Dr. Matt Rosen is a physicist, tool-builder and inventor whose research bridges the spectrum from fundamental physics to applied bioimaging work in the field of MRI. He established the Low-Field MRI and Hyperpolarized Media Laboratory at the Athinoula A. Martinos Center for Biomedical Imaging to focus on the continued development of new hyperpolarization methods and MRI-based tools.
The Rosen Lab focuses on new methods and tools to enable unconventional approaches to MRI scanner construction. This includes the development of new acquisition strategies for robust ultra-low magnetic field implementations of MRI focused on brain imaging. The laboratory also explores opportunities provided by hyperpolarization including in vivo Overhauser DNP, SABRE and spin-exchange optical pumping. The lab creates new quantitative strategies for the acquisition and the reconstruction of highly undersampled imaging data including neural network deep learning-based approaches such as AUTOMAP that leverage low-cost scalable-compute. Dr. Rosen co-directs the Center for Machine Learning at the Martinos Center.
Education
PhD in Physics, University of Michigan, Ann Arbor
Select Publications
[1] K. N. Sheth, M. H. Mazurek, M. M. Yuen, B. A. Cahn, J. T. Shah, A. Ward, J. A. Kim, E. J. Gilmore, G. J. Falcone, N. Petersen, K. T. Gobeske, F. Kaddouh, D. Y. Hwang, J. Schindler, L. Sansing, C. Matouk, J. Rothberg, G. Sze, J. Siner, M. S. Rosen, S. Spudich, and W. T. Kimberly, “Assessment of Brain Injury Using Portable, Low-Field Magnetic Resonance Imaging at the Bedside of Critically Ill Patients,” JAMA Neurol, Sep. 2020.
https://jamanetwork.com/journals/jamaneurology/fullarticle/2769858
[2] D. E. J. Waddington, T. Boele, R. Maschmeyer, Z. Kuncic, and M. S. Rosen, “High-sensitivity in vivo contrast for ultra-low field magnetic resonance imaging using superparamagnetic iron oxide nanoparticles,” Science Advances, vol. 6, no. 29, p. eabb0998, Jul. 2020.
https://advances.sciencemag.org/content/6/29/eabb0998
[3] B. Zhu, J. Z. Liu, S. F. Cauley, B. R. Rosen, and M. S. Rosen, “Image reconstruction by domain-transform manifold learning ,” Nature, vol. 555, no. 7697, pp. 487–492, Mar. 2018.
https://www.nature.com/articles/nature25988
[4] M. Sarracanie, C. D. LaPierre, N. Salameh, D. E. J. Waddington, T. Witzel, and M. S. Rosen, “Low-Cost High-Performance MRI,” Sci Rep, vol. 5, no. 1, p. 15177, Oct. 2015.
https://www.nature.com/articles/srep15177
Highlights
Co-founder: Hyperfine Research, BlinkAI, Vizma Life Sciences, Intact Data Services