nlop.MultiEcho

nlop.MultiEcho#

bartorch.nlop.MultiEcho()#

Mono-exponential multi-echo signal model for T2 or T2* mapping.

The transverse decay at a series of echo times, from BlochSim’s MultiEchoSimulator. The fitted constant is T2 for a spin-echo train and T2* for a gradient-echo train; the model is the same.

Parameters:

  • TE (sequence of float) – Echo times, in milliseconds.

  • shape (tuple of int, default=()) – The voxel shape, C order.

  • bounds (dict, default=None) – {name: (low, high)} per unknown, in its units; T2 defaults to (1, 1000) ms. Bounds of properties not in unknown are dropped.

  • unknown (sequence of str, default=('T2',)) – Properties solved for, e.g. also offset.

  • amplitude (bool, default=True) – Include a complex amplitude multiplying the signal.

  • subspace (blochsim.Subspace, default=None) – Temporal basis the prediction is projected through.

  • **scale – name=value: step size of an unbounded parameter.

Returns:

Domain (channels, *shape), codomain (len(TE), *shape).

Return type:

ModelOperator

Examples using MultiEcho#

9. Nonlinear inversion for T2 mapping

9. Nonlinear inversion for T2 mapping

Parameter maps from scanner images

Parameter maps from scanner images