Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging

@article{Kaji2019OverviewOI,
  title={Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging},
  author={S. Kaji and S. Kida},
  journal={Radiological Physics and Technology},
  year={2019},
  pages={1-14}
}
  • S. Kaji, S. Kida
  • Published 2019
  • Computer Science, Physics, Engineering, Medicine
  • Radiological Physics and Technology
Since the advent of deep convolutional neural networks (DNNs), computer vision has seen an extremely rapid progress that has led to huge advances in medical imaging. Every year, many new methods are reported at conferences such as the International Conference on Medical Image Computing and Computer-Assisted Intervention and Machine Learning for Medical Image Reconstruction, or published online at the preprint server arXiv. There is a plethora of surveys on applications of neural networks in… Expand
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