MRIPynufft#
- class mrinufft.operators.interfaces.pynufft_cpu.MRIPynufft(samples, shape, density=False, n_coils=1, n_batchs=1, smaps=None, osf=2, **kwargs)[source]#
- Bases: - FourierOperatorCPU- PyNUFFT implementation of MRI NUFFT transform. - 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. 
