Performance of Squid Sensor Arrays for Mri of the Brain

Introduction While the state of the art in MRI has moved towards stronger magnetic fields, another approach has emerged, where the precession field is typically around 100 μT [1]. The signal is detected using a superconducting quantum interference device (SQUID), which outperforms an induction coil by orders of magnitude in sensitivity at kHz frequencies and below [2]. This ultra-low-field MRI (ULF MRI) has advantages, for instance, in better T1 contrast and compatibility with other techniques such as magnetoencephalography (MEG) [1]. In MEG, magnetic signals due to neuronal activity are detected by an array of SQUID sensors. A present EU-funded project is developing a hybrid MEG-MRI scanner [3]. MEG-style 'whole-head' sensor arrays can improve the ULF-MRI signal-to-noise ratio (SNR), which is still insufficient for practical applications.