MingR-Ma / RWCNet

Official implementation of Recurrence with Correlation Network for Medical Image Registration

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RWCNet

This is the official repository for RWCNet

RWCNet Diagram

Setup

pip install -r requirements.txt

Training

  • Currently, the model caches the hidden tensors as well as the flows at each level. This ends up taking a lot of space.
  • The model training can be configured using the train_config.json. The options for the configuration can be inferred from config.py
  • When running the full model against L2R data, please use the data format used for the L2R 2022 challenge.

To train the model on L2R data:

python l2r_train_eval.py l2r_dataset_json.json train_config.json

Publication

If you find this repository useful, please cite:

Recurrence With Correlation Network for Medical Image Registration
Vignesh Sivan, Teodora Vujovic, Raj Ranabhat, Alexander Wong, Stewart Mclachlin, Michael Hardisty
eprint arXiv:2302.02283

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Official implementation of Recurrence with Correlation Network for Medical Image Registration

License:MIT License


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