deepmr.linops.NUFFTAdjointOp#
- class deepmr.linops.NUFFTAdjointOp(*args: Any, **kwargs: Any)[source]#
Adjoint Non-Uniform Fast Fourier Transform operator.
K-space sampling trajectory are expected to be shaped
(ncontrasts, nviews, nsamples, ndims)
.Input k-psace data 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 images data are expected to be shaped
(nslices, nsets, ncoils, ncontrasts, nviews, nsamples)
.- __init__(coord=None, shape=None, basis=None, weight=None, device='cpu', threadsperblock=128, width=4, oversamp=1.25, **kwargs)[source]#
Initiate the linear operator.
Methods
__init__
([coord, shape, basis, weight, ...])Initiate the linear operator.
forward
(y)Apply adjoint Non-Uniform Fast Fourier Transform.
to
(*args, **kwargs)Copy to different devices
Attributes
H
Return adjoint linear operator.