2014); 8/102 computer science, interdisciplinary applications; 1. četrtina]
  4. Bulat Ibragimov, Boštjan Likar, Franjo Pernuš in Tomaž Vrtovec. Shape representation for efficient landmark-based segmentation in 3D. IEEE Transactions on Medical Imaging, 33(4):861-874, 201 [doi:10.1109/TMI.2013.2296976] [FV: 3.390 (2014); 18/249 engineering, electrical & electronic; 1. četrtina]
  5. Tomaž Vrtovec, Michiel M.A. Janssen, Boštjan Likar, René M. Castelein, Max A. Viergever in Franjo Pernuš. A review of methods for evaluating the quantitative parameters of sagittal pelvic alignment. The Spine Journal, 12(5):433-446, 2012. [doi:10.1016/j.spinee.2012.02.013] [FV: 3.355 (2012); 3/63 orthopedics; 1. četrtina]

Study materials

  1. Biomedical Informatics, E.H. Shortliffe, J.J. Cimino, Springer, 4. izdaja, 2014.
  2. Medical Informatics: Knowledge Management and Data Mining in Biomedicine, H. Chen, S.S. Fuller, C. Friedman, W. Hersh (Eds.), Springer, 2010.
  3. PACS and Imaging Informatics: Basic Principles and Applications, H.K. Huang, Wiley- Blackwell, 2010.
  4. Basic Epidemiology, R. Bonita, R. Beaglehole, T. Kjellström, WHO, 2. izdaja, 2006.
  5. Introductory Biostatistics, C.T. Le, Wiley-Interscience, 2003.

Bodi na tekočem

Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška cesta 25, 1000 Ljubljana

E:  dekanat@fe.uni-lj.si T:  01 4768 411