radial

Generate radial sampling masks.

mr_utils.sim.traj.radial.radial(shape, num_spokes, theta=None, offset=0, theta0=0, skinny=True, extend=False)[source]

Create 2d binary radial sampling pattern.

Parameters:
  • shape (tuple) – x,y dimensions of sampling pattern.
  • num_spokes (int) – Number of spokes to simulate.
  • theta (float, optional) – Angle between spokes (rad).
  • offset (int, optional) – Number of angles to skip.
  • theta0 (float, optional) – Starting angle (rad).
  • skinny (bool, optional) – Garuantee 1px spoke width.
  • extend (bool, optional) – Extend spokes to the edge of array.
Returns:

idx – Boolean mask where samples in k-space should be taken.
Return type:

array_like

Notes

If theta=None, use golden angle. If skinny=True, edges of spokes with large slope may be curved. If extend=False, spokes confined in a circle.

mr_utils.sim.traj.radial.radial_golden_ratio_meshgrid(X, Y, num_spokes)[source]

Create 2d binary golden angle radial sampling pattern.

Parameters:
  • X (array_like) – X component of meshgrid.
  • Y (array_like) – T component of meshgrid.
  • num_spokes (int) – Number of spokes to simulate.
Returns:

samp – Mask of where samples in k-space are taken.
Return type:

array_like

Notes

Issues: For steep slopes, the spokes don’t make it all the way to the edge of the image and they curve (from the skeletonize)…