tools.phantom

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tools.phantom#

bartorch.tools.phantom()#

An analytical phantom, as an image or as its k-space.

Parameters:

  • shape (int or tuple of int, default=None) – The image’s spatial size (-x). BART’s phantom is square or cubic, so a tuple must have one size repeated; three of them ask for the three-dimensional phantom. Without one, BART’s default size.

  • kspace (bool, default=False) – Return the analytical k-space rather than the image (-k).

  • coils (int, default=None) – Simulate this many coil sensitivities (-s).

  • traj (tensor, default=None) – Sample the k-space along this trajectory (-t) rather than on a grid, which implies kspace.

  • geometry ({'circle', 'brain', 'nist', 'sonar', 'tubes', 'bart'}, default=None) – Which phantom to make; BART spells each as its own flag.

  • rotation_angle (float, int, default=None) – Rotate the phantom (--rotation-angle, --rotation-steps).

  • rotation_steps (float, int, default=None) – Rotate the phantom (--rotation-angle, --rotation-steps).

  • **extra – Further BART phantom flags, by name.

Returns:

The phantom.

Return type:

torch.Tensor

Examples

>>> image = phantom(128)
>>> kspace = phantom(128, coils=8, kspace=True)
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