MRITensorflowNUFFT#
- class mrinufft.operators.interfaces.tfnufft.MRITensorflowNUFFT(samples, shape, n_coils=1, density=False, smaps=None, eps=1e-06)[source]#
Bases:
FourierOperatorBase
MRI Transform Operator using Tensorflow NUFFT.
- Parameters:
samples (Tensor) – 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.
density (bool or Tensor) –
- 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 (Tensor)
Methods
__init__
Backward Operation.
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.
Compute the data consistency.
get_lipschitz_cst
Return the Lipschitz constant of the operator.
make_autograd
Make a new Operator with autodiff support.
Forward operation.
Estimate the density compensation using the pipe method.
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 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#
Norm factor of the operator.
- data_consistency(data, obs_data)[source]#
Compute the data consistency.
- Parameters:
data (Tensor) – Image data
obs_data (Tensor) – Observed data
- Returns:
The data consistency error in image space.
- Return type:
Tensor