@book{Lamport:Book:1989,
 author = {Lamport, Leslie},
 title = {Latex: A Document Preparation System},
 year = {1986},
 isbn = {0-201-15790-X},
 publisher = {Addison-Wesley Longman Publishing Co., Inc.},
 address = {Boston, MA, USA},
}
@article{li2020deepretina,
  title={DeepRetina: layer segmentation of retina in OCT images using deep learning},
  author={Li, Qiaoliang and Li, Shiyu and He, Zhuoying and Guan, Huimin and Chen, Runmin and Xu, Ying and Wang, Tao and Qi, Suwen and Mei, Jun and Wang, Wei},
  journal={Translational vision science \& technology},
  volume={9},
  number={2},
  pages={61--61},
  year={2020},
  publisher={The Association for Research in Vision and Ophthalmology}
}

@inproceedings{lan2020elastic,
  title={An elastic interaction-based loss function for medical image segmentation},
  author={Lan, Yuan and Xiang, Yang and Zhang, Luchan},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2020: 23rd International Conference, Lima, Peru, October 4--8, 2020, Proceedings, Part V 23},
  pages={755--764},
  year={2020},
  organization={Springer}
}

@inproceedings{lin2023dtu,
  title={DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation},
  author={Lin, Manxi and Zepf, Kilian and Christensen, Anders Nymark and Bashir, Zahra and Svendsen, Morten Bo S{\o}ndergaard and Tolsgaard, Martin and Feragen, Aasa},
  booktitle={International Conference on Information Processing in Medical Imaging},
  pages={654--666},
  year={2023},
  organization={Springer}
}

@article{lou2020fast,
  title={Fast retinal segmentation based on the wave algorithm},
  author={Lou, Shiliang and Chen, Xiaodong and Han, Xiaoyan and Liu, Jing and Wang, Yi and Cai, Huaiyu},
  journal={IEEE Access},
  volume={8},
  pages={53678--53686},
  year={2020},
  publisher={IEEE}
}
@article{chen2019automated,
  title={Automated retinal layer segmentation in OCT images of age-related macular degeneration},
  author={Chen, Zailiang and Li, Dabao and Shen, Hailan and Mo, Yufang and Wei, Hao and Ouyang, Pingbo},
  journal={IET Image Processing},
  volume={13},
  number={11},
  pages={1824--1834},
  year={2019},
  publisher={Wiley Online Library}
}
@article{kugelman2018automatic,
  title={Automatic segmentation of OCT retinal boundaries using recurrent neural networks and graph search},
  author={Kugelman, Jason and Alonso-Caneiro, David and Read, Scott A and Vincent, Stephen J and Collins, Michael J},
  journal={Biomedical optics express},
  volume={9},
  number={11},
  pages={5759--5777},
  year={2018},
  publisher={Optica Publishing Group}
}

@INPROCEEDINGS{8959021,
  author={Jha, Debesh and Smedsrud, Pia H. and Riegler, Michael A. and Johansen, Dag and Lange, Thomas De and Halvorsen, Pål and D. Johansen, Håvard},
  booktitle={2019 IEEE International Symposium on Multimedia (ISM)}, 
  title={ResUNet++: An Advanced Architecture for Medical Image Segmentation}, 
  year={2019},
  volume={},
  number={},
  pages={225-2255},
  keywords={Medical image analysis, semantic segmentation, colonoscopy, polyp segmentation, deep learning, health informatics},
  doi={10.1109/ISM46123.2019.00049}}

@article{santos2019diagnostico,
  title={DIAGN{\'O}STICO DE DEGENERA{\c{C}}{\~A}O MACULAR RELACIONADA {\`A} IDADE A PARTIR DE TOMOGRAFIA DE COER{\^E}NCIA {\'O}PTICA USANDO GEOESTAT{\'I}STICA E CAPSULE NETWORKS.},
  author={Santos, Alex Martins and others},
  year={2019},
  publisher={Universidade Federal do Maranh{\~a}o}
}

