Deep segmentation networks predict survival of non-small cell lung cancer

@article{Baek2019DeepSN,
  title={Deep segmentation networks predict survival of non-small cell lung cancer},
  author={Stephen Seung-Yeob Baek and Yusen He and Bryan G. Allen and John M. Buatti and Brian J. Smith and Ling Tong and Zhiyu Sun and Jia Wu and Maximilian Diehn and Billy W. Loo and Kristin A. Plichta and Steven N. Seyedin and Maggie Gannon and Katherine R. Cabel and Yusung Kim and Xiaodong Wu},
  journal={Scientific Reports},
  year={2019},
  volume={9}
}
Non-small-cell lung cancer (NSCLC) represents approximately 80–85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography/computed tomography (PET/CT) images have predictive power for NSCLC outcomes. To this end, easily calculated functional features such as the maximum and the mean of standard uptake value (SUV) and total lesion glycolysis (TLG) are most commonly used for… Expand
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