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M W Marcellin

Publications and source records attributed to M W Marcellin.

2 recordsLinked to original sources

Adaptive reconstruction of phased array MR imagery.

An adaptive implementation of the spatial matched filter and its application to the reconstruction of phased array MR imagery is described. Locally relevant array correlation statistics for the NMR signal and noise processes are derived directly from the set of complex individual coil images, in the form of sample correlation matrices. Eigen-analysis yields an optimal filter vector for the estimated signal and noise array correlation statistics. The technique enables near-optimal reconstruction of multicoil MR imagery without a-priori knowledge of the individual coil field maps or noise correlation structure. Experimental results indicate SNR performance approaching that of the optimal matched filter. Compared to the sum-of-squares technique, the RMS noise level in dark image regions is reduced by as much as the square root of N, where N is the number of coils in the array. The technique is also effective in suppressing localized motion and flow artifacts.

Artifacts↗

Image restoration with the Viterbi algorithm.

The Viterbi algorithm (VA) is known to given an optimal solution to the problem of estimating one-dimensional sequences of discrete-valued pixels corrupted by finite-support blur and memoryless noise. A row-by-row estimation along with decision feedback and vector quantization is used to reduce the computational complexity of the VA and allow the estimation of two-dimensional images. This reduced-complexity VA (RCVA) is shown to produce near-optimal estimation of random binary images. In addition, simulated restorations of gray-scale images show the RCVA estimates to be an improvement over the estimates obtained by the conventional Wiener filter (WF). Unlike the WF, the RCVA is capable of superresolution and is adaptable for use in restoring data from signal-dependent Poisson noise corruption. Experimental restorations of random binary data gathered from an optical imaging system support the simulations and show that the RCVA estimate has fewer than one third of the errors of the WF estimate.

Algorithms↗