tfmri.recon.partial_fourier

partial_fourier(kspace, factors, preserve_phase=None, return_kspace=False, return_complex=None, method='zerofill', **kwargs)

Reconstructs an MR image using partial Fourier methods. (deprecated arguments)

Deprecated: SOME ARGUMENTS ARE DEPRECATED: (return_complex). They will be removed after 2022-09-01. Instructions for updating: Use argument preserve_phase instead.

Parameters

  • kspace – A Tensor. The k-space data. Must have type complex64 or complex128. Must have shape [..., *K], where K are the spatial frequency dimensions. kspace should only contain the observed data, without zero-filling of any kind.

  • factors – A list of floats. The partial Fourier factors. There must be a factor for each spatial frequency dimension. Each factor must be between 0.5 and 1.0 and indicates the proportion of observed k-space values along the specified dimensions.

  • preserve_phase –

    A boolean. If True, keeps the phase information in the reconstructed images. Although it is not possible to reconstruct high-frequency phase details from an incomplete k-space, a low resolution phase map can still be recovered. If True, the output images will be complex-valued.

  • return_kspace –

    A boolean. If True, returns the filled k-space instead of the reconstructed images. This is always complex-valued.

  • return_complex –

    A boolean. If True, returns complex instead of real-valued images.

  • method – A string. The partial Fourier reconstruction algorithm. Must be one of "zerofill", "homodyne" (homodyne detection method) or "pocs" (projection onto convex sets method).

  • **kwargs – Additional method-specific keyword arguments. See Notes for

  • details. –

Returns

A Tensor with shape [..., *S] where S = K / factors. Has type kspace.dtype if either preserve_phase or return_kspace is True, and type kspace.dtype.real_dtype otherwise.

Notes

This function accepts some method-specific arguments:

  • method="zerofill" accepts no additional arguments.

  • method="homodyne" accepts the following additional keyword arguments:

    • weighting_fn: An optional string. The weighting function. Must be one of "step", "ramp". Defaults to "ramp". "ramp" helps mitigate Gibbs artifact, while "step" has better SNR properties.

  • method="pocs" accepts the following additional keyword arguments:

    • tol: An optional float. The convergence tolerance. Defaults to 1e-5.

    • max_iter: An optional int. The maximum number of iterations of the POCS algorithm. Defaults to 10.

References

1

Noll, D. C., Nishimura, D. G., & Macovski, A. (1991). Homodyne detection in magnetic resonance imaging. IEEE transactions on medical imaging, 10(2), 154-163.

2

Haacke, E. M., Lindskogj, E. D., & Lin, W. (1991). A fast, iterative, partial-Fourier technique capable of local phase recovery. Journal of Magnetic Resonance (1969), 92(1), 126-145.