niftynet.network.interventional_affine_net module

class INetAffine(decay=1e-06, affine_w_initializer=None, affine_b_initializer=None, acti_func='relu', name='inet-affine')

Bases: niftynet.network.base_net.BaseNet

__init__(decay=1e-06, affine_w_initializer=None, affine_b_initializer=None, acti_func='relu', name='inet-affine')

This network estimates affine transformations from a pair of moving and fixed image:

Hu et al., Label-driven weakly-supervised learning for multimodal deformable image registration, arXiv:1711.01666 https://arxiv.org/abs/1711.01666

Parameters:

• decay –
• affine_w_initializer –
• affine_b_initializer –
• acti_func –
• name –

layer_op(fixed_image, moving_image, is_training=True)

Parameters:

• fixed_image –
• moving_image –
• is_training –

Returns:

displacement fields transformed by estimating affine

init_affine_w(std=1e-08)

init_affine_b(spatial_rank, initial_bias=0.0)