Image Processing


About this course

Period (from – till ): 12 September 2024 - 31 January 2025 (BMS_P1_A)
Course coordinator : Dr. Kenneth Gilhuijs
Dr. Alexander Leemans, UMC Utrecht/Imaging Division, lecturer
Dr. Kenneth Gilhuijs, UMC Utrecht/Imaging Division, lecturer
Renée Allebrandi, MA (course contact person)

Course content
This course covers the full roadmap from basic to more advanced techniques that are commonly used in medical image processing. You will learn how to analyse concrete medical questions that arise from medical images, and that can be solved by mathematical analysis of CT, MRI and X-ray. We will take you from theory to design of computer-aided diagnosis systems and Radiomics systems. Examples of such systems are those that automatically detect tumors in CT and MRI scans, that automatically detect micro-aneurysms in retinal images, or that estimate the prognosis of breast-cancer patients based on imaging features that cannot be picked up by the human eye. Topics include segmentation (dynamic programming, active contours, level sets), image registration, mathematical morphology, texture analysis, pattern recognition (feature spaces, classifiers; support-vector machines and random forests). During the lectures we will provide small practical assignments using a voting system. A computer practicum will be provided to get hands-on experience with the different techniques. In addition, individual assignments are provided consisting of actual problems that were encountered in medical images.

The exam consists of 3 parts:
• Written exam: 80%
• Written report: 10%
• Presentation: 10%
The weights indicated above are applied to calculate the final mark. To pass the course the grade for the written test must be a 5.0 or higher and the final mark must be an unrounded 5.5 or higher.

Literature/study material used:
Book: Image Processing, Analysis, and Machine vision (Sonka, Hlavac, Boyle), as well as handout materials.


Medical Imaging students are registered automatically for this course upon entering the Masterprogramme.
Other UU and TU/e partnership students can register for this course via here on the Students' site.
Students from outside the UU or TU/E partnership can register for this course by sending an email to or via EduXchange. Please include your name, student number, Master’s programme and the course code.
Mandatory :
Yes, for MIMG students.

Optional for students in other GSLS Master’s programme:

Prerequisite knowledge:
A BSc in

  • (applied) physics
  • (applied) mathematics
  • computer science
  • biomedical engineering
  • science major of University College Utrecht
  • electrical engineering
  • or similar degree

Learning outcomes

After completing the course the student:

  1. is able to choose the most appropriate technique for medical imaging processing and image analysis.
  2. knows the underlying theory to understand the strengths and weaknesses of common techniques for image segmentation, image registration, image feature extraction and image feature classification
  3. is able to evaluate image processing and analysis techniques using standardized methodology
  4. is able to implement solutions for new medical imaging problems
  5. knows the benefits and pitfalls of computer-aided diagnosis

Good to know

You will be enrolled for this course by administration of the programme of this course.

Link to more information

If anything remains unclear, please check the FAQ of Utrecht University.


  • Start date

    2 September 2024

    • Ends
      8 November 2024
    • Term *
      Period 1
    • Location
    • Instruction language
    Currently no more seats available
These offerings are valid for students of TU Eindhoven