Learning A Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution

@article{Tom2019LearningAD,
  title={Learning A Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution},
  author={Francis Tom and Himanshu Sharma and Dheeraj Mundhra and Tathagato Rai Dastidar and Debdoot Sheet},
  journal={2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)},
  year={2019},
  pages={1391-1394}
}
Adversarially trained deep neural networks have significantly improved performance of single image super resolution, by hallucinating photorealistic local textures, thereby greatly reducing the perception difference between a real high resolution image and its super resolved (SR) counterpart. However, application to medical imaging requires preservation of diagnostically relevant features while refraining from introducing any diagnostically confusing artifacts. We propose using a deep… Expand
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