tools.ecalib#

bartorch.tools.ecalib()#

Coil sensitivities by ESPIRiT.

Parameters:

kspace (torch.Tensor) – Fully sampled calibration data, or k-space with a sampled centre, (coils, z, y, x), or (coils, y, x) for one slice.
maps (int, default=None) – How many sets of sensitivities to produce (-m).
calib_size (int or tuple of int, default=None) – The calibration region’s size (-r), the same on every axis or one per axis.
threshold (float, default=None) – The singular-value threshold for the calibration matrix (-t).
crop (float, default=None) – The eigenvalue below which a sensitivity is set to zero (-c).
kernel_size (int, default=None) – The calibration kernel’s size (-k).
softsense (bool, default=False) – Return the maps without the eigenvalue crop, for soft-SENSE (-S).
intensity_correction (bool, default=False) – Correct for intensity rather than normalising (-I).
return_eigenvalues (bool, default=False) – Also return the eigenvalue map, which BART writes as a second array only when asked.
**extra – Further BART ecalib options, by name. e, the axis the second step is split along, takes an axis of kspace.

Returns:

The sensitivities, and the eigenvalues when asked for, without a z axis when kspace has none.

Return type:

torch.Tensor or tuple of torch.Tensor

Examples

>>> maps = ecalib(kspace, maps=1, crop=0.8)

Examples using `ecalib`#