% ========== MEDICAL APPLICATIONS & ANOMALY DETECTION ==========
@article{,
  title={A brain tumor segmentation framework based on outlier detection},
  author={Prastawa, Marcel and Bullitt, Elizabeth and Ho, Sean and Gerig, Guido},
  journal={Medical image analysis},
  volume={8},
  number={3},
  pages={275--283},
  year={2004},
  publisher={Elsevier}
}

@article{kamber1995model,
  title={Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images},
  author={Kamber, Micheline and Shinghal, Rajjan and Collins, D Louis and Francis, Gordon S and Evans, Alan C},
  journal={IEEE Transactions on Medical Imaging},
  volume={14},
  number={3},
  pages={442--453},
  year={1995},
  publisher={IEEE}
}

@article{Baur2020a,
  title={Autoencoders for unsupervised anomaly segmentation in brain mr images: A comparative study},
  author={Baur, Christoph and Denner, Stefan and Wiestler, Benedikt and Navab, Nassir and Albarqouni, Shadi},
  journal={Medical Image Analysis},
  pages={101952},
  year={2021},
  publisher={Elsevier}
}

@inproceedings{Zimmerer2020,
  title={Unsupervised anomaly localization using variational auto-encoders},
  author={Zimmerer, David and Isensee, Fabian and Petersen, Jens and Kohl, Simon and Maier-Hein, Klaus},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={289--297},
  year={2019},
  organization={Springer}
}

@article{Ronneberger2015,
archivePrefix = {arXiv},
arxivId = {1505.04597},
author = {Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
doi = {10.1007/978-3-319-24574-4\_28},
eprint = {1505.04597},
isbn = {9783319245737},
issn = {16113349},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
pages = {234--241},
title = {{U-net: Convolutional networks for biomedical image segmentation}},
volume = {9351},
year = {2015}
}

@article{Martensson2020,
archivePrefix = {arXiv},
arxivId = {1911.00515},
author = {M{\aa}rtensson, Gustav and Ferreira, Daniel and Granberg, Tobias and Cavallin, Lena and Oppedal, Ketil and Padovani, Alessandro and Rektorova, Irena and Bonanni, Laura and Pardini, Matteo and Kramberger, Milica G and Taylor, John-Paul and Hort, Jakub and Sn{\ae}dal, J{\'{o}}n and Kulisevsky, Jaime and Blanc, Frederic and Antonini, Angelo and Mecocci, Patrizia and Vellas, Bruno and Tsolaki, Magda and K{\l}oszewska, Iwona and Soininen, Hilkka and Lovestone, Simon and Simmons, Andrew and Aarsland, Dag and Westman, Eric},
doi = {10.1016/j.media.2020.101714},
eprint = {1911.00515},
issn = {13618415},
journal = {Medical Image Analysis},
keywords = {OOD Detection},
mendeley-tags = {OOD Detection},
pages = {101714},
title = {{The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study}},
year = {2020}
}

@article{Chen2020,
arxivId = {2005.00031},
author = {Chen, Xiaoran and You, Suhang and Tezcan, Kerem Can and Konukoglu, Ender},
doi = {10.1016/j.media.2020.101713},
eprint = {2005.00031},
issn = {13618423},
journal = {Medical Image Analysis},
keywords = {Autoencoding models,Lesion detection,Medical,Unsupervised Anomaly Detection,Unsupervised learning},
mendeley-tags = {Medical,Unsupervised Anomaly Detection},
pages = {540--556},
title = {{Unsupervised lesion detection via image restoration with a normative prior}},
volume = {64},
year = {2020}
}

@article{VanLeemput2001,
doi = {10.1109/42.938237},
issn = {02780062},
journal = {IEEE Transactions on Medical Imaging},
keywords = {Digital brain atlas,MRI,Multiple sclerosis,Tissue classification},
number = {8},
pages = {677--688},
pmid = {11513020},
title = {{Automated segmentation of multiple sclerosis lesions by model outlier detection}},
volume = {20},
year = {2001}
}

