Leadership

Contact Information

Riccardo Lattanzi, PhD

Professor and Director of the Center for Biomedical Imaging, Radiology

I am a Professor of Radiology, Electrical and Computer Engineering, and Biomedical Engineering, and the Director of the Center for Biomedical Imaging. I also serve as the Director of training for CAI2R and as the Director of the PhD program in Biomedical Imaging and Technology of the Vilcek Institute of Graduate Biomedical Sciences at the NYU Grossman School of Medicine.

My research work lies at the boundary between physics, engineering and medicine. I investigate fundamental principles involving the interactions of radiofrequency electromagnetic fields with biological tissue to develop new techniques and technologies to improve the diagnostic power of MRI. My research group investigates performance limits in MRI, such as the ultimate intrinsic signal-to-noise ratio (SNR), which is the theoretically largest SNR for a given imaging task. Our broad aim is to gain physical insight to develop new MRI technology that achieves nearly optimal performance. Another area of interest is the application of compositional MRI of articular cartilage, three-dimensional modelling, and radiomics for the assessment of musculoskeletal disorders. I also work on the development of new methods for noninvasive mapping of electrical properties using MRI measurements.

I have been a recipient of several awards, including a Fulbright scholarship, the ISMRM I.I. Rabi Young Investigator Award and an NSF CAREER Award. I was a co-recipient of the 2023 Harold A. Wheeler Applications Prize Paper Award from the IEEE Transactions on Antennas and Propagation. I was selected as an Aspen Junior Fellow by the Aspen Institute Italia, a Young Leader by the Council for the United States and Italy, and a European Young Leader by Friends of Europe.

I received my laurea degree in electronic engineering from University of Bologna, my Master of Science in electrical engineering and computer science from MIT, and my Ph.D. in medical and electrical engineering from the Harvard-MIT Division of Health Sciences and Technology.

Research Projects

FireVoxel: Interactive Software for Multi-Modality Analysis of Dynamic Medical Images

FireVoxel is a freely distributed medical imaging analysis software developed at NYU Langone that provides powerful quantitative tools—especially for dynamic abdominal and genitourinary studies—and has become widely adopted in MRI research worldwide.

QUANTITATIVE MRI    SOFTWARE

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

Open-Source Software Tools for Rapid Radiofrequency Coil Modeling and Simulation in MRI

This project develops open-source, memory-efficient electromagnetic simulation tools using tensor decompositions and optimization techniques to improve RF coil modeling for ultra-high field MRI, enhancing image quality and safety while reducing computational and licensing barriers.

COILS    SIMULATIONS    SOFTWARE

Quantitative Methods for the Evaluation of Femoroacetabular Impingement Using Magnetic Resonance Imaging

This project aims to develop advanced, translation-ready quantitative MRI and radiomics methods to improve early diagnosis and evaluation of femoroacetabular impingement (FAI), enabling more reliable and reproducible assessments than standard radiologic approaches.

MSK    QUANTITATIVE MRI    RADIOMICS