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Distribution-informed and wavelength-flexible data-driven photoacoustic oximetry.

Janek GröhlKylie YeungKevin GuThomas R ElseMonika GolinskaEllie V BunceLina HackerSarah Elizabeth Bohndiek
Published in: Journal of biomedical optics (2024)
A flexible data-driven network architecture combined with the Jensen-Shannon divergence to predict the best training data set provides a promising direction that might enable robust data-driven photoacoustic oximetry for clinical use cases.
Keyphrases
  • fluorescence imaging
  • electronic health record
  • big data
  • solid state
  • virtual reality
  • photodynamic therapy
  • machine learning
  • deep learning
  • network analysis