The VIC lab has developed a tool called MIAAIM (Multi-omics Image Alignment and Analysis by Information Manifolds) that integrates multiple sources of imaging data to generate a more comprehensive view of human health and disease. By combining complementary imaging modalities, this modular framework may help identify patterns and biomarkers that are not visible through a single data source alone. This type of multimodal analysis has the potential to strengthen disease characterization, improve risk stratification, and support more precise approaches to diagnosis, monitoring, and treatment decisions.
This effort is thanks to the collaboration of the Sîrbulescu, Poznansky, and Reeves lab teams, including Joshua Hess, PhD candidate at Cornell University, and Richard Dzeng, computational biologist, VIC and PhD candidate at Tufts University.
MGB press release: https://news.massgeneralbrigham.org/en/new-tool-combining-imaging-data-may-provide-health-insights
Publication: MIAAIM: Multi-omics image integration with dimensional reduction for tissue state mapping | PLOS Computational Biology
