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)[source]#

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.

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.

toggle_grad_traj

Toggle between the gradient trajectory and the plan for type 1 transform.

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_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 samples#

Return the samples used by the operator.

toggle_grad_traj()[source]#

Toggle between the gradient trajectory and the plan for type 1 transform.