nifreeze.estimator module

A model-based algorithm for the realignment of dMRI data.

class nifreeze.estimator.Estimator(self, /, *args, **kwargs)[source]

Bases: object

Estimates rigid-body head-motion and distortions derived from eddy-currents.

static estimate(data, *, align_kwargs=None, iter_kwargs=None, models=('b0',), omp_nthreads=None, n_jobs=None, **kwargs)[source]

Estimate head-motion and Eddy currents.

Parameters:

  • data (DWI) – The target DWI dataset, represented by this tool’s internal type. The object is used in-place, and will contain the estimated parameters in its em_affines property, as well as the rotated b-vectors within its gradients property.

  • n_iter (int) – Number of iterations this particular model is going to be repeated.

  • align_kwargs (dict) – Parameters to configure the image registration process.

  • iter_kwargs (dict) – Parameters to configure the iterator strategy to traverse timepoints/orientations.

  • models (list) – Selects the diffusion model that will generate the registration target corresponding to each gradient map. See ModelFactory for allowed models (and corresponding keywords).

  • omp_nthreads (int) – Maximum number of threads an individual process may use.

  • n_jobs (int) – Number of parallel jobs.

Returns:

A list of \(4 \times 4\) affine matrices encoding the estimated parameters of the deformations caused by head-motion and eddy-currents.

Return type:

list of numpy.ndarray