Biomedical Imaging Group Rotterdam
The Biomedical Imaging Group Rotterdam (BIGR) is at the forefront of research in medical image analysis & artificial intelligence (AI). We aim to improve efficiency and quality of healthcare by developing innovative AI methods in medical imaging.
We focus on both fundamental and applied research, covering the topics of image analysis, machine learning, image reconstruction, quantitative imaging biomarkers, image-guided interventions, making use of both research data and routine clinical data.
We have a strong outward look: towards other imaging sources, other diagnostic modalities, integrated diagnostics, collaboration with clinical departments. We have strong collaborations with many researchers, clinicians and industry partners.
Wietske’s paper on an automatic human embryo volume measurement in first trimester ultrasound from the Rotterdam Periconception Cohort has now been officially published in J Med Internet Res (JMIR)!!
Stefan was interviewed about using more sustainable transport, such as the train, when we go to conferences.
Ilva will be the new vice-chair of the Panel of Nodes of the Euro-Bio Imaging Community.
Tumor localization and visualization using magnetic seed tracking and augmented reality
2024 - 2028
Current guideline-recommended risk stratification in high-risk non-muscle invasive bladder cancer (HR-NMIBC) is inadequate at predicting which patients are at the highest risk of developing progression to aggressive disease. In case of progression no personalized bladder-sparing treatment options are available for these patients and the bladder is surgically removed with a decrease of the patients’ quality of life. Clinically relevant RNA-based molecular subtypes have the potential to improve risk stratification by identification of patients at the highest risk of progression, but sequencing is costly and time-consuming. Within AI-PRECISE we will use a multimodal approach by combining artificial intelligence (AI), histopathology images and RNA sequencing data to predict molecular subtypes in bladder cancer and to identify targets for novel bladder-sparing treatment options. The AI based targets for novel treatments will be validated in bladder cancer organoids developed in our group. The final aim of this project is creating trustworthy AI models to aid clinicians in accurate patient risk stratification followed by organoid-guided decision making.
Biomedical Imaging Group Rotterdam is a part of Erasmus MC
