Bayesian 2014 - International Workshop on Bayesian and Graphical Models for Biomedical Imaging

The goal is to highlight the potential of using Bayesian or random field graphical models for advancing scientific research in biomedical image analysis. The program will consist of three keynote talks, from prominent figures in the community, and the presentation of previously unpublished and contributive papers.
We are looking for original, innovative and mathematically rigorous models and inference schemes for the analysis of medical image data. Emphasis will be placed on novel methodological approaches and interpretability with respect to the medical problem, while results will serve as proof-of-concept and illustration.
Topics of interest include but are not limited to plausible and realistic generative models, efficient inference strategies, model comparison and averaging, model uncertainty, modelling of multi-modal data, hierarchical graphical modelling and comparison to traditional/heuristic methods.
Potential applications cover the full scope of medical image analysis: segmentation, registration, classification, fusion, reconstruction, atlas construction, tractography, structural/functional modelling, and population analysis.
This workshop aims to bring together the probabilistic modelling community that works on medical image analysis. The objectives of this workshop differ from other workshops, e.g. machine learning in medical imaging, by having a stronger mathematical focus on the foundations of probabilistic modelling and inference. This forum will facilitate the presentation and detailed discussion of novel and speculative works, which may be outside the scope of the main conference, but are essential for the advancement of modelling and analysis of medical imaging data.