GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

@article{FridAdar2018GANbasedSM,
  title={GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification},
  author={Maayan Frid-Adar and I. Diamant and E. Klang and M. Amitai and J. Goldberger and H. Greenspan},
  journal={Neurocomputing},
  year={2018},
  volume={321},
  pages={321-331}
}
  • Maayan Frid-Adar, I. Diamant, +3 authors H. Greenspan
  • Published 2018
  • Computer Science, Mathematics
  • Neurocomputing
  • Abstract Deep learning methods, and in particular convolutional neural networks (CNNs), have led to an enormous breakthrough in a wide range of computer vision tasks, primarily by using large-scale annotated datasets. However, obtaining such datasets in the medical domain remains a challenge. In this paper, we present methods for generating synthetic medical images using recently presented deep learning Generative Adversarial Networks (GANs). Furthermore, we show that generated medical images… CONTINUE READING
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