Method for parallel image reconstruction using automatic...

Electricity: measuring and testing – Particle precession resonance – Using a nuclear resonance spectrometer system

Reexamination Certificate

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C324S309000

Reexamination Certificate

active

07053613

ABSTRACT:
The invention relates to a method of parallel imaging reconstruction in parallel magnetic resonance imaging reconstruction. Magnetic resonance data is acquired in parallel by an array of separate RF receiver coils. A reconstruction method based on Tikhonov regularization is presented to reduce the SNR loss due to geometric correlations in the spatial information from the array coil elements. In order to reduce the noise amplification of the reconstruction so-called “g-factor”, reference scans are utilized as a priori information of the final reconstructed image to provide regularized estimates for the reconstruction using the L-curve technique. According to the invention the method with the proposed L-curve approach was fully automatic and showed a significant reduction in average g-factors in the experimental images.

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patent: 6717406 (2004-04-01), Sodickson
Lin F-H, Kwong KK, Belliveau JW, Wald LL. “Parallel Imaging Reconstruction Using Automatic Regularization”, Magn Reson Med 2004; 51:559-567.
Hoge WS, Brooks DH, Madore B, Kyriakos W. “On the Regularization of SENSE and Space-RIP in Parallel MR Imaging”. IEEE Symposium on Biomedical Imaging (ISBI 2004). Apr. 15-18, 2004.
King KF, Angelos L. “SENSE Image Quality Improvement Using Matrix Regularization”. Proc Intl Soc Mag Reson Med 9 Glasgow, Scotland, 2001; p. 1771.
Sodickson DK. “Tailored SMASH Image Reconstructions for Robust in vivo Parallel MR Imaging”. Magn Reson Med 2000; 44:243-251.
Hansen C, “Analysis of discrete ill-posed problems by means of the L-curve”, SIAM Review, vol. 34, No. 4, pp. 561-580, Dec. 1992.
Kellman P, McVeigh ER, “SENSE coefficient calculation using adaptive regularization”, ISMRM Workshop on Minimum MR Data Acquisition Methods, Marco Island, FL USA, Oct. 20-21, 2001.

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