pytomography.projections.forward_projection#

Module Contents#

Classes#

ForwardProjectionNet

Implements a forward projection of mathematical form \(g_j = \sum_{i} c_{ij} f_i\) where \(f_i\) is an object, \(g_j\) is the corresponding image, and \(c_{ij}\) is the system matrix given by the various phenonemon modeled (e.g. atteunation/PSF).

class pytomography.projections.forward_projection.ForwardProjectionNet(obj2obj_nets, im2im_nets, object_meta, image_meta, device='cpu')#

Bases: pytomography.projections.projection.ProjectionNet

Implements a forward projection of mathematical form \(g_j = \sum_{i} c_{ij} f_i\) where \(f_i\) is an object, \(g_j\) is the corresponding image, and \(c_{ij}\) is the system matrix given by the various phenonemon modeled (e.g. atteunation/PSF).

Parameters:
forward(object, angle_subset=None)#

Implements forward projection on an object

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

  • angle_subset (list, optional) – Only uses a subset of angles (i.e. only certain values of \(j\) in formula above) when back projecting. Useful for ordered-subset reconstructions. Defaults to None,

  • used. (which assumes all angles are) –

Returns:

Forward projected image where Ltheta is specified by self.image_meta and angle_subset.

Return type:

torch.tensor[batch_size, Ltheta, Lx, Lz]