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Uncertainty quantification in multi-class segmentation: Comparison between Bayesian and non-Bayesian approaches in a clinical perspective.

Elisa ScalcoSilvia PozziGiovanna RizzoEttore Lanzarone
Published in: Medical physics (2024)
Our outcomes highlight the importance of quantifying the segmentation uncertainty and that decision-makers can choose the approach most in line with the risk propensity degree required by the application and their policy.
Keyphrases
  • deep learning
  • convolutional neural network
  • public health
  • healthcare
  • mental health
  • decision making
  • type diabetes
  • machine learning
  • metabolic syndrome
  • insulin resistance
  • glycemic control