nlop.MultiEcho

nlop.MultiEcho#

bartorch.nlop.MultiEcho()#

T2 or T2* from a multi-echo readout.

The transverse decay read at a series of echo times. Which relaxation is measured is a property of the sequence that produced the data, not of the model: a spin-echo train measures T2 and a gradient-echo train T2*, and the exponential is the same either way.

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)}; T2 defaults to (1, 1000) ms.

  • unknown (sequence of str, default=('T2',)) – What to solve for. offset is the other thing the model exposes.

  • amplitude (bool, default=True) – Carry a complex amplitude multiplying the decay.

  • subspace (torchsim.Subspace, default=None) – Solve in a temporal basis rather than in the contrasts.

  • **scale – The size of a step in a parameter left unbounded.

Examples using MultiEcho#

Parameter maps straight from k-space

Parameter maps straight from k-space

Parameter maps from scanner images

Parameter maps from scanner images