title: LMS-based active noise cancellation methods for fMRI using sub-band filtering.
abstract: We present application of adaptive LMS-based method using two different sub-band filtering techniques for active reduction of 3T-fMRI acoustic noise. Analysis and design of the sub-band filters are discussed based on the characteristics of the noise. Using the fMRI-brain scanner acoustic noise, performance of the methods are analyzed and compared for different number of sub-band filters.
authors.affiliation: Dept. of Electrical Engineering, University of Texas, Dallas, USA. ali.a.milani@student.utdallas.edu
authors.forename: Ali A
authors.initials: AA
authors.lastname: Milani
authors.forename: Issa
authors.initials: I
authors.lastname: Panahi
authors.forename: Richard
authors.initials: R
authors.lastname: Briggs
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001931:Brain Mapping / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009622:Noise / Q000517:prevention & control*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity