@article{NoisyStudent,
  title={Self-training with Noisy Student improves ImageNet classification},
  author={Qizhe Xie and Eduard Hovy and Minh-Thang Luong and Quoc V. Le},
  journal={arXiv preprint arXiv:1911.04252},
  year={2019}
}

@article{Hinton2015,
  title={Distilling the Knowledge in a Neural Network},
  author={Geoffrey E. Hinton and Oriol Vinyals and Jeffrey Dean},
  journal={ArXiv},
  year={2015},
  volume={abs/1503.02531}
}

@inproceedings{Shaw2019,
  title={MRI k-Space Motion Artefact Augmentation: Model Robustness and Task-Specific Uncertainty},
  author={Richard Shaw and Carole H. Sudre and S{\'e}bastien Ourselin and M. Jorge Cardoso},
  booktitle={MIDL},
  year={2019}
}

@article{fastMRI,
  title={fastMRI: An Open Dataset and Benchmarks for Accelerated MRI},
  author={Jure Zbontar and Florian Knoll and Anuroop Sriram and Matthew J. Muckley and Mary Bruno and others},
  journal={ArXiv},
  year={2018},
  volume={abs/1811.08839}
}

@inproceedings{Tarvainen2017,
  title={Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results},
  author={Antti Tarvainen and Harri Valpola},
  booktitle={NIPS},
  year={2017}
}

@article{Zhuo2006,
  title={AAPM/RSNA physics tutorial for residents: MR artifacts, safety, and quality control.},
  author={Jiachen Zhuo and Rao P. Gullapalli},
  journal={Radiographics},
  year={2006},
  volume={26 1},
  pages={275--97}
}

@inproceedings{Sudre19,
  author    = {Carole H. Sudre and
               Beatriz Gomez Anson and
               Silvia Ingala and
               Chris D. Lane and
               Daniel Jimenez and
               others},
  title     = {Let's Agree to Disagree: Learning Highly Debatable Multirater Labelling},
  booktitle = {MICCAI},
  pages     = {665--673},
  year      = {2019}
}

@article{Graham2018,
  title={A supervised learning approach for diffusion MRI quality control with minimal training data},
  author={Mark S. Graham and Ivana Drobnjak and Hui Zhang},
  journal={NeuroImage},
  year={2018},
  volume={178},
  pages={668--676}
}

@inproceedings{Wang2018,
  title={Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks},
  author={Guotai Wang and Wenqi Li and Michael Aertsen and Jan Deprest and S{\'e}bastien Ourselin and others},
  booktitle={Neurocomputing},
  year={2018}
}

@article{Tanno2019UncertaintyQI,
  title={Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement},
  author={Ryutaro Tanno and Daniel Worrall and Enrico Kaden and Aurobrata Ghosh and Francesco Grussu and others},
  journal={ArXiv},
  year={2019},
  url={http://arxiv.org/abs/1907.13418}
}

@article{Kendall2017,
  title={Multi-task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics},
  author={Alex Kendall and Yarin Gal and Roberto Cipolla},
  journal={CVPR},
  year={2017},
  pages={7482--7491}
}

@inproceedings{Kendall2,
  title={What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?},
  author={Alex Kendall and Yarin Gal},
  booktitle={NIPS},
  year={2017}
}

@inproceedings{Bragman2018,
  title={Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning},
  author={Felix J. S. Bragman and Ryutaro Tanno and Zach Eaton-Rosen and Wenqi Li and David J. Hawkes and others},
  booktitle={MICCAI},
  year={2018}
}

@article{ladefoged2017multi,
 title={A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients},
 author={Ladefoged, Claes N and others},
 journal={Neuroimage},
 volume={147},
 pages={346--359},
 year={2017}
}


@article{XiaoHan,
  title={MR-based synthetic CT generation using a deep convolutional neural network method},
  author={Han, Xiao},
  journal={Medical physics},
  volume={44},
  number={4},
  pages={1408--1419},
  year={2017}
}

@inproceedings{Wenqi,
  title={On the compactness, efficiency, and representation of 3D convolutional networks: brain parcellation as a pretext task},
  author={Li, Wenqi and others},
  booktitle={IPMI},
  pages={348--360},
  year={2017}
}

@article{AdaBoost,
  title={A decision-theoretic generalization of on-line learning and an application to boosting},
  author={Freund, Yoav and others},
  journal={Journal of computer and system sciences},
  volume={55},
  number={1},
  pages={119--139},
  year={1997}
}

