Medical Image Processing
- The course cannot be taken simultaneously with:
- Medical Image Processing (A6M33ZMO)
Medical Image Processing (BAM33ZMO)
- Garant předmětu:
- Jan Kybic
- Jan Kybic
- Denis Baručić, Jan Kybic
- Department of Cybernetics
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.
The knowledge of basic signal processing methods including a Fourrier transform, and the knowledge of the basic principles of medical imaging methods.
- Syllabus of lectures:
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
- Syllabus of tutorials:
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.
- Study Objective:
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.
- Study materials:
 Sonka M., Fitzpatrick J. M.: Handbook of Medical Imaging, vol.2. SPIE Press, 2000.
 Bankman, I. Handbook of Medical Imaging, Processing and Analysis, vol.1. Academic Press, 2000.
- Further information:
- Time-table for winter semester 2022/2023:
Mon Tue WedroomKN:E-127
Kotkova cvičebna K4roomKN:E-230
- Time-table for summer semester 2022/2023:
- Time-table is not available yet
- The course is a part of the following study plans:
- Medical Electronics and Bioinformatics - Specialization Image Processing (PS)
- Medical Electronics and Bioinformatics - Specialization Signal Processing (compulsory elective course)
- Medical Electronics and Bioinformatics - Specialization Bioinformatics (compulsory elective course)
- Medical Electronics and Bioinformatics - Specialization Medical Instrumentation (compulsory elective course)