TY - JOUR
T1 - Empowering cancer research in Europe
T2 - the EUCAIM cancer imaging infrastructure
AU - Martí-Bonmatí, Luis
AU - Blanquer, Ignacio
AU - Tsiknakis, Manolis
AU - Tsakou, Gianna
AU - Martinez, Ricard
AU - Capella-Gutierrez, Salvador
AU - Zullino, Sara
AU - Meszaros, Janos
AU - Bron, Esther E.
AU - Gelpi, Jose Luis
AU - Riklund, Katrine
AU - Chaabane, Linda
AU - Schlemmer, Heinz Peter
AU - Aznar, Mario
AU - Serrano Candelas, Patricia
AU - Gordebeke, Peter
AU - Hierath, Monika
AU - Scollen, Serena
AU - Martin-Sanchez, Fernando
AU - García, Oscar Gil
AU - Sandberg, Nils
AU - Penzkofer, Tobias
AU - Seebohm, Annabel
AU - Gazinska, Patrycja
AU - Haybaeck, Johannes
AU - Pallocca, Matteo
AU - Huys, Isabelle
AU - Dudova, Zdenka
AU - Holub, Petr
AU - França, Manuela
AU - Rosell Tejada, José Miguel
AU - Humbert, Olivier
AU - Hernandez-Ferrer, Carles
AU - Bobowicz, Maciej
AU - Fuhrmann, Patrick
AU - Sousa Pinto, Cátia
AU - Vos, Wim
AU - Persson, Bengt
AU - Marx, Gernot
AU - Lambin, Philippe
AU - Neri, Emanuele
AU - Rückert, Daniel
AU - Van den Bulcke, Marc
AU - van Ginneken, Bram
AU - Alberich-Bayarri, Angel
AU - Heese, Harald
AU - Beets-Tan, Regina
AU - Catalano, Carlo
AU - Saint-Aubert, Laure
AU - Hedlund, Joel
AU - European Society of Radiology
AU - EUCAIM Consortium
N1 - Funding Information:
EUCAIM is co-funded by the European Union under Grant Agreement 101100633. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.
Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12/1
Y1 - 2025/12/1
N2 - Abstract: Artificial intelligence (AI) is a powerful technology with the potential to disrupt cancer detection, diagnosis and treatment. However, the development of new AI algorithms requires access to large and complex real-world datasets. Although such datasets are constantly being generated, access to them is limited by data fragmentation across numerous repositories and sites, heterogeneity, lack of annotations, and potential privacy issues. The European Cancer Imaging Initiative is a flagship of Europe’s Beating Cancer Plan, aiming to unlock the power of AI for cancer patients, clinicians, and researchers by establishing a federated European infrastructure for cancer images through the EU-funded EUropean Federation for CAncer IMages (EUCAIM) project. This infrastructure, called Cancer Image Europe, builds on the AI for Health Imaging network (AI4HI), established European Research Infrastructures (Euro-BioImaging, BBMRI-ERIC, EATRIS, ECRIN, and ELIXIR), and numerous related partners providing access to research tools, images, and related clinical, pathology and molecular data. The infrastructure targets clinicians, researchers, and innovators by providing the means to develop and validate data-intensive AI-based and other IT-enabled clinical decision-making systems supporting precision medicine. Common data models, including a linking hyperontology, quality standards, compliance with the FAIR (Findability, Accessibility, Interoperability and Reusability) principles, data annotation, curation and anonymization services are provided to ensure data quality and interoperability, consistency and privacy. In summer 2024, the EUCAIM project released the first prototype of an EU-wide infrastructure, with a comprehensive dashboard integrating applications for dataset discovery, federated search, data access request, metadata harvesting, annotation, secure processing environments and federated processing. Critical relevance statement: EUCAIM’s federated infrastructure for cancer image data advances medical research and related AI development in Europe. It addresses the current fragmentation and heterogeneity of data repositories is legally compliant, and facilitates collaboration among clinicians, researchers, and innovators. Key Points: AI solutions to advance cancer care rely on large, high-quality real-world datasets. EUCAIM’s federated infrastructure for cancer image data empowers cancer research in Europe. It provides access to research tools, images, and related clinical, pathology and molecular data.
AB - Abstract: Artificial intelligence (AI) is a powerful technology with the potential to disrupt cancer detection, diagnosis and treatment. However, the development of new AI algorithms requires access to large and complex real-world datasets. Although such datasets are constantly being generated, access to them is limited by data fragmentation across numerous repositories and sites, heterogeneity, lack of annotations, and potential privacy issues. The European Cancer Imaging Initiative is a flagship of Europe’s Beating Cancer Plan, aiming to unlock the power of AI for cancer patients, clinicians, and researchers by establishing a federated European infrastructure for cancer images through the EU-funded EUropean Federation for CAncer IMages (EUCAIM) project. This infrastructure, called Cancer Image Europe, builds on the AI for Health Imaging network (AI4HI), established European Research Infrastructures (Euro-BioImaging, BBMRI-ERIC, EATRIS, ECRIN, and ELIXIR), and numerous related partners providing access to research tools, images, and related clinical, pathology and molecular data. The infrastructure targets clinicians, researchers, and innovators by providing the means to develop and validate data-intensive AI-based and other IT-enabled clinical decision-making systems supporting precision medicine. Common data models, including a linking hyperontology, quality standards, compliance with the FAIR (Findability, Accessibility, Interoperability and Reusability) principles, data annotation, curation and anonymization services are provided to ensure data quality and interoperability, consistency and privacy. In summer 2024, the EUCAIM project released the first prototype of an EU-wide infrastructure, with a comprehensive dashboard integrating applications for dataset discovery, federated search, data access request, metadata harvesting, annotation, secure processing environments and federated processing. Critical relevance statement: EUCAIM’s federated infrastructure for cancer image data advances medical research and related AI development in Europe. It addresses the current fragmentation and heterogeneity of data repositories is legally compliant, and facilitates collaboration among clinicians, researchers, and innovators. Key Points: AI solutions to advance cancer care rely on large, high-quality real-world datasets. EUCAIM’s federated infrastructure for cancer image data empowers cancer research in Europe. It provides access to research tools, images, and related clinical, pathology and molecular data.
KW - Artificial intelligence
KW - Cancer research
KW - European Health Data Space
KW - Imaging
KW - Infrastructure
U2 - 10.1186/s13244-025-01913-x
DO - 10.1186/s13244-025-01913-x
M3 - Article
SN - 1869-4101
VL - 16
JO - Insights into Imaging
JF - Insights into Imaging
IS - 1
M1 - 47
ER -