compute_mti_coefficients

compute_mti_coefficients#

mrinufft.extras.field_map.compute_mti_coefficients(field_map, readout_time, mask, L=-1, n_bins=1024, lazy=False)[source]#

Compute off-resonance correction coefficients using Mixed Time interpolator (MTI).

Parameters:

  • field_map (NDArray) – The field map (off-resonance map) in rad/s, If complex-valued, the real part is interpreted as R2* mapping. If real-valued this is the field inhomogeneities in Hz. and will be multiplied by \(2j\pi\)

  • readout_time (NDArray) – The vector of time points (in seconds) at which to compute phase evolution.

  • mask (NDArray) – Binary mask indicating object region for field map/statistics.

  • L (int, optional) – Number of virtual centers or basis functions retained (default is -1, automatically estimated).

  • n_bins (int, optional) – Number of histogram bins for off-resonance value clustering (default is 1000).

  • lazy (bool, default False) – If True, use a lazy evaluation scheme for the space interpolator C, saving memory.

Returns:

  • B (NDArray) – [L, nbins] phase basis matrix in the time domain.

  • C (NDArray) – [L, nt] interpolation matrix to transform weighted basis to phase at the time points; nt = len(readout_time).

  • E (NDArray) – [nbins, nt] exponential off-resonance phase matrix at input histogram bins.

References

D. C. Noll, C. H. Meyer, J. M. Pauly, D. G. Nishimura and A. Macovski, “A homogeneity correction method for magnetic resonance imaging with time-varying gradients,” in IEEE Transactions on Medical Imaging, vol. 10, no. 4, pp. 629-637, Dec. 1991, doi: 10.1109/42.108599

Note

This function uses numpy for all CPU arrays, and cupy for all on-gpu array. It will convert all its array argument to the respective array library. The outputs will be converted back to the original array module and device.

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