Development of a model for the automatic detection of clinically relevant landmarks in 3D imaging modalities.
We are continuously looking for interesting new projects. More information about project proposals can be found here.
MSc students are eligible to receive a monthly reimbursement of €500,- for a period of six months. For more information, please read the requirements. An overview of current project vacancies can be seen below.
Development of a model to determine the individual fetal heart rates in twin pregnancies.
Development of an AI-assisted algorithm for automatic detection of adhesions on cine MRIRead more →
Development of deep learning algorithms and a web application for automated classification of COVID-19.Read more →
Development of a deep learning algorithm and web application for automated detection of fractures in the radius, ulna, and metacarpal bones on conventional radiographs.Read more →
Development of machine learning systems to find and annotate protected health information in medical records.Read more →
Development of a model for accurate facial profile outcome prediction following oral and maxillofacial surgery.Read more →
Development of a deep learning algorithm that can classify the different types of artifacts in whole slide images.Read more →
Development of deep learning algorithms and web application for automated classification of COVID-19.Read more →
Development of a deep learning algorithm for learning face representations.Read more →
Development of a model that can identify whether a febrile ICU patient with acute brain injury has an infectious fever or non-infectious fever.Read more →
We develop algorithms for segmentation of muscles and fat tissue in 3D CT images.Read more →
Project aimed at development of deep learning algorithms for the (semi-) automated scoring of PD-L1 positive tumor cells, an established biomarker for immunotherapy treatment response in lung cancer patients.Read more →
Development of a model for prediction of quality of life.Read more →