Examination arrangement

Course content

The course teaches central principles and methods for processing and analyzing digital images, with a focus on medical images. Central topics in the course are normalization, filtering, registration, fusing, segmentation and automated classification using both classical methods and modern methods based on artificial intelligence.

Learning outcome

A candidate that has completed the course should have the following learning outcomes:

Knowledge:

• Has in-depth knowledge of the structure and properties of digital images
• Has broad knowledge of principles for normalization, filtering, registration and other basic methods for image processing
• Has broad knowledge of principles for segmentation, classification and other basic methods for image analysis

Skills:

• Can use relevant image processing tools independently
• Can apply various image processing and analysis methods based on a given problem and unprocessed images
• Can assess the possibilities and limitations of different image processing and analysis methods
• Can apply knowledge to evaluate new research in image processing and analysis

General competence:

• Masters the terminology and has insight into the mode of operation of methods for medical image processing and analysis
• Can discuss problems, methods and conclusions within medical image processing and analysis with collaborating professionals, colleagues and students
• Can analyze problems and results within the research field of medical image processing and analysis

Learning methods and activities

Blockwise lectures and group work with electronic submission. Sessions will be held (on campus and/or digitally) over up to eight days during the semester, and students have four compulsory assignments. The assignments will be student-active, with exercises with imaging data. All exercises come with written and / or video-based tutorials. The assignments facilitate the thematic linking of theory and practice. All learning resources are made available via the e-learning platform: articles, links, short films (animations, lectures etc.), answers to assignments and discussion forums with students and teachers.

Compulsory assignments

• Written assignment 1
• Written assignment 2
• Written assignment 3
• Written assignment 4

Further on evaluation

Students must submit four mandatory written work requirements that must be approved before they can take the exam.

Compulsory activities are generally valid for a calendar year, but the department may, upon application and assessment, make exceptions.

Specific conditions

Course materials

Course material will be presented at the start of the course