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. BIGR is rooted and embedded in Department of Radiology & Nuclear Medicine of Erasmus MC - University Medical Center Rotterdam, the Netherlands.
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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. BIGR is rooted and embedded in Department of Radiology & Nuclear Medicine of Erasmus MC - University Medical Center Rotterdam, the Netherlands.
Find out more
We develop novel techniques to co-learn from various datatypes using AI to perform integrated diagnostics, focussed on creating imaging-based biomarkers to improve diagnosis and treatment in oncology.
We bring state-of-the-art techniques from computer science to the medical imaging domain, further developing, optimizing and rigorously validating them.
We develop accurate and robust tools for clinicians, such as retinal motion correction and co-localization of different imaging modalities, by using artificial intelligence and image processing techniques on ophthalmic data.
We aim to optimally combine brain imaging, clinical data and artificial intelligence techniques to promote an accurate and early diagnosis, and eventually the right treatment, for patients with neurodegenerative disease.
We are developing trackerless navigation approaches, where the imaging systems used for image guidance are utilized to track the anatomy and instruments, and to align pre-operative 3D models to the interventional images.
Our goals are to improve the understanding of how various omics affect the complex traits and to make use of such insights to improve the diagnosis, prevention and treatment of diseases whenever possible.
We improve the management of prostate cancer patients by developing machine learning-based prognostic models that stratify patients into those that will benefit from additional diagnostic procedures and those that do not.
Our infrastructure can greatly benefit personalized medicine by making pipelines for imaging biomarker extraction available to researchers and clinicians. Additionally, we create a reference database for different imaging biomarkers, which can be used to compare an individual against the general population. This will enable improved re-use of imaging data for diagnostics and prognostics.
We aim to design accelerated quantitative MRI acquisitions and use advanced reconstruction techniques to create images that allow clinical diagnosis to be made.
We develop novel techniques for quantitative analysis of medical images, with a focus on deep learning techniques and on large-scale image-based studies. Currently our main application areas are in neuro-, vascular-, and pulmonary image analysis
We focuse on using artificial intelligence and advanced image analysis techniques to improve diagnosis and prediction of musculoskeletal diseases.
Imaging infrastructure for the COllaboration for New TReatments of Acute Stroke Consortium
2023 - 2028
Euro-BioImaging is a research infrastructure that offers open access to imaging technologies, training and data services in biological and biomedical imaging. Euro-BioImaging consists of imaging facilities, called Nodes, that have opened their doors to all life science researchers.
Health-RI serves as the national coordination point for agreements on the reuse of health data, stimulating cooperation between all parties and supporting researchers.
At the Imaging Office we provide (nearly) ready to use AI pipelines and infrastructure solutions developed at BIGR as a service.
We are looking for two PhD students on this multi-center international consortium project to work on building a benchmark MRI dataset for liver cancer, developing novel AI methods for liver tumor phenotyping, and performing clinical validation studies.
We are looking for two PhD students and a PostDoc to work on our novel AI for Integrated Diagnostics research line, which aims to join forces of radiomics and pathomics to create trustworthy models to aid clinicians in decision making. This PhD position focusses on developing novel deep learning methods, exploiting automated machine learning and meta-learning concepts.
We are looking for two PhD students and a PostDoc to work on our novel AI for Integrated Diagnostics research line, which aims to join forces of radiomics and pathomics to create trustworthy models to aid clinicians in decision making. This PhD position focusses on developing pathomics AI methods for soft-tissue tumors (STT).
Biomedical Imaging Group Rotterdam is a part of Erasmus MC
