Systems and methods of deep learning for large-scale dynamic magnetic resonance image reconstruction

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United States of America

PATENT NO 12265145
APP PUB NO 20230194640A1
SERIAL NO

17642016

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Abstract

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A method for performing magnetic resonance imaging on a subject comprises obtaining undersampled imaging data, extracting one or more temporal basis functions from the imaging data, extracting one or more preliminary spatial weighting functions from the imaging data, inputting the one or more preliminary spatial weighting functions into a neural network to produce one or more final spatial weighting functions, and multiplying the one or more final spatial weighting functions by the one or more temporal basis functions to generate an image sequence. Each of the temporal basis functions corresponds to at least one time-varying dimension of the subject. Each of the preliminary spatial weighting functions corresponds to a spatially-varying dimension of the subject. Each of the final spatial weighting functions is an artifact-free estimation of the one of the one or more preliminary spatial weighting functions.

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Patent Owner(s)

Patent OwnerAddress
CEDARS-SINAI MEDICAL CENTER8700 BEVERLY BLVD LOS ANGELES CA 90048

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Chen, Yuhua Los Angeles, US 132 1656
Christodoulou, Anthony Los Angeles, US 9 3
Li, Debiao Los Angeles, US 40 240

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