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Abstract #2669

An Estimation Method for Improved Reconstruction of MR Signal Parameters in Unilateral Scanner

Elad Bergman1, Arie Yeredor1, Uri Nevo1

1Tel-Aviv University, Tel Aviv, Israel

This work shows the potential of post-processing estimation for SNR improvement in Unilateral NMR, aiding the use of such devices in bio-medical applications. We present a novel post-processing method to improve the SNR of the acquired signal in unilateral NMR scanners. We estimate the signal parameters from the noisy data with the weighted least square approach, and exploit more efficiently the inherently known characteristics of the NMR signal. The method was first develop and tested for T2 measurements with a CPMG-like sequence. Then, using a similar concept we further developed this method to improve the SNR of lateral sliceselective imaging scans.

Keywords

accelerate acquisition aiding allow amplitude amplitudes applications applied appropriate architecture assume averaging axis biological biomedical blue channel channels characteristics clinical coil complex components constant cost costs covariance criteria curve curves decay decaying defining depth derived described destructive developed devices dictated echoes efficiently encoded encoding error errors estimation evaluate evaluated every excitations excited exploit exploiting expression feasible fitted forces frequency generated glycerol gold gradient green imaginary implementation improve improved improvement independently indicate inherently inhomogeneity introduce known lateral least like linear logging long longitudinal matrix microns minimization minimizing model mouse need noise noisy none novel open original paraffin periods planar poor portability post potential previously problem processing real reconstructed reconstruction reduce reducing relatively remains repetitions respectively routinely sample samples scanner scanners schemes selective separate shape short significantly simulation since slice slices slow solving spatial spec square step straightforward suggest table thin tissue tool uniform unilateral valuable variance variation various vector versus white yielding