Vanderbilt University
Institute of Imaging Science
Colin McKnight, M.D.
Assistant Professor
The Glymphatic Pathway: A Neuroradiologist's Perspective
Zhe-Pei Liang, Ph.D.
Franklin W. Woeltge Professor, University of Illinois
"SPICY" MRIs: A Marriage of Spin Physics with Machine Learning for Ultrafast MRSI   (more ...)
"SPICY" MRIs: A Marriage of Spin Physics with Machine Learning for Ultrafast MRSI   (hide ...)

Magnetic resonance spectroscopic imaging (MRSI) has long been recognized as a powerful tool for non-invasive, label-free molecular imaging and a lot of outstanding work has been done over the past three decades, resulting in significant advances in MRSI data acquisition, pulse sequences, data processing, and image reconstruction. However, in spite of these enormous progresses, current MRSI technology still falls short of providing adequate spatial resolution, speed, and signal-to-noise ratio (SNR) for routine clinical and research applications. This talk will discuss our recent advances in overcoming the long-standing technical barriers for label-free molecular imaging using intrinsic MR signals. The ultrafast MRSI technology (known as SPICE: SPectroscopic Imaging by exploiting spatiospectral CorrElation), resulting from many years of research efforts, is based on a new approach to spatiospectral imaging, which includes rapid data acquisition, sparse sampling of (k, t)-space, constrained image reconstruction, and learning-based spectral quantification using spectral basis from quantum mechanical simulations. SPICE has demonstrated an unprecedented combination of resolution, speed and SNR for MRSI. In this talk, I will give an overview of SPICE and show some "SPICY" experimental results that we have obtained.