Voxelmorph2d
Labelprop Index / Labelprop / Voxelmorph2d
Auto-generated documentation for labelprop.voxelmorph2d module.
- Voxelmorph2d
- AffineGenerator
- AffineGenerator3D
- Dice
- FeaturesToAffine
- Grad
- MSE
- MultiLevelNet
- NCC
- ResizeTransform
- SingleLevelNet
- SpatialTransformer
- VecInt
- VxmDense
AffineGenerator
Show source in voxelmorph2d.py:178
Dense network that takes affine matrix and generate affine transformation
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class AffineGenerator(nn.Module):
def __init__(self, inshape): ...
AffineGenerator().forward
Show source in voxelmorph2d.py:189
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def forward(self, x1, x2): ...
AffineGenerator3D
Show source in voxelmorph2d.py:197
Dense network that takes affine matrix and generate affine transformation
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class AffineGenerator3D(nn.Module):
def __init__(self, inshape): ...
AffineGenerator3D().forward
Show source in voxelmorph2d.py:208
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def forward(self, x1, x2): ...
Dice
Show source in voxelmorph2d.py:518
N-D dice for segmentation
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class Dice: ...
Dice().loss
Show source in voxelmorph2d.py:523
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def loss(self, y_true, y_pred): ...
FeaturesToAffine
Show source in voxelmorph2d.py:158
Dense network that takes pixels of features map and convert it to affine matrix
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class FeaturesToAffine(nn.Module):
def __init__(self, inshape): ...
FeaturesToAffine().forward
Show source in voxelmorph2d.py:172
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def forward(self, x): ...
Grad
Show source in voxelmorph2d.py:531
N-D gradient loss.
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class Grad:
def __init__(self, penalty="l1", loss_mult=None): ...
Grad().loss
Show source in voxelmorph2d.py:540
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def loss(self, _, y_pred): ...
MSE
Show source in voxelmorph2d.py:509
Mean squared error loss.
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class MSE: ...
MSE().loss
Show source in voxelmorph2d.py:514
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def loss(self, y_true, y_pred): ...
MultiLevelNet
Show source in voxelmorph2d.py:257
Convolutional network generating deformation field with different scales.
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class MultiLevelNet(nn.Module):
def __init__(self, inshape, in_channels=2, levels=3, features=16): ...
MultiLevelNet().compose_deformation
Show source in voxelmorph2d.py:309
Returns flow_k_j(flow_i_k(.)) flow
Arguments
flow_i_k flow_k_j
Returns
[Tensor]- Flow field flow_i_j = flow_k_j(flow_i_k(.))
Signature
def compose_deformation(self, flow_i_k, flow_k_j): ...
MultiLevelNet().compose_list
Show source in voxelmorph2d.py:303
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def compose_list(self, flows): ...
MultiLevelNet().forward
Show source in voxelmorph2d.py:320
For each levels, downsample the input and apply the convolutional block.
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def forward(self, x, registration=False): ...
MultiLevelNet().get_conv_blocks
Show source in voxelmorph2d.py:279
For each levels, create a convolutional block with two Conv Tanh BatchNorm layers
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def get_conv_blocks(self, in_channels, levels, intermediate_features): ...
MultiLevelNet().get_downsample_blocks
Show source in voxelmorph2d.py:273
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def get_downsample_blocks(self, in_channels, levels): ...
MultiLevelNet().get_transformer_list
Show source in voxelmorph2d.py:294
Create a list of spatial transformer for each level.
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def get_transformer_list(self, levels, inshape): ...
NCC
Show source in voxelmorph2d.py:444
Local (over window) normalized cross correlation loss.
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class NCC:
def __init__(self, win=None): ...
NCC().loss
Show source in voxelmorph2d.py:452
Signature
def loss(self, y_true, y_pred, mean=True): ...
ResizeTransform
Show source in voxelmorph2d.py:410
Resize a transform, which involves resizing the vector field and rescaling it.
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class ResizeTransform(nn.Module):
def __init__(self, vel_resize, ndims): ...
ResizeTransform().forward
Show source in voxelmorph2d.py:424
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def forward(self, x): ...
SingleLevelNet
Show source in voxelmorph2d.py:215
Convolutional network generating deformation field
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class SingleLevelNet(nn.Module):
def __init__(self, inshape, in_channels=2, features=16): ...
SingleLevelNet().forward
Show source in voxelmorph2d.py:245
Forward pass of the network
Arguments
x[Tensor] - Tensor of shape (B,C,H,W)
Returns
[Tensor]- Tensor of shape (B,C,H,W)
Signature
def forward(self, x): ...
SingleLevelNet().get_conv_blocks
Show source in voxelmorph2d.py:227
For each levels, create a convolutional block with two Conv Tanh BatchNorm layers
Signature
def get_conv_blocks(self, in_channels, intermediate_features): ...
SpatialTransformer
Show source in voxelmorph2d.py:343
N-D Spatial Transformer
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class SpatialTransformer(nn.Module):
def __init__(self, size, mode="bilinear", levels=4): ...
SpatialTransformer().forward
Show source in voxelmorph2d.py:368
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def forward(self, src, flow): ...
VecInt
Show source in voxelmorph2d.py:390
Integrates a vector field via scaling and squaring.
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class VecInt(nn.Module):
def __init__(self, inshape, nsteps): ...
VecInt().forward
Show source in voxelmorph2d.py:403
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def forward(self, vec): ...
VxmDense
Show source in voxelmorph2d.py:10
VoxelMorph network for (unsupervised) nonlinear registration between two images.
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class VxmDense(nn.Module):
def __init__(
self,
inshape,
int_steps=7,
int_downsize=2,
bidir=False,
use_probs=False,
src_feats=1,
trg_feats=1,
unet_half_res=False,
sub_levels=3,
): ...
VxmDense().forward
Show source in voxelmorph2d.py:111
Arguments
source- Source image tensor.target- Target image tensor.registration- Return transformed image and flow. Default is False.
Signature
def forward(self, source, target, registration=False): ...