deepmr.linops.FFTGramOp

class deepmr.linops.FFTGramOp(*args: Any, **kwargs: Any)

Self-adjoint Sparse Fast Fourier Transform operator.

K-space sampling mask, if provided, is expected to to have the following dimensions:

• 2D MRI: (ncontrasts, ny, nx)

• 3D MRI: (ncontrasts, nz, ny)

Input and output images are expected to have the following dimensions:

• 2D MRI: (nslices, nsets, ncoils, ncontrasts, ny, nx)

• 3D MRI: (nsets, ncoils, ncontrasts, nz, ny)

where nsets represents multiple sets of coil sensitivity estimation for soft-SENSE implementations (e.g., ESPIRIT), equal to 1 for conventional SENSE and ncoils represents the number of receiver channels in the coil array.

__init__(mask=None, basis=None, device=None, **kwargs)

Initiate the linear operator.

Methods

__init__([mask, basis, device])	Initiate the linear operator.
forward(x)	Apply Toeplitz convolution (SparseFFT.H * SparseFFT).
to(*args, **kwargs)	Copy to different devices

Attributes

H	Return adjoint linear operator.