ST-FL: style transfer preprocessing in federated learning for COVID-19 segmentation

@inproceedings{Georgiadis2022STFLST,
  title={ST-FL: style transfer preprocessing in federated learning for COVID-19 segmentation},
  author={Antonios Georgiadis and Varun Babbar and Fran Silavong and Sean J. Moran and Rob den Otter},
  booktitle={Medical Imaging},
  year={2022}
}
Chest Computational Tomography (CT) scans present low cost, speed and objectivity for COVID-19 diagnosis and deep learning methods have shown great promise in assisting the analysis and interpretation of these images. Most hospitals or countries can train their own models using in-house data, however empirical evidence shows that those models perform poorly when tested on new unseen cases, surfacing the need for coordinated global collaboration. Due to privacy regulations, medical data sharing… 

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