title: Field-inhomogeneity-corrected low-rank filtering of magnetic resonance spectroscopic imaging data.
abstract: Low signal-to-noise ratio has been a major problem in magnetic resonance spectroscopic imaging (MRSI). A low-rank approximation based denoising method has been recently proposed to address this problem by exploiting the partial separability properties of MRSI data. However, field inhomogeneity, an unavoidable complication in practice, can violate the partial separability assumption and thus degrade the denoising performance of the low-rank filtering method. This paper presents a field-inhomogeneity-corrected low-rank filtering method to achieve more robust denoising of practical MRSI data. In vivo experiment results have been used to demonstrate the effectiveness of the proposed method.
authors.forename: Yan
authors.initials: Y
authors.lastname: Liu
authors.forename: Chao
authors.initials: C
authors.lastname: Ma
authors.forename: Bryan
authors.initials: B
authors.lastname: Clifford
authors.forename: Fan
authors.initials: F
authors.lastname: Lam
authors.forename: Curtis L
authors.initials: CL
authors.lastname: Johnson
authors.forename: Zhi-Pei
authors.initials: ZP
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D059906:Neuroimaging / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D012984:Software