Erasmus University Medical Center Rotterdam

Erasmus MC (EMC), University Medical Center Rotterdam is an innovative center for high-quality medical research, education and care. The overall research aim of EMC is to translate bench discoveries to bedside applications. The Department of Radiology & Nuclear Medicine is one of the largest, most advanced medical imaging departments in Europe in terms of staff size, scientific output, and equipment. The Biomedical Imaging Group Rotterdam (BIGR), a research group within the Radiology & Nuclear Medicine department, develops and validates advanced AI techniques for use in processing and analyzing large, complex, and heterogeneous sets of medical imaging data. BIGR is actively involved in several infrastructure initiatives such as the Dutch Health Research Infrastructure initiative (Health-RI) and Euro-BioImaging (Flagship Node Population Imaging Infrastructure), which develop and share tools designed to facilitate large-scale data-driven science in the field of medical imaging.

Role of institution in the project

Erasmus MC is involved in the implementation of the central hub (WP4) to host and support an XNAT database for central storage of anonymized cancer images, to introduce a harmonized structure for storing image-derived data, and to connect to central services for collecting searchable FAIR Metadata. In addition, EMC is involved in the federated data processing and analysis (WP6), to develop a containerized version of software for automatic construction of radiomics models and interactive segmentation. Regarding use cases (WP7), EMC is supporting validation of the platform to ensure that the image (meta)data storage infrastructure meets the usecase requirements.

Hakim Achterberg

Hakim Achterberg (PhD) is a Research Software Engineer at the department of Radiology & Nuclear Medicine, Erasmus MC. He is the lead developer of the BIGR IT infrastructure group (the Infra Group). He is responsible for the architecture and development of the software created and maintained by the Infra Group (e.g. XNATpy). The Infra Group aims to improve the efficiency in medical imaging research and healthcare through leveraging advanced technologies and software engineering practices. To this end, the Infra Group creates software, organises community meetings, and is working towards defining (meta-)data standards. In EUCAIM he is part of T4.3 and will focus on the meta-data models and standards.

Esther Bron

Esther Bron (PhD) is assistant professor at the department of Radiology & Nuclear Medicine, Erasmus MC, where she is principal investigator of the research line Neuroimage analysis & Machine learning, with applications in neurodegenerative diseases, cardiovascular diseases and dementia. Her research focuses on novel quantitative imaging biomarkers, diagnosis and prediction models based on high-dimensional data, and infrastructure for centralized or federated data access to imaging and related data. She has been a PI in multiple multicenter projects (e.g., Heart-Brain Connection consortium, Netherlands Consortium of Dementia Projects, TAP-Dementia). In EUCAIM, she co-leads WP4. Esther also works at Health-RI as imaging data coordinator of the architecture team. Personal website:

Stefan Klein

Stefan Klein (PhD) is associate professor in Medical Image Analysis at the Department of Radiology and Nuclear Medicine, Erasmus MC. He is co-principal developer of a widely used open-source software package for medical image registration, called Elastix, was co-organiser of three grand challenges (CADDementia, TADPOLE, KNOAP2020), general chair of the WBIR2018 conference, and is Associate-Editor of the IEEE Transactions in Medical Imaging. His current research interests include machine learning for medical image analysis, image registration, image reconstruction and quantification, and disease progression modelling, with applications in oncology, ophthalmology, musculoskeletal disorders, and neurodegenerative disease. Publication list: Google scholar profile. Besides performing research, Stefan is also active in setting up infrastructures that facilitate research in medical imaging, and he has for instance initiated a national Health-RI research archive for medical imaging data, currently used by numerous multi-centre imaging studies in the Netherlands) and is Manager of the Health-RI Imaging Community ( Also on a European level, he was/is involved in several research infrastructure related projects, and he is director of the Euro-BioImaging Population Imaging node.

Marcel Koek

Marcel Koek is the team lead of the IT Infrastructure Group (the Infra Group), which is part of the Biomedical Imaging Group Rotterdam (BIGR) at the department of Radiology & Nuclear Medicine of Erasmus MC. The aim of the Infra Group is to improve the efficiency in medical imaging research and healthcare through leveraging advanced technologies and software engineering practices. The team consists of Research Software Engineers connecting the space between research and software engineering. The Infra Group is part of the Population Flagship Node in Euro-BioImaging, and have active roles in the Health-RI Imaging , RSE-NL and international XNAT Communities. The Infra Group have (co-)organised a large number of hackathons, workshops and community meetings bringing RSE’s and researchers together to work on and discuss image analysis infrastructures, XNAT, and consolidation image analysis methods. In EUCAIM Marcel is T4.4 leader together with UPV, coordinating the operationalisation of the Storage and AI Development infrastructure.

Martijn Starmans

Martijn Starmans (PhD) is postdoctoral researcher in AI for Medical Image Analysis in Oncology at the Department of Radiology and Nuclear Medicine, Erasmus MC. His main research interest is the use of radiomics and deep learning to improve the diagnostic work-up in oncology. To this end, he focusses on exploiting automated machine learning and meta-learning to generalize methods across applications. To evaluate this generalization, he works on a variety of clinical applications (e.g. sarcoma, liver cancer, colorectal cancer, bladder cancer, melanoma, cardiology, neuroendocrine tumors) with various clinicians. He is part of various international consortia, e.g., lead of the platform work package of the Horizon 2020 EuCanImage project, and external advisor of the Horizon Health RadioVal project. He has co-initiated and is co-leading three consortia on AI for specific cancer types (sarcoma, liver, colorectal liver metastases). As supporter of open science, he has released software for an automatic adaptive radiomics framework and a large public database of 930 patients ( Besides research, Martijn is active in education, including co-initiating and developing two courses, which he is still teaching yearly. Website:

Join the EUCAIM Consortium

Open Call for New Beneficiaries

We’re inviting new partners to enhance our pan-European infrastructure for cancer images and artificial intelligence.

Whether you’re a data holder with valuable cancer images or an innovator developing AI tools for precision medicine, this is your chance to contribute to a groundbreaking project.

Apply by 10 June 2024!

Open Call Webinar

We recently hosted a webinar with more details for prospective applicants to the open call. A recording is available.

Our open Call for new collaborators
launches in April 2024

Opportunities for data holders & AI developers to contribute await! Let‘s join forces to enhance cancer diagnosis and treatment

Be the first to know and apply!

March 14, 10:00-11:30 aM CET



Explore the potential for AI-driven cancer care advancements!
Learn how to access and utilize our federated cancer image repository. The webinar is for AI Innovators & Data Providers interested in the platform and will feature an introduction to EUCAIM & Cancer Image Europe and a demonstration of data exploration & access.

Survey Invitation

Join Leading Experts In Shaping AI In Cancer

EUCAIM is looking for your feedback! We have recently published a Stakeholder Survey in order to reach out to potential end-users and stakeholders. We believe that your insights could significantly contribute to understanding the expectations of potential users and identifying the essential aspects that stakeholders find crucial for future engagement and collaboration with the platform.

Therefore, we would like to invite you to participate in the Stakeholder Survey about the Cancer Image Europe platform.

Completing the survey will take approximately 10 minutes. Your participation is crucial to the success of this project, and we deeply appreciate your expertise in shaping the future of cancer imaging and treatment.