pytomography.projectors.SPECT.starguide_system_matrix#

Module Contents#

Classes#

StarGuideSystemMatrix

System matrix for the StarGuide SPECT imaging system form General Electric Healthcare.
class pytomography.projectors.SPECT.starguide_system_matrix.StarGuideSystemMatrix(object_meta, proj_meta, obj2obj_transforms=[], proj2proj_transforms=[])[source]#

Bases: pytomography.projectors.system_matrix.SystemMatrix

System matrix for the StarGuide SPECT imaging system form General Electric Healthcare.

Parameters:

  • obj2obj_transforms (Sequence[Transform]) – Sequence of object mappings that occur before forward projection.

  • proj2proj_transforms (Sequence[Transform]) – Sequence of proj mappings that occur after forward projection.

  • object_meta (SPECTObjectMeta) – SPECT Object metadata.

  • proj_meta (StarGuideProjMeta) – Projection metadata pertaining to the StarGuide system.

  • object_initial_based_on_camera_path (bool) – Whether or not to initialize the object estimate based on the camera path; this sets voxels to zero that are outside the SPECT camera path. Defaults to False.

forward(object, subset_idx=None)[source]#

Applies forward projection to object.

Parameters:

  • object (torch.tensor[Lx, Ly, Lz]) – The object to be forward projected

  • subset_idx (int, optional) – Only uses a subset of angles \(g_m\) corresponding to the provided subset index \(m\). If None, then defaults to the full projections \(g\).

Returns:

forward projection estimate \(g_m=H_mf\)

Return type:

torch.tensor

backward(proj, subset_idx=None)[source]#

Applies back projection.

Parameters:

  • proj (torch.tensor) – projections \(g\) which are to be back projected

  • subset_idx (int, optional) – Only uses a subset of angles \(g_m\) corresponding to the provided subset index \(m\). If None, then defaults to the full projections \(g\).

  • return_norm_constant (bool) – Whether or not to return \(H_m^T 1\) along with back projection. Defaults to ‘False’.

Returns:

the object \(\hat{f} = H_m^T g_m\) obtained via back projection.

Return type:

torch.tensor

compute_normalization_factor(subset_idx=None)[source]#

Function used to get normalization factor \(H^T_m 1\) corresponding to projection subset \(m\).

Parameters:

subset_idx (int | None, optional) – Index of subset. If none, then considers all projections. Defaults to None.

Returns:

normalization factor \(H^T_m 1\)

Return type:

torch.Tensor

set_n_subsets(n_subsets)[source]#

Sets the subsets for this system matrix given n_subsets total subsets.

Parameters:

n_subsets (int) – number of subsets used in OSEM

Return type:

list

get_projection_subset(projections, subset_idx)[source]#

Gets the subset of projections \(g_m\) corresponding to index \(m\).

Parameters:

  • projections (torch.tensor) – full projections \(g\)

  • subset_idx (int) – subset index \(m\)

Returns:

subsampled projections \(g_m\)

Return type:

torch.tensor

_translate_object(obj, translations)[source]#

Internal function that applies translations to an object with a batch size dimension.

Parameters:

  • obj (torch.Tensor) – Object to be translated

  • translations (torch.Tensor) – Translations for each object in the batch

Returns:

Translated object

Return type:

torch.Tensor