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deepmr.piecewise_fa

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deepmr.piecewise_fa#

deepmr.piecewise_fa(fa_ref=[1.5556, 70.0, 0.7778], length=[350, 230], recovery=300, head=None)[source]#

Design a multi-segment linear flip angle train.

The resulting train, similar to the one introduced by Gomez et al. [1], consists of len(fa_max) linear sections. The n-th sections starts at fa_ref[n] [deg], ends at fa_ref[n+1] [deg] and consists of length[n] pulses. The train is followed by a constant flip angle section of length recovery.

Parameters:

  • fa_ref (Iterable[float], optional) – Starting flip angle in [deg] per linear segment. The default is (1.5556, 70., 0.7778) [deg].

  • length (Iterable[int], optional) – Linear segment length. The default is (350, 200) pulses.

  • recovery (int, optional) – Constant flip angle recovery train length. The default is 300.

  • head (Header, optional) – Pre-existing acquisition header. If provided, interpolate FA train to ncontrast = head.traj.shape[0] and include it in the head.FA field. The default is None.

Returns:

If head is not provided, returns piecewise linear flip angle train in [deg] as a torch.Tensor. If head is provided, insert flip angle train (linearly interpolated to ncontrast = head.traj.shape[0]) in head.FA field.

Return type:

torch.Tensor | deepmr.Header

References

[1] Gómez, P.A., Cencini, M., Golbabaee, M. et al. Rapid three-dimensional multiparametric MRI with quantitative transient-state imaging. Sci Rep 10, 13769 (2020). https://doi.org/10.1038/s41598-020-70789-2

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