Medical Image Analysis
Course description
Content
Medical diagnosis, prognosis and quantification of progression is in general based on biomarkers. These may be blood or urine markers, but currently, imaging is taking over as a more indicative biomarker for many purposes.
This course will give an introduction to medical image formation in the different scanning modalities: X-ray, CT, MR, fMRI, PET, US etc. We will continue with the underlying image analysis disciplines of segmentation, registration and end with specific machine learning applications in clinical practise.
Prerequisites
The students are expected to have a mature and operational mathematical knowledge. Linear algebra, geometry, basic mathematical analysis, and basic statistics are mandatory disciplines.
In the course, we will be using Python as the programming language, and programming skills in Python are highly recommended.
Academic qualifications equivalent to a BSc degree are recommended.
Practical information
The course is offered as a single-subject course at the Faculty of Science. Single-subject courses typically run for seven to nine weeks with scheduled activities approx. one day per week.
You will be attending the course together with full-time students from the Faculty of Science, and you must meet various admission requirements. The course ends with an exam.
The number of places is limited, and they are allocated on a first-come, first-served basis, so do not delay your application!
Location
Faculty of Science
Department of Computer Science
Nørre Allé 61
DK-2100 Copenhagen
