Projects

GRASP MRI

This project focuses on the ongoing development and clinical translation of GRASP MRI—a fast, motion-robust dynamic imaging method combining golden-angle radial sampling, compressed sensing, and parallel imaging—which has been widely adopted in clinical practice, expanded into advanced variants, and increasingly applied in both diagnostic and therapeutic settings.

BRAIN RAPID 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

In Vivo Insights into Aging-Related Small-Vessel Changes Using USPIO-Enhanced MRI

This project aims to develop an ultra-high-resolution USPIO-enhanced MRI technique to visualize the brain's microvascular architecture, quantify vascular density, and investigate age-related neurovascular changes, potentially advancing the understanding of microvascular aging and its role in neurologic disorders.

AGING BRAIN

Cloud MR: An Open-Source Software Framework to Democratize MRI Training and Research

This project aims to democratize MRI research by developing Cloud MR, an open-source virtual scanner platform accessible via web browser, enabling MRI experimentation, education, and development without the need for physical MRI machines.

COILS PULSE SEQUENCES SIMULATIONS SOFTWARE

Noninvasive Estimation of Electrical Properties from Magnetic Resonance Measurements

This project develops a three-pronged strategy—combining global inverse modeling, physics-informed neural networks, and vision transformers—to generate high-resolution maps of tissue electrical properties using MRI, with broad applications in medical imaging and treatment.

QUANTITATIVE MRI SIMULATIONS

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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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