• Corpus ID: 220249738

Generalizable Cone Beam CT Esophagus Segmentation Using In Silico Data Augmentation

@article{Alam2020GeneralizableCB,
  title={Generalizable Cone Beam CT Esophagus Segmentation Using In Silico Data Augmentation},
  author={Sadegh R. Alam and Tianfang Li and Si-Yuan Zhang and Pengpeng Zhang and Saad Nadeem},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.15713}
}
Lung cancer radiotherapy entails high quality planning computed tomography (pCT) imaging of the patient with radiation oncologist contouring of the tumor and the organs at risk (OARs) at the start of the treatment. This is followed by weekly low-quality cone beam CT (CBCT) imaging for treatment setup and qualitative visual assessment of tumor and critical OARs. In this work, we aim to make the weekly CBCT assessment quantitative by automatically segmenting the most critical OAR, esophagus… 

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