Symposium on Artifical Inteligence for Medical Imaging SAIMI

Overview

With the rise and influence of machine learning (ML) in medical application and the need to translate newly developed techniques into clinical practice, questions about safety and uncertainty over measurements and reported quantities have gained importance. Obtaining accurate measurements is insufficient, as one needs to establish the circumstances under which these values generalize, or give appropriate error bounds for these measures. This is becoming particularly relevant to patient safety as many research groups and companies have deployed or are aiming to deploy ML technology in clinical practice.

Details

In the last few years, machine learning (ML) techniques have permeated many aspects of the MICCAI community, leading to substantial progress in a wide range of applications ranging from image analysis to surgical assistance. However, in medical applications, algorithms ultimately assist life and death decisions, and translation of such innovations into practice requires a measure of safety. In practice, ML systems often face situations where the correct decision is ambiguous, and therefore principled mechanisms for quantifying uncertainty are required to envision potential practical deployment.

Format

This symposium will be held as an in-person event in Bern.

Scope

The goal of SAIMI is to provide the opportunity to meet and discuss research ideas with the local MICCAI/MIDL community around Switzerland. To this end, we invite short abstract submissions on the topics related to AI for medical image analysis. Topics of interests include (but are not limited to):

This symposium is non-archival, and we welcome submissions of preliminary results (work in progress), as well as work under submission or recently published work(publication date 2025 or 2026).Submissions will be reviewed in a double-blind manner. The aim of the review process is to determine (1) fit within the SAIMI scope, (2) quality of the abstract, (3) guide poster and spotlight talks selection.

Submission Format

We invite you to submit a 1-page abstract describing your work, following this structure: 1) Objective of the study, 2) Motivation & background, 3) Short description of methods, 4) Summary of main results, 5) Conclusion.

Author names, affiliations and acknowledgements, as well as any obvious phrasings or clues that can identify authors must be removed to ensure anonymity.

Note that the 1 page limit refers only to the main content. Including references and acknowledgements the submission may exceed 1 pages.

Please submit your abstract as a .pdf file, in Arial or Time New Roman, minimum 10pt font size. Figures or tables are allowed.

How to submit?

Please submit abstracts using the abstract submission system. The Microsoft CMT service is used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support. Submission Deadline: 30.04.2026.

Presentation

All accepted abstracts will be presented as a poster during the symposium day. Additionally, we will select a number of papers for oral presentation based on the reviewers' suggestions.

Registration

Registration will open soon.

Prices

Attending the event is free of charge. However, registration is mandatory.

In case of questions, please feel free to reach out!

anna.wundram@unilu.ch