Open projects

We have several open research projects for MSc students who want to do an internship or graduation project. We keep these projects in a portfolio document: BIGR MSc Project Portfolio. In general, the projects focus on medical image processing.

Biomedical Imaging Research Infrastructure

  • The Departments of Child and Adolescent Psychiatry/Psychology and Radiology & Nuclear Medicine are hiring a full-time Imaging Data Manager. As data manager you will work with two of the world’s largest neuroimaging cohort studies in addition to several novel clinical studies. First, the Department of Child and Adolescent Psychiatry/Psychology has been collecting neuroimaging data in the Generation R Study, a population-based birth cohort, since 2008. Second, the Departments of Epidemiology and Radiology have been collecting neuroimaging data in the Rotterdam Study, a longitudinal cohort of aging, since 2005. Lastly, the Departments of Radiology and Child and Adolescent Psychiatry/Psychology has several ongoing clinical studies where (anonymized) imaging data needs to be retrieved from different centres (both nationally and internationally) and maintained in a database that adheres to the FAIR principles (Findable, Accessible, Interoperable & Reproducible). The data manager is actively working with and contributing to the data management plan of the department(s).

Quantitative MR reconstruction

  • Gadolinium-based contrast agents (GBCAs) are widely used in clinical magnetic resonance imaging (MRI) to identify the presence of brain tumours, lesions in Multiple Sclerosis, and many other tissue abnormalities. Per annum millions of doses of GBCAs are administered in medical imaging centres worldwide. However, there is evidence of contrast agent accumulation in patients, with unknown long-term consequences. Indeed, it is widely recognized that a reduction and even avoidance of contrast agents urgently needed. In a collaborative project the MR Physics group in Erasmus MC and the Medical Imaging Cluster at TU Delft developed new quantitative MR techniques allowing sub-voxel characterization of tissues. Furthermore, preliminary evidence by the MR Physics group suggests that gliomas as well as MS lesions can be characterized based on quantitative MRI without the necessity of gadolinium contrast injection through AI techniques. In this project, we aim to facilitate contrast-free characterization of glioma and MS lesions by combining the best aspects of two revolutionary technologies: quantitative MRI and deep learning AI technology. The project involves a synergistic collaboration between Erasmus MC, TU Delft and GE Healthcare.
If you have your own ideas for a medical imaging analysis MSc project, feel free to contact dr. Stefan Klein.