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Early esophageal adenocarcinoma detection using deep learning methods.

Noha GhatwaryMassoud ZolgharniXujiong Ye
Published in: International journal of computer assisted radiology and surgery (2019)
In this paper, recent deep learning object detection methods are adapted to detect esophageal abnormalities automatically. The evaluation of the methods proved its ability to locate abnormal regions in the esophagus from endoscopic images. The automatic detection is a crucial step that may help early detection and treatment of EAC and also can improve automatic tumor segmentation to monitor its growth and treatment outcome.
Keyphrases
  • deep learning
  • convolutional neural network
  • artificial intelligence
  • loop mediated isothermal amplification
  • machine learning
  • real time pcr
  • label free
  • squamous cell carcinoma
  • quantum dots
  • smoking cessation