sigpy.mri.kspace_precond¶
-
sigpy.mri.
kspace_precond
(mps, weights=None, coord=None, lamda=0, device=<CPU Device>, oversamp=1.25)[source]¶ Compute a diagonal preconditioner in k-space.
Considers the optimization problem:
\[\min_P \| P A A^H - I \|_F^2\]where A is the Sense operator.
Parameters: - mps (array) – sensitivity maps of shape [num_coils] + image shape.
- weights (array) – k-space weights.
- coord (array) – k-space coordinates of shape […] + [ndim].
- lamda (float) – regularization.
Returns: k-space preconditioner of same shape as k-space.
Return type: array