The MICCAI 2026 Open Data Initiative has received a MICCAI Society Award for the Advancement of Health Equity. The project is led by Martijn P.A. Starmans and Kaouther Mouheb (from BIGR) and was recognized for its contribution to promoting equitable access and global participation in medical imaging research.
The MICCAI Society Awards for the Advancement of Health Equity recognize projects that address inequities in medical imaging and AI research. In 2026, the MICCAI Open Data Initiative was selected in the Europe category.
The initiative builds on previous MICCAI Open Data Sessions and addresses a key challenge in the field: the limited diversity of publicly available medical imaging datasets, which are predominantly sourced from high-income countries. This lack of diversity can restrict the generalizability and fairness of AI models used in healthcare.
To address this, the project provides targeted financial and logistical support to researchers—particularly those from low- and middle-income countries—to help them share medical imaging datasets that represent under-served diseases and populations. The initiative supports overcoming practical barriers such as limited infrastructure, legal or ethical constraints, and limited experience with data sharing.
The project will culminate in the 3rd MICCAI Open Data Session, highlighting exemplary datasets and fostering exchange within the MICCAI community. To support long-term sustainability, the initiative also includes the establishment of a MICCAI Open Data Special Interest Group (SIG) dedicated to open and inclusive research practices.
Project team
- Martijn P.A. Starmans (lead), Erasmus University Medical Center
- Apostolia Tsirikoglou, Karolinska Institutet
- Lidia Garrucho Moras, University of Barcelona
- Kaouther Mouheb, Erasmus University Medical Center
This award recognizes the leadership of Martijn and Kaouther and highlights the importance of coordinated community efforts to improve data diversity and promote more equitable, AI-driven healthcare innovation.
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