Merging imaging modalities is increasingly important for biomedical questions related to time and space scales including function and anatomy. Integrating modalities from multiple scales can assist with understanding development and function, disease, diagnosis and treatment. This workshop will bring together researchers who are attempting to combine and integrate different imaging modalities to better understand anatomy, function and disease from the cellular to organ level.
Methodologies and challenges in combining imaging data from multiple sources, such as MRI, fMRI, DTI, PET, EEG, MEG, CT, ultrasound, NMR, x-ray diffraction, electron microscopy, proteomic and genomic data will be explored. Merging data from different modality time scales (functional time scales from nanoseconds to minutes; developmental time scales from embryonic to adult) and space scales (from microns to millimeters) present many mathematical questions. Interpretation, analysis and modeling of multi-modality data as it applies to development, disease models and therapies will also be explored. The heterogeneity of the data presents many difficult challenges that are suited for mathematical exploration.
The focus will include brain and cardiac imaging related to multiscale and bioscale data collection, merging data, modeling and analysis. This workshop will be of interest to mathematicians working in areas of statistical analysis, PDE modeling, inverse problems, differential geometry, computational visualization and multiscale problems. Biomedical researchers interested in merging imaging modalities to investigate questions related to genomics, gene expression and biomarkers and the role they play in macroscopic function would benefit from this workshop.