Contactd.ruijters@ tue.nl Flux 4.130
Danny Ruijters is a part-time full professor in the area of data driven value-based healthcare in image guided therapy. This comprises the development of intelligent and context aware systems that optimize the data gathering and application in minimally invasive treatment. Particularly, the translation of large population datasets to the individual patient and vice-versa, and the direct application during image guided therapy is part of his research focus. He is also a principal scientist at Philips, with a track record of creating prototypes for interventional patient treatment, evaluating those prototypes in a live clinical setting, taking into account the technical, clinical and regulatory aspects.
Hyper-personalized patient treatment is enabled by translating insights from large data sets to individual patients, improving patient outcome and reducing costs for society, while lowering the administrative burden for the clinical staff.
Danny Ruijters received his engineering degree from the University of Technology in Aachen, Germany in 2001. He performed his master thesis at the École Nationale Supérieure des Télécommunications (ENST), ParisTech, Paris, France, on the topic of cortical surface extraction and separation of the hemispheres in MRI datasets by 3D segmentation. In 2010, he received a PhD degree from the TU/e and the Katholieke Universiteit Leuven on the topic of multi-modal image fusion during minimally invasive treatment. He is employed by Philips Healthcare since 2001, and is a principal scientist at the Philips Image Guided Therapy Systems Innovation department since 2011.
Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomyMedical Image Analysis (2022)
A Hidden Markov Model for 3D Catheter Tip Tracking with 2D X-ray Catheterization Sequence and 3D Rotational AngiographyIEEE Transactions on Medical Imaging (2017)
Understanding angiography-based aneurysm flow fields through comparison with computational fluid dynamicsAmerican Journal of Neuroradiology (2017)
GPU prefilter for accurate cubic B-spline interpolationComputer Journal (2012)
Vesselness-based 2D-3D registration of the coronary arteriesInternational Journal of Computer Assisted Radiology and Surgery (2009)
- Principal Scientist, Philips