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Federated 3D multi-organ segmentation with partially labeled and unlabeled data.

Zhou ZhengYuichiro HayashiMasahiro OdaTakayuki KitasakaKazunari MisawaKensaku Mori
Published in: International journal of computer assisted radiology and surgery (2024)
This study considers a novel problem of multi-organ segmentation, which aims to develop a generalizable model using distributed, partially labeled, and unlabeled CT images. A practical framework is presented, which, through extensive validation, has proved to be an effective solution, demonstrating strong potential in addressing this challenging problem.
Keyphrases
  • deep learning
  • convolutional neural network
  • pet imaging
  • computed tomography
  • big data
  • machine learning
  • positron emission tomography
  • dual energy
  • risk assessment
  • neural network