• Corpus ID: 239885894

Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data

@article{Haque2021GeneralizedML,
  title={Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data},
  author={Ayaan Haque and Abdullah-Al-Zubaer Imran and Adam Wang and Demetri Terzopoulos},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.13185}
}
Deep learning-based models, when trained in a fully-supervised manner, can be effective in performing complex image analysis tasks, although contingent upon the availability of large labeled datasets. Especially in the medical imaging domain, however, expert image annotation is expensive, time-consuming, and prone to variability. Semi-supervised learning from limited quantities of labeled data has shown promise as an alternative. Maximizing knowledge gains from copious unlabeled data benefits… 

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