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News archive

EuCanImage presented at the 17th International Workshop on Breast Imaging in Chicago

EuCanImage joined LimkedIn Community!

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About the project

EuCanImage will build and demonstrate a GDPR-compliant and scalable platform for leveraging large-scale, high-quality and interoperable cancer imaging datasets adequately linked to biological and health cancer data. The platform will integrate advanced capabilities and new standards to develop and validate integrative decision support systems for precision oncology with increased clinical trust and adoption. The project consortium is an experienced and ambitious academic-industrial-clinical partnership, with a proven track record in data management, responsible data sharing, cancer imaging research, and AI for personalised medicine.

The key objectives are to:

Objective 1: Build a FAIR (Findable, Accessible, Inter-operable, Re-usable) cancer imaging platform linked to biological and health repositories for integrated multi-scale AI in clinical oncology.

Objective 2: Provide comprehensive and user-friendly data curation, annotation, and hosting tools, as well as training material, to promote future data deposition and scalability of the platform.

Objective 3: Build a multi-centre and multi-scale AI development platform for cancer imaging by leveraging the unique expertise of consortium members in radiomics, distributed learning and interpretable AI.

Objective 4: Build an AI assessment and benchmarking platform for multi-disciplinary and clinically-driven evaluation of image-based AI solutions for oncology care.

Objective 5: Develop the legal framework, as well as innovative solutions, that will enable responsible data sharing and enhanced Open Science within EuCanImage and the cancer research community.

Objective 6: Develop a platform that will ultimately contribute to addressing currently unmet clinical needs in personalised cancer care.

Objective 7: Disseminate the EuCanImage platform at large to create the largest community of data contributors as well as AI developers, by leveraging the consortium’s extensive channels and partnering associations.

Work Packages

The project is divided into eight work packages with their own theme.

Public deliverables

We’re making our research findings available free of charge for readers and are providing open access to public deliverables and reports.


Find all press publications, media, and our scientific publications here.

View our research results

Our scientific publications are published free of any restrictions on access. View our scientific publications and our public reports.

Press and media

Download all our promotional materials, such as flyers and folders, and read our press releases.


If you have additional questions or would like to receive more in-depth information on EuCanImage, don’t hesitate to get in touch with us!

Karim Lekadir

Dr. Karim Lekadir is the Director of the Artificial Intelligence in Medicine Lab at the Universitat de Barcelona (BCN-AIM) and the Project Coordinator of EuCanImage. He chairs the EuCanImage consortium and leads the project in scientific and technical aspects.

Jamilia Arykbaeva

Jamilia Arykbaeva is the Project Manager of EuCanImage. She holds a Master’s degree in Political Science and in Political and Electoral Analysis from the University of Granada and Pontificia Universidad Católica Mater Maestra (PUCMM).

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