Subject description - BEAM33ZMO

Summary of Study | Summary of Branches | All Subject Groups | All Subjects | List of Roles | Explanatory Notes               Instructions
BEAM33ZMO Medical Image Processing
Roles:PS, PV Extent of teaching:2P+2C
Department:13133 Language of teaching:EN
Guarantors:Kybic J. Completion:Z,ZK
Lecturers:Kybic J. Credits:6
Tutors:Baručić D., Kybic J. Semester:Z

Web page:


This subject describes algorithms for digital image processing of 2D and 3D images, with emphasis on biomedical applications. We shall therefore concentrate on the most often used techniques in medical image processing: segmentation, registration, and classification. The methods will be illustrated by a range of examples on medical data. The students will implement some of the algorithms during the practice sessions. Because of the very large overlap between courses A6M33ZMO and A4M33ZMO, the courses will be taught together this year.

Study targets:

Learn the principles and usage of basic algorithms for medical image processing, such as registration, segmentation and classification. The students will learn to implement some of the algorithms.

Course outlines:

1. Segmentation - active contours, level sets
2. Segmentation - shape models,
3. Segmentation - superpixels, random walker, GraphCuts, graph search, normalized cuts
4. Segmentation - texture, texture descriptors, textons
5. Segmentation - CNN, U-net
6. Detection of cells and nuclei
7. Detection of vessels and fibers
8. Detection of nodules and mammographic lesions
9. Localization of organs and structures
10. Registration - ICP, coherent point drift, B-splines, rigid registration, multiresolution
11. Registration - rigid, elastic, daemons
12. Registration by CNN

Exercises outline:

Individual works will consist of independent practical work in a computer laboratory involving the use of algorithms covered by the course for analysis of specific medical data. Some algorithms will be implemented from scratch and some using existing freely available libraries and toolkits. Apart from a general overview, the students will gain a deeper understanding of some of the methods and will learn to apply them to practical problems.


[1] Sonka M., Fitzpatrick J. M.: Handbook of Medical Imaging, vol.2. SPIE Press, 2000.
[2] Bankman, I. Handbook of Medical Imaging, Processing and Analysis, vol.1. Academic Press, 2000.


The knowledge of basic signal processing methods including a Fourrier transform, and the knowledge of the basic principles of medical imaging methods.


image processing, medical imaging, registration, segmentation, classification, interpolation, detection, reconstruction, noise suppression, active contours.

Subject is included into these academic programs:

Program Branch Role Recommended semester
MEBIO3_2018 Image Processing PS 3
MEBIO2_2018 Medical Instrumentation PV 3
MEBIO4_2018 Signal Processing PV 3
MEBIO1_2018 Bioinformatics PV 3

Page updated 5.12.2023 14:54:51, semester: L/2022-3, Z/2024-5, Z,L/2023-4, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)