@article{Schlegl2019,
title = {f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks},
journal = {Medical Image Analysis},
volume = {54},
pages = {30-44},
year = {2019},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2019.01.010},
url = {https://www.sciencedirect.com/science/article/pii/S1361841518302640},
author = {Thomas Schlegl and Philipp Seeböck and Sebastian M. Waldstein and Georg Langs and Ursula Schmidt-Erfurth},
keywords = {Anomaly detection, Wasserstein generative adversarial network, Unsupervised learning, Optical coherence tomography}
}

@article{Schlegl2017,
archivePrefix = {arXiv},
arxivId = {1703.05921},
author = {Schlegl, Thomas and Seeb{\"{o}}ck, Philipp and Waldstein, Sebastian M. and Schmidt-Erfurth, Ursula and Langs, Georg},
doi = {10.1007/978-3-319-59050-9\_12},
eprint = {1703.05921},
isbn = {9783319590493},
issn = {16113349},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
pages = {146--147},
title = {{Unsupervised anomaly detection with generative adversarial networks to guide marker discovery}},
volume = {10265 LNCS},
year = {2017}
}

@article{Chen2018a,
archivePrefix = {arXiv},
arxivId = {1806.04972},
author = {Chen, Xiaoran and Konukoglu, Ender},
eprint = {1806.04972},
keywords = {Medical,Unsupervised Anomaly Detection},
mendeley-tags = {Medical,Unsupervised Anomaly Detection},
number = {Midl},
pages = {1--9},
title = {{Unsupervised Detection of Lesions in Brain MRI using constrained adversarial auto-encoders}},
url = {http://arxiv.org/abs/1806.04972},
year = {2018}
}

@inproceedings{Baur2019a,
  title={Deep autoencoding models for unsupervised anomaly segmentation in brain MR images},
  author={Baur, Christoph and Wiestler, Benedikt and Albarqouni, Shadi and Navab, Nassir},
  booktitle={International MICCAI Brainlesion Workshop},
  pages={161--169},
  year={2018},
  organization={Springer}
}

@article{valverde2017improving,
  title={Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach},
  author={Valverde, Sergi and Cabezas, Mariano and Roura, Eloy and Gonz{\'a}lez-Vill{\`a}, Sandra and Pareto, Deborah and Vilanova, Joan C and Rami{\'o}-Torrent{\`a}, Llu{\'\i}s and Rovira, {\`A}lex and Oliver, Arnau and Llad{\'o}, Xavier},
  journal={NeuroImage},
  volume={155},
  pages={159--168},
  year={2017},
  publisher={Elsevier}
}


@article{carass2017,
title = {Longitudinal multiple sclerosis lesion segmentation: Resource and challenge},
journal = {NeuroImage},
volume = {148},
pages = {77-102},
year = {2017},
issn = {1053-8119},
doi = {https://doi.org/10.1016/j.neuroimage.2016.12.064},
url = {https://www.sciencedirect.com/science/article/pii/S1053811916307819},
author = {Aaron Carass and Snehashis Roy and Amod Jog and Jennifer L. Cuzzocreo and Elizabeth Magrath and Adrian Gherman and Julia Button and James Nguyen and Ferran Prados and Carole H. Sudre and Manuel {Jorge Cardoso} and Niamh Cawley and Olga Ciccarelli and Claudia A.M. Wheeler-Kingshott and Sébastien Ourselin and Laurence Catanese and Hrishikesh Deshpande and Pierre Maurel and Olivier Commowick and Christian Barillot and Xavier Tomas-Fernandez and Simon K. Warfield and Suthirth Vaidya and Abhijith Chunduru and Ramanathan Muthuganapathy and Ganapathy Krishnamurthi and Andrew Jesson and Tal Arbel and Oskar Maier and Heinz Handels and Leonardo O. Iheme and Devrim Unay and Saurabh Jain and Diana M. Sima and Dirk Smeets and Mohsen Ghafoorian and Bram Platel and Ariel Birenbaum and Hayit Greenspan and Pierre-Louis Bazin and Peter A. Calabresi and Ciprian M. Crainiceanu and Lotta M. Ellingsen and Daniel S. Reich and Jerry L. Prince and Dzung L. Pham},
keywords = {Magnetic resonance imaging, Multiple sclerosis},
}

