title: Noise estimation in parallel MRI: GRAPPA and SENSE.
abstract: Parallel imaging methods allow to increase the acquisition rate via subsampled acquisitions of the k-space. SENSE and GRAPPA are the most popular reconstruction methods proposed in order to suppress the artifacts created by this subsampling. The reconstruction process carried out by both methods yields to a variance of noise value which is dependent on the position within the final image. Hence, the traditional noise estimation methods - based on a single noise level for the whole image - fail. In this paper we propose a novel methodology to estimate the spatial dependent pattern of the variance of noise in SENSE and GRAPPA reconstructed images. In both cases, some additional information must be known beforehand: the sensitivity maps of each receiver coil in the SENSE case and the reconstruction coefficients for GRAPPA.
authors.affiliation: LPI, ETSI Telecomunicación, Universidad de Valladolid, Spain. Electronic address: sanaja@tel.uva.es.
authors.forename: Santiago
authors.initials: S
authors.lastname: Aja-Fernández
authors.affiliation: LPI, ETSI Telecomunicación, Universidad de Valladolid, Spain. Electronic address: gvegsan@lpi.tel.uva.es.
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Vegas-Sánchez-Ferrero
authors.affiliation: LPI, ETSI Telecomunicación, Universidad de Valladolid, Spain. Electronic address: atriveg@lpi.tel.uva.es.
authors.forename: Antonio
authors.initials: A
authors.lastname: Tristán-Vega
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D015233:Models, Statistical; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio
keywords: GRAPPA; Multiple-coil; Noise estimation; Parallel imaging; SENSE