deepmr.linops.NUFFTOp#
- class deepmr.linops.NUFFTOp(*args: Any, **kwargs: Any)[source]#
Non-Uniform Fast Fourier Transform operator.
K-space sampling trajectory are expected to be shaped
(ncontrasts, nviews, nsamples, ndims)
.Input images are expected to have the following dimensions:
2D MRI:
(nslices, nsets, ncoils, ncontrasts, ny, nx)
3D MRI:
(nsets, ncoils, ncontrasts, nz, ny, nx)
where
nsets
represents multiple sets of coil sensitivity estimation for soft-SENSE implementations (e.g., ESPIRIT), equal to1
for conventional SENSE andncoils
represents the number of receiver channels in the coil array.Similarly, output k-space data are expected to be shaped
(nslices, nsets, ncoils, ncontrasts, nviews, nsamples)
.- __init__(coord=None, shape=None, basis_adjoint=None, weight=None, device='cpu', threadsperblock=128, width=4, oversamp=1.25)[source]#
Initiate the linear operator.
Methods
__init__
([coord, shape, basis_adjoint, ...])Initiate the linear operator.
forward
(x)Apply Non-Uniform Fast Fourier Transform.
to
(*args, **kwargs)Copy to different devices
Attributes
H
Return adjoint linear operator.