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Polarimetric imaging for cervical pre-cancer screening aided by machine learning: ex vivo studies.

Demelza RobinsonKevin HoongWillem Bastiaan KleijnAlexander DoroninJean RehbinderJeremy VizetAngelo PierangeloTatiana Novikova
Published in: Journal of biomedical optics (2023)
Combination of Mueller polarimetry and machine learning is a powerful tool for the task of screening for pre-cancerous conditions in cervical tissue sections. Nevertheless, there is a inherent bias with conventional processes that can be addressed using more conservative classifier training approaches. This results in overall improvements of the sensitivity and specificity of the developed techniques for "unseen" images.
Keyphrases
  • machine learning
  • deep learning
  • artificial intelligence
  • papillary thyroid
  • high resolution
  • big data
  • convolutional neural network
  • squamous cell
  • optical coherence tomography
  • childhood cancer
  • mass spectrometry