SIG Biomedical Image Analysis Challenges (SIG-BIAC)

Every year, hundreds of new computational methods are published in the field of biomedical image analysis. For a long time, validation and evaluation of new algorithms was based on the authors’ private data sets, rendering fair and direct comparison of solutions impossible. In the meantime, common research practice has changed and involves the organization of international competitions (‘challenges’) that allow for comparative benchmarking algorithms in a controlled environment. After almost 15 years of biomedical challenges at MICCAI, we have carefully analyzed and critically questioned common practice related to the design and organization of biomedical challenges. Given this analysis, the mission of the Special Interest Group on Biomedical Image Analysis Challenges (SIG-BIAC) is to bring biomedical image analysis challenges to the next level of quality. In this process, in line with the ‘FAIR Guiding Principles for scientific data management and stewardship’, we are committed to Findability, Accessibility, Interoperability, and Reuse of digital assets, as well as to openness, transparency, and knowledge dissemination among diverse academic, clinical, and industrial research groups.


Best practices for the MICCAI community: The SIG will have the potential to build consensus regarding standards and best practices in the field, by fostering inclusively and integrating the expertise of the minor and major SIG-specific laboratories in academia and industry, from around the world. This, in turn, has the potential to lead to better quality,  reproducibility, interpretability, and transparency of benchmarking studies.

Leading role in method benchmarking: Major machine learning and related medical imaging conferences are increasingly attracting submission from researchers that were traditionally heavily involved in MICCAI. However, best practices with respect to benchmarking in the biomedical image analysis domain requires credibility with respect to the target domain (biomedicine). The MICCAI society is thus in a unique position to establish itself as the international lead organization with respect to the systematic benchmarking of biomedical image analysis algorithms.

Assistance in challenge-related aspects: The SIG will assist MICCAI in handling challenge-related aspects, such as the review of applications for challenge organization or endorsement.


The SIG-BIAC Board builds upon the MICCAI challenge working group, founded in summer 2018 and has the following members:


Lena Maier-Hein (President)

Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany Read more 


Anne Martel

Department of Medical Biophysics, University of Toronto, Ontario, Canada, Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada Read more 



Michal Kozubek

Centre for Biomedical Image Analysis, Masaryk University, Brno, Czech Republic Read more


Spyridon (Spyros) Bakas (Treasurer)

Center for Biomedical Image Computing & Analytics (CBICA), Perelman School of Medicine, University of Pennsylvania, Philadelphia, US Read more



Bennett Landman

Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA Read more 



Annette Kopp-Schneider

Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany Read more



Annika Reinke (Secretary)

Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany Read more