Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure
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, acces...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-02-01
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| Series: | Insights into Imaging |
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| Online Access: | https://doi.org/10.1186/s13244-025-01913-x |
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| author | Luis Martí-Bonmatí Ignacio Blanquer Manolis Tsiknakis Gianna Tsakou Ricard Martinez Salvador Capella-Gutierrez Sara Zullino Janos Meszaros Esther E. Bron Jose Luis Gelpi Katrine Riklund Linda Chaabane Heinz-Peter Schlemmer Mario Aznar Patricia Serrano Candelas Peter Gordebeke Monika Hierath the EUCAIM Consortium European Society of Radiology |
| author_facet | Luis Martí-Bonmatí Ignacio Blanquer Manolis Tsiknakis Gianna Tsakou Ricard Martinez Salvador Capella-Gutierrez Sara Zullino Janos Meszaros Esther E. Bron Jose Luis Gelpi Katrine Riklund Linda Chaabane Heinz-Peter Schlemmer Mario Aznar Patricia Serrano Candelas Peter Gordebeke Monika Hierath the EUCAIM Consortium European Society of Radiology |
| author_sort | Luis Martí-Bonmatí |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b3c0910fc8e3479b8bae006d52f0c23c |
| institution | OA Journals |
| issn | 1869-4101 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Insights into Imaging |
| spelling | doaj-art-b3c0910fc8e3479b8bae006d52f0c23c2025-08-20T02:01:30ZengSpringerOpenInsights into Imaging1869-41012025-02-0116111010.1186/s13244-025-01913-xEmpowering cancer research in Europe: the EUCAIM cancer imaging infrastructureLuis Martí-Bonmatí0Ignacio Blanquer1Manolis Tsiknakis2Gianna Tsakou3Ricard Martinez4Salvador Capella-Gutierrez5Sara Zullino6Janos Meszaros7Esther E. Bron8Jose Luis Gelpi9Katrine Riklund10Linda Chaabane11Heinz-Peter Schlemmer12Mario Aznar13Patricia Serrano Candelas14Peter Gordebeke15Monika Hierath16the EUCAIM ConsortiumEuropean Society of RadiologyBiomedical Imaging Research Group, Instituto de Investigación Sanitaria La FeUniversitat Politècnica de ValènciaFoundation for Research and Technology, HellasMaggioli SPA, Research and Development LabUniversitat de ValènciaBarcelona Supercomputing CenterEATRIS ERICCenter for IT and IP Law, KU LeuvenBiomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center RotterdamUniversitat De BarcelonaDepartment of Diagnostics and Interventions, Umea UniversitetEURO-BIOIMAGING ERIC, Med-Hub, Institute of Biostructures and Bioimaging (IBB), Italian National Research Council (CNR)Division of Radiology, German Cancer Research Center (DKFZ)Matical InnovationBiomedical Imaging Research Group, Instituto de Investigación Sanitaria La FeEIBIR Gemeinnutzige Gmbh Zur Forderung Der Erforschung Der Biomedizinischen BildgebungEIBIR Gemeinnutzige Gmbh Zur Forderung Der Erforschung Der Biomedizinischen BildgebungAbstract 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.https://doi.org/10.1186/s13244-025-01913-xCancer researchImagingInfrastructureArtificial intelligenceEuropean Health Data Space |
| spellingShingle | Luis Martí-Bonmatí Ignacio Blanquer Manolis Tsiknakis Gianna Tsakou Ricard Martinez Salvador Capella-Gutierrez Sara Zullino Janos Meszaros Esther E. Bron Jose Luis Gelpi Katrine Riklund Linda Chaabane Heinz-Peter Schlemmer Mario Aznar Patricia Serrano Candelas Peter Gordebeke Monika Hierath the EUCAIM Consortium European Society of Radiology Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure Insights into Imaging Cancer research Imaging Infrastructure Artificial intelligence European Health Data Space |
| title | Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure |
| title_full | Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure |
| title_fullStr | Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure |
| title_full_unstemmed | Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure |
| title_short | Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure |
| title_sort | empowering cancer research in europe the eucaim cancer imaging infrastructure |
| topic | Cancer research Imaging Infrastructure Artificial intelligence European Health Data Space |
| url | https://doi.org/10.1186/s13244-025-01913-x |
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