MPnRAGEModel

MPnRAGEModel#

class torchsim.models.MPnRAGEModel(diff=None, chunk_size=None, device=None, *args, **kwargs)[source]#

Bases: AbstractModel

Magnetization Prepared (n) RApid Gradient Echo (MPnRAGE) Model.

This class models Magnetization Prepared RApid Gradient Echo with n volumes per segment (MPnRAGE) signals based on tissue properties, pulse sequence parameters, and experimental conditions. It uses Extended Phase Graph (EPG) formalism to compute the magnetization evolution over time.

Parameters:

  • diff (str | tuple[str] | None)

  • chunk_size (int | None)

  • device (str | device | None)

set_properties(T1, M0=1.0, B1=1.0, inv_efficiency=1.0)[source]#

Sets tissue relaxation properties and experimental conditions.

Parameters:
set_sequence(nshots, flip, TR, TI=0.0, slice_prof=1.0)[source]#

Configures the pulse sequence parameters for the simulation.

Parameters:
_engine(T1, flip, TR, TI=0.0, M0=1.0, B1=1.0, inv_efficiency=1.0,

slice_prof=1.0)

Computes the MPnRAGE signal for given tissue properties and sequence parameters.

Examples

from torchsim.models import MPnRAGEModel

model = MPnRAGEModel()
model.set_properties(T1=1000, inv_efficiency=0.95)
model.set_sequence(nshots=128, flip=5.0, TR=10.0)
signal = model()

Methods

__init__

Initialize the model with automatic parameter segregation and engine setup.

forward

Get forward method.

jacobian

Get Jacobian method.

set_properties

Set tissue and system-specific properties for the MRF model.

set_sequence

Set sequence parameters for the SPGR model.
set_properties(T1, M0=1.0, B1=1.0, inv_efficiency=1.0)[source]#

Set tissue and system-specific properties for the MRF model.

Parameters:

  • T1 (float | npt.ArrayLike) – Longitudinal relaxation time in milliseconds.

  • M0 (float or array-like, optional) – Proton density scaling factor, default is 1.0.

  • B1 (float | npt.ArrayLike, optional) – Flip angle scaling map, default is 1.0.

  • inv_efficiency (float | npt.ArrayLike, optional) – Inversion efficiency map, default is 1.0.

set_sequence(nshots, flip, TR, TI=0.0, slice_prof=1.0)[source]#

Set sequence parameters for the SPGR model.

Parameters:

  • nshots (int) – Number of SPGR shots per inversion block.

  • flip (float) – Flip angle train in degrees.

  • TR (float) – Repetition time in milliseconds.

  • TI (float, optional) – Inversion time in milliseconds. The default is 0.0.

  • slice_prof (float | npt.ArrayLike, optional) – Flip angle scaling along slice profile. The default is 1.0.

static _engine(T1, nshots, flip, TR, TI=0.0, M0=1.0, B1=1.0, inv_efficiency=1.0, slice_prof=1.0)[source]#

Core computational function for the model.

Parameters: