Paper doi abstract bibtex

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 ! 1) 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.

@article{larsson_snr-optimality_2003, title = {{SNR}-optimality of sum-of-squares reconstruction for phased-array magnetic resonance imaging}, volume = {163}, issn = {10907807}, url = {https://linkinghub.elsevier.com/retrieve/pii/S1090780703001320}, doi = {10.1016/S1090-7807(03)00132-0}, 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 ! 1) 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.}, language = {en}, number = {1}, urldate = {2022-03-31}, journal = {Journal of Magnetic Resonance}, author = {Larsson, Erik G. and Erdogmus, Deniz and Yan, Rui and Principe, Jose C. and Fitzsimmons, Jeffrey R.}, month = jul, year = {2003}, pages = {121--123}, }

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