Research focuses on developing analytic methods for biomedical data integration, with a particular interest in the spatial integration of radiology and pathology images. Such integrative methods may be applied to create comprehensive multi-scale representations of biomedical processes and pathological conditions, thus enabling their in-depth characterization. The radiology-pathology fusion allows the creation of rich spatial labels that can be used as input for advanced machine learning to predict the presence and aggressiveness of cancers.
