Finding novelty with uncertainty

@inproceedings{Reinhold2020FindingNW,
  title={Finding novelty with uncertainty},
  author={Jacob C. Reinhold and Yufan He and Shizhong Han and Yunqiang Chen and Dashan Gao and Junghoon Lee and Jerry L Prince and Aaron Carass},
  booktitle={Medical Imaging: Image Processing},
  year={2020}
}
Medical images are often used to detect and characterize pathology and disease; however, automatically identifying and segmenting pathology in medical images is challenging because the appearance of pathology across diseases varies widely. To address this challenge, we propose a Bayesian deep learning method that learns to translate healthy computed tomography images to magnetic resonance images and simultaneously calculates voxel-wise uncertainty. Since high uncertainty occurs in pathological… 

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