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.
The FUTURE-AI guideline for trustworthy and deployable AI by FUTURE-AI consortium in which Martijn is involved has finally been published by none other than BMJ!
Gennady Roshchupkin received De Frans van der Helm Award for Best Young Researcher BME 2025 at the 10th Dutch Conference on Bio-Medical Engineering.
The new research program for better stroke care, by the Dutch CONTRAST Consortium with Theo as one of the program chairs, was granted with 4 million euros.
Imaging infrastructure for the COllaboration for New TReatments of Acute Stroke Consortium
2023 - 2028
Tumor localization and visualization using magnetic seed tracking and augmented reality
2024 - 2028
Frontotemporal dementia (FTD) is a type of dementia that has a debilitating effect on patients and their caregivers. About 20% of patients have genetic FTD caused by known pathogenetic mutations. For the other patients, who have sporadic FTD, diagnosis is slow (~4 years) with frequent misdiagnosis due to clinical, genetic and molecular heterogeneity. Thus, there is an urgent need for biomarkers that improve diagnosis of sporadic FTD and its pathological subtypes. Artificial intelligence is expected to play a key role here, driven by its expanding role in the medical field, in particular radiology, in combination with the growth of clinical data and medical imaging made available for medical research. This project focuses on the diagnosis of FTD by validating a comprehensive set of liquid and imaging biomarkers and developing an AI-driven diagnostic tool. As a PhD candidate on this project, you will apply state-of-the-art machine-learning based methodology, particularly deep neural networks and disease progression modeling, to address key challenges in FTD diagnosis.
Biomedical Imaging Group Rotterdam is a part of Erasmus MC
