ImgGen

Radiogenomic analysis in gliomas

We are building Bayesian variable selection approaches to identify associations between molecular characteristics and imaging heterogeneity. These assocaitions are also studied while considering (by mimicking) the tumor growth process. We are specifically interested in radiological-imaging and the cancer driver-genes/pathways of lower grade gliomas. We are employing methods from geometric functional data analysis. We are also working on methods for compositional data to assess associations of genomics and the volumetric characteristics of the tumor.