Corpus ID: 22323188

Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation

@article{Jungo2018UncertaintydrivenSC,
  title={Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation},
  author={Alain Jungo and R. Meier and Ekin Ermis and E. Herrmann and M. Reyes},
  journal={ArXiv},
  year={2018},
  volume={abs/1806.03106}
}
  • Alain Jungo, R. Meier, +2 authors M. Reyes
  • Published 2018
  • Computer Science
  • ArXiv
  • Uncertainty estimates of modern neuronal networks provide additional information next to the computed predictions and are thus expected to improve the understanding of the underlying model. Reliable uncertainties are particularly interesting for safety-critical computer-assisted applications in medicine, e.g., neurosurgical interventions and radiotherapy planning. We propose an uncertainty-driven sanity check for the identification of segmentation results that need particular expert review. Our… CONTINUE READING

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