Focus
Medical imaging is the field of creating images to display the anatomy and diseases in the human body and of developing computer algorithms that extract information from those images to aid clinicians in diagnosing disease, making therapy plans and performing treatment.
The Medical Image Analysis group at TU/e focusses on developing AI methods for both the acquisition of medical images and the automatic analysis of those images. Research on image acquisition aims to improve medical images, for instance, by reducing artefacts and noise, by reducing acquisition times, by reducing the dose required for acquisition or by thinking of new ways to make anatomical structures or disease visible in images. Examples are MR navigator techniques to correct for breathing motion during scanning, smart sampling trajectories in k-space for fast acquisition and deep learning to improve images reconstructed from low-dose CT. Research on image analysis aims to automatically detect disease in images, to classify what is found into categories, to measure structures or to track moving objects. Examples are methods that can support large screening studies for early detection of diseases (‘bevolkingsonderzoek’), methods that classify suspicious lesions in the breast into type of tumour to help decide on the optimal treatment, and methods that measure the size of the brain as a biomarker for Alzheimer’s disease.
In both acquisition and analysis, state-of-the-art AI methods can have substantial impact on the accuracy, safety and costs of medical care. Most of our research is in close collaboration with industry and/or hospitals
Variants – BME/ME/MIx
Medical Image Analysis offers both the Biomedical Engineering (BME) and Medical Engineering (ME) programme. In addition, there is a joint special master’s track with the Center for Image Sciences at UMC Utrecht, called Medical Imaging (MIx), with students enrolled from both Utrecht and Eindhoven. You can choose to either do a regular BME or ME programme in Eindhoven or to do those in the joint variant with Utrecht, i.e. BME-MIx or ME-MIx.
Medical Imaging (MIx) – with UMC Utrecht
The joint master’s track allows you to take courses both at TU/e and at UMCU. The Center for Image Sciences in Utrecht is a large research institute in medical imaging, working in close collaboration with clinical departments. It hosts numerous regular scanners (e.g. CT, MRI, SPECT) as well as novel research scanners (dual energy CT, MR-linac, MR-hifu).
Course programme
The study programme adheres to the standard BME and ME programmes of the Department, with ECs for specialisation courses, free space, an externship and a master’s project. The difference between BME/ME at TU/e or BME/ME in the joint MIx master is the list from which you choose your specialisation courses. You can find the lists in the Education Guide.
More questions?
You can find further information on the FAQ page.
Courses
The medical image analysis group provides the following courses:
| Name of the course | Course code | Teachers | Quartile |
|---|---|---|---|
| OGO Beeldanalyse voor risicoanalyse van huidkanker | 8QA01 | Josien Pluim Marielle Bosboom | 2 |
| Beeldvorming en -verwerking | 8DB00 | Josien Pluim Alexander Raaijmakers Richard Lopata | 4 |
| Medische Beeldanalyse | 8DC00 | Maureen van Eijnatten Cian Scannell | 1 |
| Voortgezette Beeldvormende Technieken | 8VC00 | Richard Lopata Alexander Raaijmakers | 2 |
| Project AI for Medical Imaging | 8P361 | Mitko Veta | 3 |
| Team Challenge in Medical Imaging | 8DM10 | Mitko Veta Koen Vincken Josien Pluim | GS1-3 |
| Machine Learning in Medical Imaging and Biology | 8DM50 | Mitko Veta Federica Eduati | GS1 |
| Electromagnetic fields in MRI | 5LPE0 | Alexander Raaijmakers | GS2 |
| Capita Selecta in Medical Image Analysis | 8DM20 | Josien Pluim Marcel Breeuwer Cian Scannell | GS3 |