Advances in digital imaging and computer power over the last couple of decades have made advanced tomographic and pseudo-tomographic imaging with X-rays possible. More recently, artificial intelligence-based processes have been introduced in the medical imaging field, including applications in image reconstruction. New image formation methods that take advantage of digital detectors, iterative reconstruction, and AI-based approaches allow for the development of high spatial- and temporal-resolution functional imaging with x rays, either for material decomposition and/or for dynamic perfusion imaging. These are key approaches that will allow enhanced screening and treatment planning and monitoring.
The AXTI lab is engaged in the development of cutting-edge dedicated breast CT and digital breast tomosynthesis systems for functional imaging of the breast. These new modalities involve the development, optimization, characterization, and patient testing of the first such systems in the world.
You will guide a team of PhD students and participate in the development of new image acquisition and correction methods that combine traditional methods and AI-based approaches, for both imaging modalities: dedicated breast CT and digital breast tomosynthesis. While the focus of the work will be on the medical physics aspects of image formation and correction, there will also be opportunities to contribute to all steps of the imaging chain, including reconstruction and radiomics-based analysis. There will be close collaboration with industry partners to facilitate the translation of these methods into clinical evaluation and use.
Tasks will consist of development, implementation, validation, and testing of image acquisition and correction methods using, where needed, AI-based methods, computer simulations of image acquisition, physical and digital phantom-based imaging, presenting and writing papers on the study results, supervising PhD students (and potentially Master’s students), and participating and aiding in the planning and writing of new grant applications.
You should be a creative and enthusiastic researcher with a PhD degree in medical physics, biomedical engineering, or similar.
In addition you possess the following characteristics:
Please apply here
All additional information about the vacancy can be obtained from Dr. Ioannis Sechopoulos, Associate Professor.
Nijmegen is the oldest Dutch city with a rich history and one of the liveliest city centers in the Netherlands. Radboud University has over 17,000 students. Radboud University Medical Centre (Radboudumc) is a leading academic center for medical science, education and health care with over 8,500 staff and 3,000 students. Radboudumc strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. The Department of Radiology and Nuclear Medicine is one of the most active research departments of the Radboudumc, where more than 100 researchers are continuously striving to optimize healthcare.