tools.traj

tools.traj#

bartorch.tools.traj()#

k-space trajectory in grid units, Cartesian or radial.

Parameters:

  • readout (int, default=None) – Samples per readout (-x); BART’s default is 128.

  • spokes (int, default=None) – Readouts per frame (-y); BART’s default is 128.

  • frames (int, default=None) – Number of frames along BART’s time axis, each rotated by a fraction of the angular increment (-t, BART’s turns); radial only.

  • radial (bool, default=False) – Radial spokes rather than Cartesian lines (-r).

  • golden (bool, default=False) – Golden-angle increment between spokes (-G); implies radial.

  • turns (int, default=None) – Simultaneous multi-slice factor: partitions along BART’s slice axis (-m); radial only.

  • oversampling (bool, default=False) – Correct the transverse gradient error of a radial trajectory (-O). Readout oversampling is traj -o, passed as o=factor.

  • **extra – Further BART traj options, by name.

Returns:

Coordinates (..., spokes, readout, 3), kx, ky, kz in grid units, with leading axes for frames and turns when they exceed one. The layout every non-Cartesian transform in this package takes.

Return type:

torch.Tensor

Examples

>>> trajectory = traj(readout=256, spokes=64, radial=True, golden=True)

Examples using traj#

7. Basics of non-Cartesian imaging

7. Basics of non-Cartesian imaging

8. Radial SENSE

8. Radial SENSE

Dynamic golden-angle radial MRI

Dynamic golden-angle radial MRI

Subspace-constrained T1 mapping

Subspace-constrained T1 mapping