Ultra-low field and unconventional MRI.

A promising approach to portable MRI is operation at ultra-low magnetic field where cost-effective electromagnets become practical. MRI in the ultra-low field (ULF) regime —when the magnetic field used for signal detection is below 10 mT—is inherently challenging mainly due to intrinsically low Boltzmann polarization. We will discuss hardware methods to improve attainable SNR in the Johnston-noise-dominated regime of ULF using improved coils such as quadrature volume coils at 276 kHz (6.5 mT). We will also discuss our work to reduce noise and increase attainable information per unit time using compute-based approaches that leverage low-cost GPU. These include magnetic resonance fingerprinting (MRF) to enable multiple quantitative contrasts at ULF, and the use of our neural network deep learning approach, AUTOMAP (AUtomated TransfOrm by Manifold APproximation), to reconstruct highly-undersampled low SNR imaging data..