Corpus ID: 237572171

Robust Automated Framework for COVID-19 Disease Identification from a Multicenter Dataset of Chest CT Scans

@article{Heidarian2021RobustAF,
  title={Robust Automated Framework for COVID-19 Disease Identification from a Multicenter Dataset of Chest CT Scans},
  author={Shahin Heidarian and Parnian Afshar and Nastaran Enshaei and Farnoosh Naderkhani and Moezedin Javad Rafiee and Anastasia Oikonomou and Akbar Shafiee and Faranak Babaki Fard and Konstantinos N. Plataniotis and Arash Mohammadi},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.09241}
}
The objective of this study is to develop a robust deep learning-based framework to distinguish COVID-19, Community-Acquired Pneumonia (CAP), and Normal cases based on chest CT scans, which are acquired in different imaging centers using various scanners, scanning protocols, and radiation doses. We showed that while our proposed model is trained on a relatively small dataset acquired from only one imaging center using a specific scanning protocol, the model performs well on heterogeneous test… Expand

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