Related Experiment Video
Updated: May 11, 2026

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition
Published on: January 5, 2024
Suppressing multi-channel ultra-low-field MRI measurement noise using data consistency and image sparsity
Fa-Hsuan Lin1, Panu T Vesanen, Yi-Cheng Hsu
1Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan. fhlin@ntu.edu.tw
Abstract:
Ultra-low-field (ULF) MRI (B 0 = 10-100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.
Related Concept Videos
NMR Spectrometers: Resolution and Error Correction
Magnetic Resonance Imaging
¹³C NMR: ¹H–¹³C Decoupling
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
Imaging Studies IV: Magnetic Resonance Imaging

