title: Suppressing multi-channel ultra-low-field MRI measurement noise using data consistency and image sparsity.
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.
authors.affiliation: Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan. fhlin@ntu.edu.tw
authors.forename: Fa-Hsuan
authors.initials: FH
authors.lastname: Lin
authors.forename: Panu T
authors.initials: PT
authors.lastname: Vesanen
authors.forename: Yi-Cheng
authors.initials: YC
authors.lastname: Hsu
authors.forename: Jaakko O
authors.initials: JO
authors.lastname: Nieminen
authors.forename: Koos C J
authors.initials: KC
authors.lastname: Zevenhoven
authors.forename: Juhani
authors.initials: J
authors.lastname: Dabek
authors.forename: Lauri T
authors.initials: LT
authors.lastname: Parkkonen
authors.forename: Juha
authors.initials: J
authors.lastname: Simola
authors.forename: Antti I
authors.initials: AI
authors.lastname: Ahonen
authors.forename: Risto J
authors.initials: RJ
authors.lastname: Ilmoniemi
mesh_terms: D006225:Hand / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000592:standards* / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods / Q000592:standards*; D009778:Occipital Lobe / Q000033:anatomy & histology; D019047:Phantoms, Imaging / Q000592:standards; D059629:Signal-To-Noise Ratio