Medical Image Processing

Corequisite:

The course cannot be taken simultaneously with:

Medical Image Processing (A6M33ZMO)
Medical Image Processing (BEAM33ZMO)

The course is a substitute for:

Medical Image Processing (A6M33ZMO)

Garant předmětu:

Jan Kybic

Lecturer:

Jan Kybic

Tutor:

Denis Baručić, Jan Kybic

Supervisor:

Department of Cybernetics

Synopsis:

This course covers the most used advanced image analysis methods, with emphasis on images from medical and biological modalities, from microscopy, to ultrasound, MRI, or CT, including time sequences.

Requirements:

Programming, the knowledge of basic image analysis methods and basic principles of medical imaging devices.

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:

1. Toennies: Guide to Medical Image Analysis, Springer 2012

2. Deserno: Biomedical Image Processing, Springer 2011

3. Yoo: Insight into images. Taylor & Francis, 2004

4. Birkfellner: Applied Medical Image Processing, CRC Press 2011

5. Jan: Medical Image Processing, Reconstruction and Restoration, CRC Press 2006

6. Dhawan: Medical Image Analysis, IEEE Press, 2003

7. Šonka, Fitzpatrick: Handbook of Medical Imaging: Volume 2, Medical Image Processing and Analysis, SPIE Press,

2000

Note:

Further information:

https://cw.fel.cvut.cz/wiki/courses/zmo

Time-table for winter semester 2022/2023:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
Wed	roomKN:E-127 Kybic J. 09:15–10:45 (lecture parallel1) Karlovo nám. Kotkova cvičebna K4roomKN:E-230 Baručić D. 11:00–12:30 (lecture parallel1 parallel nr.101) Karlovo nám. Laboratoř PC
Thu
Fri

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 (compulsory elective course)
• Medical electronics and bioinformatics (compulsory elective course)
• Medical electronics and bioinformatics (PS)
• Medical electronics and bioinformatics (compulsory elective course)