title: SNR-optimality of sum-of-squares reconstruction for phased-array magnetic resonance imaging.
abstract: We consider the commonly used "Sum-of-Squares" (SoS) reconstruction method for phased-array magnetic resonance imaging with unknown coil sensitivities. We show that the signal-to-noise ratio (SNR) in the image produced by SoS is asymptotically (as the input SNR--> infinity ) equal to that of maximum-ratio combining, which is the best unbiased reconstruction method when the coil sensitivities are known. Finally, we discuss the implications of this result.
authors.affiliation: Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA. larsson@dsp.ufl.edu
authors.forename: Erik G
authors.initials: EG
authors.lastname: Larsson
authors.forename: Deniz
authors.initials: D
authors.lastname: Erdogmus
authors.forename: Rui
authors.initials: R
authors.lastname: Yan
authors.forename: Jose C
authors.initials: JC
authors.lastname: Principe
authors.forename: Jeffrey R
authors.initials: JR
authors.lastname: Fitzsimmons
mesh_terms: D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D016018:Least-Squares Analysis; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D015233:Models, Statistical; D011786:Quality Control; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic; D013269:Stochastic Processes