Projects

Improving the Efficacy of Ultra-Low-Field MRI Using AI

This project aims to develop AI methods to improve the image quality of ultra-low-field MRI to enhance the mobility, accessibility, and efficiency of MRI in clinical radiology and neuroscientific research.

AI   BRAIN

Data-Driven Learning Framework for Fast Quantitative Knee Joint Mapping

This project leverages advanced machine learning and deep learning to optimize T2 and T1rho mapping for knee osteoarthritis (OA), aiming to accelerate MRI techniques and enable earlier detection of cartilage degeneration.

AI   MSK   QUANTITATIVE MRI

Prediction Models of Knee Osteoarthritis Incidence and Progression using Deep Learning

This project develops and validates deep-learning models that analyze clinical and imaging data to predict individuals' five-year risk of knee osteoarthritis progression and total knee replacement, aiming to enable early intervention and personalized treatment.

AI   MSK

Researchers at the Center for Biomedical Imaging at NYU Langone Health develop transformative imaging technologies to advance basic science and address unsolved clinical problems.

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