sigpy.mri.app.JsenseRecon

class sigpy.mri.app.JsenseRecon(y, mps_ker_width=16, ksp_calib_width=24, lamda=0, device=<CPU Device>, comm=None, weights=None, coord=None, img_shape=None, grd_shape=None, max_iter=10, max_inner_iter=10, normalize=True, show_pbar=True)[source]

JSENSE/NLINV reconstruction.

Considers the problem

\[\min_{l, r} \frac{1}{2} \| l \ast r - y \|_2^2 + \frac{\lambda}{2} (\| l \|_2^2 + \| r \|_2^2)\]

where \(\ast\) is the convolution operator.

This formulation with regularization corresponds to the version described in the NLINV paper. Without regularization (which is the default) this corresponds to the version from the JSENSE paper but using a truncated Fourier representation of the coils (as in NLINV) instead of polynomials.

Parameters:
  • y (array) – k-space measurements.
  • mps_ker_width (int) – sensitivity maps kernel width.
  • ksp_calib_width (int) – k-space calibration width.
  • lamda (float) – regularization parameter.
  • device (Device) – device to perform reconstruction.
  • weights (float or array) – weights for data consistency.
  • coord (None or array) – coordinates.
  • img_shape (None or list) – Image shape.
  • grd_shape (None or list) – Shape of grid.
  • max_iter (int) – Maximum number of iterations.
  • max_inner_iter (int) – Maximum number of inner iterations.

References

Ying, L., & Sheng, J. (2007). Joint image reconstruction and sensitivity estimation in SENSE (JSENSE). Magnetic Resonance in Medicine, 57(6), 1196-1202.

Uecker, M., Hohage, T., Block, K. T., & Frahm, J. (2008). Image reconstruction by regularized nonlinear inversion- joint estimation of coil sensitivities and image content. Magnetic Resonance in Medicine, 60(#), 674-682.

__init__(y, mps_ker_width=16, ksp_calib_width=24, lamda=0, device=<CPU Device>, comm=None, weights=None, coord=None, img_shape=None, grd_shape=None, max_iter=10, max_inner_iter=10, normalize=True, show_pbar=True)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(y[, mps_ker_width, …]) Initialize self.
run() Run the App.