@article{moraal2010,
author = {Moraal, Bastiaan and Wattjes, Mike P. and Geurts, Jeroen J. G. and Knol, Dirk L. and van Schijndel, Ronald A. and Pouwels, Petra J. W. and Vrenken, Hugo and Barkhof, Frederik},
title = {Improved Detection of Active Multiple Sclerosis Lesions: 3D Subtraction Imaging},
journal = {Radiology},
volume = {255},
number = {1},
pages = {154-163},
year = {2010},
doi = {10.1148/radiol.09090814},
    note ={PMID: 20308453},

URL = { 
        https://doi.org/10.1148/radiol.09090814
    
},
eprint = { 
        https://doi.org/10.1148/radiol.09090814
    
}
}


% ========== OUT-OF-DISTRIBUTION DETECTION FOR GENERATIVE MODELS ========Kingma2014a==
@article{bishop1994novelty,
  title={Novelty detection and neural network validation},
  author={Bishop, Christopher M},
  journal={IEE Proceedings-Vision, Image and Signal processing},
  volume={141},
  number={4},
  pages={217--222},
  year={1994},
  publisher={IET}
}

@article{Choi2019,
archivePrefix = {arXiv},
arxivId = {1810.01392},
author = {Choi, Hyunsun and Jang, Eric and Alemi, Alexander A.},
eprint = {1810.01392},
journal = {ICLR},
title = {{WAIC, but Why? Generative Ensembles for Robust Anomaly Detection}},
url = {http://arxiv.org/abs/1810.01392},
year = {2019}
}

@article{Nalisnick2019a,
archivePrefix = {arXiv},
arxivId = {arXiv:1810.09136v3},
author = {Nalisnick, Eric and Matsukawa, Akihiro and Teh, Yee Whye and Gorur, Dilan and Lakshminarayanan, Balaji},
eprint = {arXiv:1810.09136v3},
journal = {7th International Conference on Learning Representations, ICLR 2019},
keywords = {Generative Model,OOD Detection},
mendeley-tags = {Generative Model,OOD Detection},
pages = {1--19},
title = {{Do deep generative models know what they don't know?}},
year = {2019}
}

@article{Nalisnick2019,
archivePrefix = {arXiv},
arxivId = {1906.02994},
author = {Nalisnick, Eric and Matsukawa, Akihiro and Teh, Yee Whye and Lakshminarayanan, Balaji},
eprint = {1906.02994},
pages = {1--15},
title = {{Detecting Out-of-Distribution Inputs to Deep Generative Models Using Typicality}},
url = {http://arxiv.org/abs/1906.02994},
year = {2019}
}

@article{Ren2019a,
archivePrefix = {arXiv},
arxivId = {1906.02845},
author = {Ren, Jie and Liu, Peter J. and Fertig, Emily and Snoek, Jasper and Poplin, Ryan and DePristo, Mark A. and Dillon, Joshua V. and Lakshminarayanan, Balaji},
eprint = {1906.02845},
journal = {arXiv},
number = {NeurIPS},
title = {{Likelihood ratios for out-of-distribution detection}},
year = {2019}
}

