Submission Details
We require all materials to be original and not previously published. The submitted and accepted abstract is what will get published – no changes to the abstract after its acceptance are allowed. Submissions that are substantially similar to versions that have been accepted or submitted in parallel to other conferences with proceedings are not allowed.
Imaging: Classification, object localization, segmentation, image registration, image reconstruction, image quality.
Natural Language: Radiology reports, protocols, workflow optimization, business operations.
Clinical Deployment and Validation: Benchmarks, bias and fairness, AI governance, quality assurance, prospective integration, continuous monitoring, cost analysis.
Toolkits, Infrastructure, Datasets, and Standards: Research toolkits, annotation software, data visualization, development and deployment platforms, compute architectures, novel hardware, cloud integration, emerging libraries and languages, standards.
Emerging Data Science Methods: Generative models, foundational models, one-shot and few-shot learning, weakly supervised learning, self-supervised learning, contrastive learning, clustering, active learning, federated and distributed learning, reinforcement learning, quantum computing.
Other: Any other machine learning in medical imaging-related topics that have not been covered above

Questions?
Testimonials
“SIIM and C-MIMI are always fantastic experiences, with the perfect blend of science, big picture discussions, and opportunities to network with people who are interested in chatting, including some of the most highly regarded people in the field.”
CMIMI Attendee