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SYSTEM AND METHOD FOR SPARSE IMAGE RECONSTRUCTION UTILIZING NULL DATA CONSISTENCY
SYSTEM AND METHOD FOR SPARSE IMAGE RECONSTRUCTION UTILIZING NULL DATA CONSISTENCY
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机译:利用空数据一致性稀疏图像重建的系统和方法
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摘要
A method is provided that includes acquiring coil data from a magnetic resonance imaging device. The coil data includes undersampled k-space data. The method includes processing the coil data using an image reconstruction technique to generate an initial undersampled image. The method includes generating a reconstructed image based on the coil data, the initial undersampled image, and multiple iterative blocks of a residual deep-learning image reconstruction network. A first iterative block of the residual deep-learning image reconstruction network receives the initial undersampled image. Each of the multiple iterative blocks includes a data-consistency unit that preserves the fidelity of the coil data in a respective output of a respective iterative block utilizing zeroed data consistency. The initial undersampled image is added to an output of the last iterative block via a residual connection. The residual deep-learning image reconstruction network is a neural network trained using previously acquired coil data.
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