pytomography.projections
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Submodules#
Package Contents#
Classes#
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). |
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Implements a back projection of mathematical form \(f_i = \frac{1}{\sum_j c_{ij}}\sum_{j} c_{ij} g_j\). where \(f_j\) is an object, \(g_j\) is an image, and \(c_{ij}\) is the system matrix given by the various phenonemon modeled (e.g. atteunation correction/PSF). Subclass of the |
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Abstract parent class for projection networks. Any subclass of this network must implement the |
- class pytomography.projections.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:
obj2obj_nets (list[pytomography.mappings.MapNet]) –
im2im_nets (list[pytomography.mappings.MapNet]) –
object_meta (pytomography.metadata.ObjectMeta) –
image_meta (pytomography.metadata.ImageMeta) –
device (str) –
- 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]
- class pytomography.projections.BackProjectionNet(obj2obj_nets, im2im_nets, object_meta, image_meta, device='cpu')#
Bases:
pytomography.projections.projection.ProjectionNet
Implements a back projection of mathematical form \(f_i = \frac{1}{\sum_j c_{ij}}\sum_{j} c_{ij} g_j\). where \(f_j\) is an object, \(g_j\) is an image, and \(c_{ij}\) is the system matrix given by the various phenonemon modeled (e.g. atteunation correction/PSF). Subclass of the
ProjectionNet
class.- Parameters:
obj2obj_nets (list[pytomography.mappings.MapNet]) –
im2im_nets (list[pytomography.mappings.MapNet]) –
object_meta (pytomography.metadata.ObjectMeta) –
image_meta (pytomography.metadata.ImageMeta) –
device (str) –
- forward(image, angle_subset=None, prior=None, normalize=False, return_norm_constant=False, delta=1e-11)#
Implements back projection on an image, returning an object.
- Parameters:
image (torch.tensor[batch_size, Ltheta, Lr, Lz]) – image which is to be back 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, which assumes all angles are used.
prior (Prior, optional) – If included, modifes normalizing factor to \(\frac{1}{\sum_j c_{ij} + P_i}\) where \(P_i\) is given by the prior. Used, for example, during in MAP OSEM. Defaults to None.
normalize (bool) – Whether or not to divide result by \(\sum_j c_{ij}\)
return_norm_constant (bool) – Whether or not to return \(1/\sum_j c_{ij}\) along with back projection. Defaults to ‘False’.
delta (float, optional) – Prevents division by zero when dividing by normalizing constant. Defaults to 1e-11.
- Returns:
the object obtained from back projection.
- Return type:
torch.tensor[batch_size, Lr, Lr, Lz]
- class pytomography.projections.ProjectionNet(obj2obj_nets, im2im_nets, object_meta, image_meta, device='cpu')#
Bases:
torch.nn.Module
Abstract parent class for projection networks. Any subclass of this network must implement the
forward
method.- Parameters:
obj2obj_nets (list[pytomography.mappings.MapNet]) –
im2im_nets (list[pytomography.mappings.MapNet]) –
object_meta (pytomography.metadata.ObjectMeta) –
image_meta (pytomography.metadata.ImageMeta) –
device (str) –
- initialize_correction_nets()#
Function that initializes all mapping networks with the required object and image metadata corresponding to the projection network.
- abstract foward()#
Abstract method that must be implemented by any subclass of this class.