@article{Morningstar2020,
archivePrefix = {arXiv},
arxivId = {2006.09273},
author = {Morningstar, Warren R. and Ham, Cusuh and Gallagher, Andrew G. and Lakshminarayanan, Balaji and Alemi, Alexander A. and Dillon, Joshua V.},
eprint = {2006.09273},
keywords = {OOD detection},
mendeley-tags = {OOD detection},
title = {{Density of States Estimation for Out-of-Distribution Detection}},
url = {http://arxiv.org/abs/2006.09273},
year = {2020}
}

@article{TAYLOR2017262,
annote = {Data Sharing Part II},
author = {Taylor, Jason R and Williams, Nitin and Cusack, Rhodri and Auer, Tibor and Shafto, Meredith A and Dixon, Marie and Tyler, Lorraine K and Cam-CAN and Henson, Richard N},
doi = {https://doi.org/10.1016/j.neuroimage.2015.09.018},
issn = {1053-8119},
journal = {NeuroImage},
keywords = { Ageing, Brain imaging, Cognition, Magnetic resonance imaging, Magnetoencephalography,Data repository},
pages = {262--269},
title = {{The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample}},
url = {http://www.sciencedirect.com/science/article/pii/S1053811915008150},
volume = {144},
year = {2017}
}

@article{BraTS17,
  title={The multimodal brain tumor image segmentation benchmark (BRATS)},
  author={Menze, Bjoern H and Jakab, Andras and Bauer, Stefan and Kalpathy-Cramer, Jayashree and Farahani, Keyvan and Kirby, Justin and Burren, Yuliya and Porz, Nicole and Slotboom, Johannes and Wiest, Roland and others},
  journal={IEEE transactions on medical imaging},
  volume={34},
  number={10},
  pages={1993--2024},
  year={2014},
  publisher={IEEE}
}


@article{Konukoglu2018,
  title={Reconstructing subject-specific effect maps},
  author={Konukoglu, Ender and Glocker, Ben and Alzheimer's Disease Neuroimaging Initiative and others},
  journal={NeuroImage},
  volume={181},
  pages={521--538},
  year={2018},
  publisher={Elsevier}
}

% ========== GENERATIVE MODELS ==========
@article{Goodfellow2014,
archivePrefix = {arXiv},
arxivId = {arXiv:1406.2661v1},
author = {Goodfellow, Ian J. and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
eprint = {arXiv:1406.2661v1},
issn = {10495258},
journal = {Advances in Neural Information Processing Systems},
keywords = {GAN},
mendeley-tags = {GAN},
number = {January},
pages = {2672--2680},
title = {{Generative adversarial nets}},
volume = {3},
year = {2014}
}

@article{Kingma2014a,
archivePrefix = {arXiv},
arxivId = {1312.6114},
author = {Kingma, Diederik P. and Welling, Max},
eprint = {1312.6114},
journal = {2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings},
keywords = {Representation Learning,VAE},
mendeley-tags = {Representation Learning,VAE},
number = {Ml},
pages = {1--14},
title = {{Auto-encoding variational bayes}},
year = {2014}
}


@article{Louizos2017,
arxivId = {1703.01961},
author = {Louizos, Christos and Welling, Max},
eprint = {1703.01961},
isbn = {9781510855144},
journal = {34th International Conference on Machine Learning, ICML 2017},
pages = {3480--3489},
title = {{Multiplicative normalizing flows for variational Bayesian neural networks}},
volume = {5},
year = {2017}
}

% ========== MISCELLANEOUS ==========
@inproceedings{Kiefer1953SequentialMS,
  title={Sequential minimax search for a maximum},
  author={J. Kiefer},
  year={1953}
}

@article{n4_bias_correction,
  title={N4ITK: improved N3 bias correction},
  author={Tustison, Nicholas J and Avants, Brian B and Cook, Philip A and Zheng, Yuanjie and Egan, Alexander and Yushkevich, Paul A and Gee, James C},
  journal={IEEE transactions on medical imaging},
  volume={29},
  number={6},
  pages={1310--1320},
  year={2010},
  publisher={IEEE}
}