Lines of research
- Improving screening strategies for the national screening program for breast cancer, in particular exploring the potential for personalized risk-based strategies to optimize the harm-benefit ratio, effectiveness, and efficiency of the current programs.
- Development of artificial intelligence techniques to get the clinically most relevant data from radiological images, including automated measurements of breast density, automated lesion detection and classification in various imaging modalities, and cancer characterization through multimodal radiomics.
- Evaluation and validation of new and emerging imaging modalities for breast examination, including various advanced MRI techniques, digital breast tomosynthesis, breast CT, automated breast ultrasound, point-of care ultrasound, microwave imaging, as well as evaluation of the advantages of novel artificial intelligence approaches for imaging evaluation and patient care.
- Analyzing deep learning algorithms for assessment of pathological whole slide images (WLI) of breast cancer and lymph nodes and implementing these algorithms in daily clinical practice.
- Improving distress screening with psychometric research and development and efficacy studies for matched supportive care.
- Unraveling the oncogenesis of the various types of ovarian cancer.
- Developing intraperitoneal natural killer cell therapy in ovarian cancer.
- Developing and implementing new treatment strategies in (prevention of) ovarian cancer.
- BRCA tumor test as a pre-screen for therapy and predisposition (OPA).
News & agendas
Centers of clinical expertise
Information might be only available in Dutch.