Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement.

@article{Liu2021ArtificialII,
  title={Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement.},
  author={Juan Liu and Masoud Malekzadeh and Niloufar Mirian and Tzu-An Song and Chi Liu and Joyita Dutta},
  journal={PET clinics},
  year={2021},
  volume={16 4},
  pages={
          553-576
        }
}
High noise and low spatial resolution are two key confounding factors that limit the qualitative and quantitative accuracy of PET images. Artificial intelligence models for image denoising and deblurring are becoming increasingly popular for the postreconstruction enhancement of PET images. We present a detailed review of recent efforts for artificial intelligence-based PET image enhancement with a focus on network architectures, data types, loss functions, and evaluation metrics. We also… Expand

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