MRIfinufft

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

Bases: FourierOperatorCPU

MRI Transform Operator using finufft.

Parameters:

• samples (array) – The samples location of shape Nsamples x N_dimensions. It should be C-contiguous.

• shape (tuple) – Shape of the image space.

• n_coils (int) – Number of coils.

• n_batchs (int) – Number of batchs .

• n_trans (int) – Number of parallel transform

• density (bool or array) –

  Density compensation support.

  • If a Tensor, it will be used for the density.

  • If True, the density compensation will be automatically estimated, using the fixed point method.

  • If False, density compensation will not be used.

• smaps (array) – Sensitivity maps of shape N_coils x *shape.

• squeeze_dims (bool) – If True, the dimensions of size 1 for the coil and batch dimension will be squeezed.

Methods

__init__
adj_op	Non Cartesian MRI adjoint operator.
compute_density	Compute the density compensation weights and set it.
data_consistency	Compute the gradient data consistency.
get_lipschitz_cst	Return the Lipschitz constant of the operator.
op	Non Cartesian MRI forward operator.
with_off_resonnance_correction	Return a new operator with Off Resonnance Correction.

Attributes

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_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.