MRISigpyNUFFT

class mrinufft.operators.interfaces.sigpy.MRISigpyNUFFT(samples, shape, density=False, n_coils=1, n_batchs=1, n_trans=1, smaps=None, squeeze_dims=True, **kwargs)

Bases: FourierOperatorCPU

NUFFT using SigPy.

This is a wrapper around the SigPy NUFFT operator.

Methods

__init__
adj_op	Non Cartesian MRI adjoint operator.
cg	Conjugate Gradient method to solve the inverse problem.
check_shape	Validate the shapes of the image or k-space data against operator shapes.
compute_density	Compute the density compensation weights and set it.
compute_smaps	Compute the sensitivity maps and set it.
data_consistency	Compute the gradient data consistency.
get_lipschitz_cst	Return the Lipschitz constant of the operator.
make_autograd	Make a new Operator with autodiff support.
op	Non Cartesian MRI forward operator.
with_autograd	Return a Fourier operator with autograd capabilities.
with_off_resonance_correction	Return a new operator with Off Resonnance Correction.

Attributes

autograd_available
available
backend
cpx_dtype	Return complex floating precision of the operator.
density	Density compensation of the operator.
dtype	Return floating precision of the operator.
interfaces
n_batchs	Number of coils for the operator.
n_coils	Number of coils for the operator.
n_samples	Return the number of samples used by the operator.
ndim	Number of dimensions in image space of the operator.
norm_factor	Normalization factor of the operator.
samples	Return the samples used by the operator.
shape	Shape of the image space of the operator.
smaps	Sensitivity maps of the operator.
uses_density	Return True if the operator uses density compensation.
uses_sense	Return True if the operator uses sensitivity maps.

property norm_factor

Normalization factor of the operator.