PhD student: MRI Segmentation by machine learning

Eindhoven University of Technology
Eindhoven, The Netherlands
Job Type: 
Full Time
Closing Date: 
Wednesday, May 9, 2018

The PhD project

The design of accurate and robust MR image segmentation algorithms is a very challenging task, due to the highly varying appearance of anatomical structure in the MR images. This variation can be caused by differences in the scan protocol (scanner parameter settings), but also by patient variations (e.g. differences in weight) and by scanner software and hardware variations.

The development, optimization, and validation of image segmentation algorithms is a tedious and time-consuming process. Especially novel model-based methods that use machine learning approaches, such as deep learning, require large training sets of annotated data. There is a clear need to develop MRI segmentation methods that are as much as possible insensitive to the specific MR image contrast (T1-weighted, T2-weighthed, etc.) and to patient and scanner variations. The development of such algorithms is the focus of this PhD project. Their availability would significantly reduce training and validation efforts and broaden the applicability in clinical practice.

The PhD research is funded by the highly prestigious and competitive Marie Curie Innovative Training Networks (ITN) fellowship program, in a project called “Open Ground Truth Training Network (openGTN)”, see the website You will work closely together with 2 other PhD researchers in openGTN, who will focus on generating ample simulated MR images of the brain, spine and heart, with ground truth segmentations, supplying you with data for training and testing of your algorithms.

The team

You will become part of the Medical Image Analysis group at the Department of Biomedical Engineering, Eindhoven University of Technology: . You will be academically supervised by prof. dr. Marcel Breeuwer (professor at TU/e and Principal Scientist at Philips Healthcare, project leader of openGTN) and prof. dr. Josien Pluim (head of the Medical Image Analysis department).

For this Marie Curie ITN project, you will spend 50% of your time at Philips Research Hamburg, Germany (in the first three years), and you will also work for extended secondments (short externships) at the University Medical Center Utrecht, The Netherlands, Philips Healthcare, Best, The Netherlands, King’s College London, United Kingdom, Deutsches Zentrum für Neurodegeneratieve Erkrankungen, Bonn, Germany, and Klinikum Rechts der Isar / Technical University, München, Germany.


Applicants should have a Master’s degree in Electrical Engineering, Computer Science, Applied Physics, Applied Mathematics or Biomedical Engineering. Applicants with prior experience in MRI and medical image analysis will be given highest preference, as will candidates with ample experience in software design and implementation. Candidates should be able to work independently as well as in a team and be highly skilled in written and spoken English.

Candidates will be required to meet the Marie Curie Early Stage Researcher eligibility criteria. In particular, at the time of recruitment by the host organisation, candidates must be in the first four years (full-time equivalent research experience) of their research careers and not yet have been awarded a doctoral degree. This is measured from the date when they obtained the degree which would formally entitle them to embark on a doctorate. They are required to undertake trans-national mobility (i.e. move from one country to another) when taking up their appointment. At the time of recruitment by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in The Netherlands for more than 12 months in the 3 years immediately prior to the start date. Short stays such as holidays and/or compulsory national service are not taken into account.


Further information and applications

More information on the position and how to apply can be found here.