MRIStackedNUFFT

class mrinufft.operators.stacked.MRIStackedNUFFT(samples, shape, backend, smaps, z_index='auto', n_coils=1, n_batchs=1, squeeze_dims=False, **kwargs)

Bases: FourierOperatorBase

Stacked NUFFT Operator for MRI.

The dimension of stacking is always the last one.

Parameters:

• samples (array-like) – Sample locations in a 2D kspace

• shape (tuple) – Shape of the image.

• z_index (array-like) – Cartesian z index of masked plan. if “auto” the z_index is computed from the samples, if they are 3D, using the last coordinate.

• backend (str or FourierOperatorBase) – Backend to use. If str, a NUFFT operator is initialized with str being a registered backend. If FourierOperatorBase, operator is checked for compatibility and used as is notably one should have: n_coils = self.n_coils*len(z_index), squeeze_dims=True, smaps=None

• smaps (array-like) – Sensitivity maps.

• n_coils (int) – Number of coils.

• n_batchs (int) – Number of batchs.

• **kwargs (dict) – Additional arguments to pass to the backend.

Methods

__init__
adj_op	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	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 dtype.
interfaces
n_coils	Number of coils for the operator.
n_samples	Return number of samples.
ndim	Number of dimensions in image space of the operator.
norm_factor	Normalization factor of the operator.
samples	Return samples as a N_slice x N_samples x 3 array.
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 dtype

Return dtype.

property n_samples

Return number of samples.

static _fftz(data)

Apply FFT on z-axis.

static _ifftz(data)

Apply IFFT on z-axis.

op(data, ksp=None)

Forward operator.

_op_sense(data, ksp=None)

Apply SENSE operator.

adj_op(coeffs, img=None)

Adjoint operator.

_safe_squeeze(arr)

Squeeze the first two dimensions of shape of the operator.

get_lipschitz_cst(max_iter=10)

Return the Lipschitz constant of the operator.

Parameters:

• max_iter (int) – number of iteration to compute the lipschitz constant.

• **kwargs – Extra arguments givent

Returns:

Spectral Radius

Return type:

float

Notes

This uses the Iterative Power Method to compute the largest singular value of a minified version of the nufft operator. No coil or B0 compensation is used, but includes any computed density.

property samples

Return samples as a N_slice x N_samples x 3 array.

Built from the 2D samples and the z_index normalized to [-0.5, 0.5).