niftynet.contrib.csv_reader.applications_maybe.label_driven_registration module¶
- A preliminary re-implementation of:
- Hu et al., Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration, Medical Image Analysis (2018) https://doi.org/10.1016/j.media.2018.07.002
- The original implementation and tutorial is available at:
- https://github.com/YipengHu/label-reg
-
class
RegApp
(net_param, action_param, action)[source]¶ Bases:
niftynet.application.base_application.BaseApplication
-
REQUIRED_CONFIG_SECTION
= 'REGISTRATION'¶
-
initialise_dataset_loader
(data_param=None, task_param=None, data_partitioner=None)[source]¶ this function initialise self.readers
Parameters: - data_param – input modality specifications
- task_param – contains task keywords for grouping data_param
- data_partitioner – specifies train/valid/infer splitting if needed
Returns:
-
initialise_sampler
()[source]¶ Samplers take
self.reader
as input and generates sequences of ImageWindow that will be fed to the networksThis function sets
self.sampler
.
-
initialise_network
()[source]¶ This function create an instance of network and sets
self.net
Returns: None
-