3D model of Tumor Habitat

Radiation necrosis vs. tumor recurrence using radiomics on routine MRI

Radiation necrosis vs. tumor recurrence using radiomics on routine MRI

Collaboration with GE Healthcare

Survival prediction in Glioblastoma patients using radiomics analysis

Radiogenomic analysis of brain tumors

Studying structural deformations in Glioblastoma to predict patient survival

Sex-specific Computational Histopathology Predicts Survival in High-Grade Gliomas Using Deep Learning

Lab Hangout

AI in Ophthalmology: GA lesion detection​

About Us

IDiA Lab develops artificial intelligence (AI), machine learning (ML), and statistical modeling approaches for translational applications in oncology and neurological disorders. Our primary focus is on advancing tools for disease prediction, prognosis, and treatment assessment. A key approach of research involves identifying radiomic (image-based) phenotypes from medical imaging and exploring their associations with genomics (radiogenomics) and histopathology (radiopathomics) to enhance disease characterization.

Please check the research page for specific projects and research focus of our group.