https://iborz.org/

I develop computational and analytical methods for quantifying neurodegenerative and musculoskeletal disease from medical images, using deep learning, explainable AI, biophysical modeling, disease progression modeling, and multimodal biomarker integration. My current work focuses on tau PET quantification in Alzheimer’s disease, imaging heterogniety that distinguish multiple system atrophy from Parkinson’s disease, and MRI harmonization for multi-site studies. I created the THETA score, the first tau PET metric that captures the full spatial heterogeneity of tau spread across the brain. During my PhD, I applied similar quantitative approaches to musculoskeletal imaging, developing methods to detect hip osteoarthritis and fracture risk from clinical CT.