FPF: UIMOIBP063 Advanced Methods of Medical Image Data Processing (Summer 2024)
Course objectives
The course Advanced Methods of Medical Image Data Processing is primarily intended for students who are interested in the field of image processing in the context of modeling information from medical image data. During the course, students will be acquainted with the basic techniques for medical image editing with the aim of digital interpretation and visualization of image data. The next part of the course will deal with methods of image preprocessing in order to optimize image information (luminance and geometric transformations). In the following part of the course, methods of image filtering and analysis of objectification parameters will be discussed, which enable an objective analysis of the effectiveness of the respective filtering. The last part of the course will be devoted to segmentation methods, enabling the extraction of clinical information from medical images. Students will be acquainted with conventional principles of regional segmentation, time-deformable curves and cluster analysis methods. Attention will also be paid to unconventional methods of image segmentation, containing elements of heuristics with the aim of genesis of an optimized mathematical model of biological tissue. An integral part of part of the segmentation techniques will be methods for extracting the symptoms of the model of appropriate tissues.
Learning outcomes
After completing the course, the student will be able to:
- describe basic techniques for medical image editing with the aim of digital interpretation and visualization of image data,
- apply image preprocessing methods in order to optimize image information
- describe segmentation methods
Teaching methods
interactive lecture exercises
Assessment methods
75% attendance at exercises, active approach
Written test: 60 points
Elaboration of a semester project: 40 points
Fulfillment of min. 51 points
Course syllabus
FPF: UIMOIBK063 Advanced Methods of Medical Image Data Processing (Summer 2024)
Course objectives
The course Advanced Methods of Medical Image Data Processing is primarily intended for students who are interested in the field of image processing in the context of modeling information from medical image data. During the course, students will be acquainted with the basic techniques for medical image editing with the aim of digital interpretation and visualization of image data. The next part of the course will deal with methods of image preprocessing in order to optimize image information (luminance and geometric transformations). In the following part of the course, methods of image filtering and analysis of objectification parameters will be discussed, which enable an objective analysis of the effectiveness of the respective filtering. The last part of the course will be devoted to segmentation methods, enabling the extraction of clinical information from medical images. Students will be acquainted with conventional principles of regional segmentation, time-deformable curves and cluster analysis methods. Attention will also be paid to unconventional methods of image segmentation, containing elements of heuristics with the aim of genesis of an optimized mathematical model of biological tissue. An integral part of part of the segmentation techniques will be methods for extracting the symptoms of the model of appropriate tissues.
Learning outcomes
After completing the course, the student will be able to:
- describe basic techniques for medical image editing with the aim of digital interpretation and visualization of image data,
- apply image preprocessing methods in order to optimize image information
- describe segmentation methods
Teaching methods
interactive lecture exercises
Assessment methods
75% attendance at exercises, active approach
Written test: 60 points
Elaboration of a semester project: 40 points
Fulfillment of min. 51 points
Course syllabus
