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
nsetsrepresents multiple sets of coil sensitivity estimation for soft-SENSE implementations (e.g., ESPIRIT), equal to1for conventional SENSE andncoilsrepresents 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
HReturn adjoint linear operator.