Diffusion MRI

Course goals

After completing the course the student:
•    can identify common MRI artifacts present in diffusion MRI data
•    will know the basic processing steps that are required for diffusion MRI
•    is able to discriminate between different diffusion MRI model strategies
•    will have a basic hands-on knowledge of analysing and visualizing diffusion MRI data
•    will understand the limitations and pitfalls in the context of neuroscientific and biomedical applications

Content

Period (from – till): 14 December 2026 - 05 February 2027 (BMS_P2_A). This course can be followed together with AI for Medical Imaging BMB4708022, the schedules do not overlap.

This course covers theory and practice of processing, analysing and visualising diffusion MRI data. Key concepts and practical considerations of data processing and analysis are explained. Topics include:
•    Quality assessment
•    Artifact correction
•    Diffusion approaches
•    Fiber tractography
•    Automated analyses
•    Visualisation methods

During computer practical sessions students will learn how to work with real diffusion MRI data.

Literature/study material used:
handouts

Registration: 
You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Students' site.
Students from outside the UU or TU/E MI-track can register for this course by sending an email to mix@umcutrecht.nl or via EduXchange. Please include your name, student number, Master’s programme and the course code.

Mandatory for students in Master’s programme:
no

Optional for students in other GSLS Master’s programme:
yes