TL;DR
- Joint FAIMI, BRIDGE, and EPIMI workshop at MICCAI 2026 (Strasbourg, France)
- Date: TBC
- Location: TBC (in person only)
- Full joint organizer list will be posted here as soon as it is finalized
Workshop Overview
FAIMI has again been selected to host a workshop at MICCAI 2026. This year, the workshop is being organized jointly with BRIDGE (Regulatory Evaluation) and EPIMI (Ethics & Philosophy).
The joint workshop brings together three connected perspectives needed for trustworthy medical AI:
- FAIMI: fairness, bias identification, and bias mitigation in medical imaging AI
- BRIDGE: regulatory science and evaluation for emerging AI paradigms
- EPIMI: ethical and philosophical analysis of new challenges in medical imaging AI
At present, the organizer list below reflects the FAIMI team coordinating this page and the FAIMI-led workshop activities. The full combined FAIMI + BRIDGE + EPIMI organizer list will be added here once confirmed.
Call for Papers
We invite the submission of papers for
FAIMI: The MICCAI 2026 Workshop on Fairness of AI in Medical Imaging.
Over the past several years, research on fairness, equity, and accountability in the context of machine learning has extensively demonstrated ethical risks in the deployment of machine learning systems in critical infrastructure, such as medical imaging. The FAIMI workshop aims to encourage and emphasize research on and discussion of fairness of AI within the medical imaging domain. We therefore invite the submission of papers, which will be selected for oral or poster presentation at the workshop. Topics include but are not limited to:
- Assessment of bias in ML applications for medical imaging
- Healthcare inequalities and/or the role of ML in addressing these
- Discussion of definitions of fairness in medical contexts
- Discussion of applicability of fairness in medical contexts
- Bias mitigation strategies for ML/medical imaging
- Ethics of fairness for medical imaging and medicine
- Legal/regulatory considerations of fairness
- Causality and fairness in medical imaging
- The interplay of algorithmic and dataset bias
The workshop proceedings will be published in the MICCAI workshops volumes of the Springer Lecture Notes Computer Science (LNCS) series. Papers should be anonymized and at most 8 pages plus at most 2 extra pages of references using the LNCS format. The review process is conducted in a double-blind manner, following MICCAI standards. Submissions are made in CMT.
Following the MICCAI paper submission guidelines, the submission of additional supplementary material is possible.
NEW Supplementary materials are limited to multimedia content (e.g., videos) as warranted by the technical application (e.g. robotics, surgery, ...). These files should not display any proofs, analysis, or additional results, and should not show any identification markers either. Violation of this guideline will lead to desk rejection. PDF files may not be submitted as supplementary materials in 2026 unless authors are citing a paper that has not yet been published. In such a case, authors are required to submit an anonymized version of the cited paper.
All supplementary material must be self-contained and zipped into a single file. Only the following formats are allowed: avi, mp4, wmv. We encourage authors to submit videos using an MP4 codec such as DivX contained in an AVI. A README text file must be included with each video specifying the exact codec used and a URL where the codec can be downloaded.
While the reviewers will have access to such supplementary material, they are under no obligation to review it, and the paper itself must contain all necessary information and illustrations for review purposes.
Dates
All times are 23:59 Pacific Time
Full Paper Deadline: July 1, 2026
Notification of Acceptance: July 31, 2026
Camera-ready Version: August 15, 2026
Workshop: September 27 or October 1, 2026
FAIMI Horizon Award
The FAIMI Horizon Award aims to provide financial support and highlight one talented early-career researcher attending the conference for the first time, with a special focus on individuals from diverse and underserved backgrounds.
The award offers a full scholarship to attend the FAIMI Workshop, creating a valuable opportunity to present research, engage with the global community, and build lasting professional networks.
Eligibility Criteria:
To be eligible for the FAIMI Horizon Award, the first author of the submitted paper must meet all of the following:
- The candidate must be a first-time attendee of the MICCAI conference.
- The candidate must be an early-career researcher, defined as a current student (undergraduate, master’s, PhD, or medical student), within two years of completing their terminal degree (i.e., MICCAI Young Scientists), or within four years of completing their terminal degree (i.e., Early-Career Scientists).
- The candidate should identify with one or more diverse or underserved backgrounds, such as being from an underrepresented gender or racial/ethnic group, having differing abilities, coming from a low- or lower-middle-income country, or residing in a country historically underrepresented at MICCAI. Candidates with other forms of social, cultural, or economic disadvantage are also encouraged to apply.
Please note: The MICCAI Registration and Travel Grants are intended to support in-person participation in the conference. If a selected grantee is unable to attend in person, the award will be offered to the next eligible candidate.
Current FAIMI Organizers
Aasa Feragen, DTU Compute, Technical University of Denmark
Andrew King, King’s College London
Ben Glocker, Imperial College London
Enzo Ferrante, CONICET, Universidad Nacional del Litoral
Eike Petersen, Fraunhofer Institute for Digital Medicine MEVIS
Esther Puyol-Antón, HeartFlow and King’s College London
Melanie Ganz-Benjaminsen, University of Copenhagen & Neurobiology Research Unit, Rigshospitalet
Veronika Cheplygina, IT University Copenhagen
Louisa Fay, Stanford University
Emma Stanley, Imperial College London
Gelei Xu, University of Notre Dame
Christopher Thomas Boland, DTU Compute, Technical University of Denmark
Tareen Dawood, DTU Compute, Technical University of Denmark
Contact
Please direct any inquiries related to the workshop or this website to faimi-organizers@googlegroups.com.