@article{NiftyNet,
  author    = {Eli Gibson and others},
  title     = {NiftyNet: a deep-learning platform for medical imaging},
  journal   = {CoRR},
  year      = {2017},
  url       = {http://arxiv.org/abs/1709.03485},
  archivePrefix = {arXiv},
  eprint    = {1709.03485},
  timestamp = {Thu, 05 Oct 2017 09:42:53 +0200}
}

@inproceedings{Nie,
  title={Medical image synthesis with context-aware generative adversarial networks},
  author={Nie, Dong and others},
  booktitle={MICCAI},
  pages={417--425},
  year={2017},
  organization={Springer}
}

@inproceedings{Adam,
 author    = {Diederik P. Kingma and
              Jimmy Ba},
 title     = {Adam: {A} Method for Stochastic Optimization},
 booktitle = {ICLR},
 year      = {2015},
 url       = {http://arxiv.org/abs/1412.6980},
 timestamp = {Thu, 25 Jul 2019 01:00:00 +0200}
}

@article{Net1,
  title={Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation},
  author={Kamnitsas, Konstantinos and others},
  journal={Medical image analysis},
  volume={36},
  pages={61--78},
  year={2017},
  publisher={Elsevier}
}

@article{Net2,
  title={Deep MRI brain extraction: a 3D convolutional neural network for skull stripping},
  author={Kleesiek, Jens and others},
  journal={NeuroImage},
  volume={129},
  pages={460--469},
  year={2016},
  publisher={Elsevier}
}


@article{Lorenz,
  title={An Adaptive Sampling Scheme to Efficiently Train Fully Convolutional Networks for Semantic Segmentation},
  author={Berger, Lorenz and others},
  journal={arXiv preprint arXiv:1709.02764},
  year={2017}
}


@inproceedings{rupprecht2017learning,
 title={Learning in an uncertain world: Representing ambiguity through multiple hypotheses},
 author={Rupprecht, Christian and others},
 booktitle={Proceedings of the IEEE ICCV},
 pages={3591--3600},
 year={2017}
}

@article{He,
author    = {Kaiming He and
               others},
title     = {Deep Residual Learning for Image Recognition},
journal   = {CoRR},
volume    = {abs/1512.03385},
year      = {2015},
url       = {http://arxiv.org/abs/1512.03385},
archivePrefix = {arXiv},
eprint    = {1512.03385},
timestamp = {Wed, 07 Jun 2017 14:41:17 +0200},
biburl    = {https://dblp.org/rec/bib/journals/corr/HeZRS15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{sutton2000policy,
  title={Policy gradient methods for reinforcement learning with function approximation},
  author={Sutton, Richard S and McAllester, David A and Singh, Satinder P and Mansour, Yishay},
  booktitle={Advances in neural information processing systems},
  pages={1057--1063},
  year={2000}
}


@article{Prado2019DualNN,
  title={Dual Neural Network Architecture for Determining Epistemic and Aleatoric Uncertainties},
  author={Augustin Prado and Ravinath Kausik and Lalitha Venkataramanan},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.06153}
}

@inproceedings{Hu2019,
  title={Supervised Uncertainty Quantification for Segmentation with Multiple Annotations},
  author={Shi Hu and Daniel Worrall and Stefan J. L. Knegt and Bas Veeling and Henkjan J. Huisman and others},
  booktitle={MICCAI},
  year={2019}
}

@inproceedings{Isensee2019,
  title={Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation},
  author={Fabian Isensee and Jens Petersen and Andr{\'e} Klein and David Zimmerer and Paul F. Jaeger and others},
  booktitle={Bildverarbeitung f{\"u}r die Medizin},
  year={2019}
}

@inproceedings{EatonRosen2019,
  title={As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging},
  author={Zach Eaton-Rosen and Thomas Varsavsky and S{\'e}bastien Ourselin and M. Jorge Cardoso},
  booktitle={MICCAI},
  year={2019}
}

@article{Jee1986,
author = {Debabrata Mukher Jee  and  Makarand V   Ratnaparkhi},
title = {On the functional relationship between entropy and variance with related applications},
journal = {Communications in Statistics - Theory and Methods},
volume = {15},
number = {1},
pages = {291-311},
year  = {1986},
publisher = {Taylor & Francis},
eprint = {https://www.tandfonline.com/doi/pdf/10.1080/03610928608829122}
}

