deepmr.linops.NUFFTGramOp#
- class deepmr.linops.NUFFTGramOp(*args: Any, **kwargs: Any)[source]#
Self-adjoint Non-Uniform Fast Fourier Transform operator.
K-space sampling trajectory are expected to be shaped
(ncontrasts, nviews, nsamples, ndims)
.Input and output data are expected to be shaped
(nslices, nsets, ncoils, ncontrasts, nviews, nsamples)
, wherensets
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.- __init__(coord, shape, basis=None, weight=None, device='cpu', threadsperblock=128, width=6, **kwargs)[source]#
Initiate the linear operator.
Methods
__init__
(coord, shape[, basis, weight, ...])Initiate the linear operator.
forward
(x)Apply Toeplitz convolution (
NUFFT.H * NUFFT
).to
(*args, **kwargs)Copy to different devices
Attributes
H
Return adjoint linear operator.