Systems and methods for image reconstruction using variable-density spiral trajectory

    公开(公告)号:US09989611B2

    公开(公告)日:2018-06-05

    申请号:US14677877

    申请日:2015-04-02

    CPC classification number: G01R33/5611 G01R33/4818 G01R33/4824

    Abstract: In image reconstruction using a variable-density spiral trajectory, a method includes acquiring magnetic resonance (MR) data, which includes determining a multi-level undersampling pattern based on sampling distance and probability functions, and determining a desired variable-density spiral trajectory based on the undersampling pattern. Acquiring the MR data also includes generating spiral gradient waveforms based on the desired trajectory, and tracing a variable-density spiral trajectory using the spiral gradient waveforms. After tracing, the MR data can be sub-sampled based on the variable-density spiral trajectory. One or more images can be reconstructed based on the acquired MR data.

    Motion compensation for MRI imaging

    公开(公告)号:US11846692B2

    公开(公告)日:2023-12-19

    申请号:US17733967

    申请日:2022-04-29

    Abstract: Training a neural network to correct motion-induced artifacts in magnetic resonance images includes acquiring motion-free magnetic resonance image (MRI) data of a target object and applying a spatial transformation matrix to the motion-free MRI data. Multiple frames of MRI data are produced having respective motion states. A Non-uniform Fast Fourier Transform (NUFFT) can be applied to generate respective k-space data sets corresponding to each of the multiple frames of MRI; the respective k-space data sets can be combined to produce a motion-corrupted k-space data set and an adjoint NUFFT can be applied to the motion-corrupted k-space data set. Updated frames of motion-corrupted MRI data can be formed. Using the updated frames of motion corrupted MRI data, a neural network can be trained that generates output frames of motion free MRI data; and the neural network can be saved.

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