niftynet.network.highres3dnet module¶
-
class
niftynet.network.highres3dnet.
HighRes3DNet
(num_classes, w_initializer=None, w_regularizer=None, b_initializer=None, b_regularizer=None, acti_func='prelu', name='HighRes3DNet')¶ Bases:
niftynet.network.base_net.BaseNet
- implementation of HighRes3DNet:
- Li et al., “On the compactness, efficiency, and representation of 3D convolutional networks: Brain parcellation as a pretext task”, IPMI ‘17
-
layer_op
(images, is_training, layer_id=-1)¶
-
class
niftynet.network.highres3dnet.
HighResBlock
(n_output_chns, kernels=(3, 3), acti_func='relu', w_initializer=None, w_regularizer=None, with_res=True, name='HighResBlock')¶ Bases:
niftynet.layer.base_layer.TrainableLayer
This class define a high-resolution block with residual connections kernels - specify kernel sizes of each convolutional layer
- e.g.: kernels=(5, 5, 5) indicate three conv layers of kernel_size 5
with_res - whether to add residual connections to bypass the conv layers
-
layer_op
(input_tensor, is_training)¶