@article{sousa2021automatic,
  title={Automatic segmentation of retinal layers in OCT images with intermediate age-related macular degeneration using U-Net and DexiNed},
  author={Sousa, Jefferson Alves and Paiva, Anselmo and Silva, Arist{\'o}fanes and Almeida, Jo{\~a}o Dallyson and Braz Junior, Geraldo and Diniz, Jo{\~a}o Ot{\'a}vio and Figueredo, Weslley Kelson and Gattass, Marcelo},
  journal={Plos one},
  volume={16},
  number={5},
  pages={e0251591},
  year={2021},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{farsiu2014quantitative,
  title={Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography},
  author={Farsiu, Sina and Chiu, Stephanie J and O'Connell, Rachelle V and Folgar, Francisco A and Yuan, Eric and Izatt, Joseph A and Toth, Cynthia A and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group and others},
  journal={Ophthalmology},
  volume={121},
  number={1},
  pages={162--172},
  year={2014},
  publisher={Elsevier}
}
@article{abdar2021review,
  title={A review of uncertainty quantification in deep learning: Techniques, applications and challenges},
  author={Abdar, Moloud and Pourpanah, Farhad and Hussain, Sadiq and Rezazadegan, Dana and Liu, Li and Ghavamzadeh, Mohammad and Fieguth, Paul and Cao, Xiaochun and Khosravi, Abbas and Acharya, U Rajendra and others},
  journal={Information fusion},
  volume={76},
  pages={243--297},
  year={2021},
  publisher={Elsevier}
}
@article{lakshminarayanan2017simple,
  title={Simple and scalable predictive uncertainty estimation using deep ensembles},
  author={Lakshminarayanan, Balaji and Pritzel, Alexander and Blundell, Charles},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}
@article{kendall2017uncertainties,
  title={What uncertainties do we need in bayesian deep learning for computer vision?},
  author={Kendall, Alex and Gal, Yarin},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@inproceedings{dong2018psdf,
  title={PSDF fusion: Probabilistic signed distance function for on-the-fly 3D data fusion and scene reconstruction},
  author={Dong, Wei and Wang, Qiuyuan and Wang, Xin and Zha, Hongbin},
  booktitle={Proceedings of the European conference on computer vision (ECCV)},
  pages={701--717},
  year={2018}
}

@inproceedings{ma2020distance,
  title={How distance transform maps boost segmentation CNNs: an empirical study},
  author={Ma, Jun and Wei, Zhan and Zhang, Yiwen and Wang, Yixin and Lv, Rongfei and Zhu, Cheng and Gaoxiang, Chen and Liu, Jianan and Peng, Chao and Wang, Lei and others},
  booktitle={Medical Imaging with Deep Learning},
  pages={479--492},
  year={2020},
  organization={PMLR}
}

@article{bogensperger2023score,
  title={Score-based generative models for medical image segmentation using signed distance functions},
  author={Bogensperger, Lea and Narnhofer, Dominik and Ilic, Filip and Pock, Thomas},
  journal={arXiv preprint arXiv:2303.05966},
  year={2023}
}


@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}


@article{wang2022reliable,
  title={Reliable joint segmentation of retinal edema lesions in oct images},
  author={Wang, Meng and Yu, Kai and Feng, Chun-Mei and Zou, Ke and Xu, Yanyu and Meng, Qingquan and Goh, Rick Siow Mong and Liu, Yong and Fu, Huazhu},
  journal={arXiv preprint arXiv:2212.00330},
  year={2022}
}
@article{isensee2021nnu,
  title={nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation},
  author={Isensee, Fabian and Jaeger, Paul F and Kohl, Simon AA and Petersen, Jens and Maier-Hein, Klaus H},
  journal={Nature methods},
  volume={18},
  number={2},
  pages={203--211},
  year={2021},
  publisher={Nature Publishing Group}
}

@ARTICLE{Xue2020-dk,
  title     = "Shape-aware organ segmentation by predicting signed distance
               maps",
  author    = "Xue, Y and Tang, H and Qiao, Z and Gong, G and Yin, Y and Qian,
               Z and {others}",
  abstract  = "In this work, we propose to resolve the issue existing in
               current deep learning based organ segmentation systems that they
               often produce results that do not capture the overall shape …",
  journal   = "Proceedings of the",
  publisher = "ojs.aaai.org",
  year      =  2020
}



@InProceedings{Hu_2017_CVPR,
author = {Hu, Ping and Shuai, Bing and Liu, Jun and Wang, Gang},
title = {Deep Level Sets for Salient Object Detection},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}


@article{zhao2005fast,
  title={A fast sweeping method for eikonal equations},
  author={Zhao, Hongkai},
  journal={Mathematics of computation},
  volume={74},
  number={250},
  pages={603--627},
  year={2005}
}

@Article{su13031224,
AUTHOR = {Liu, Xiangbin and Song, Liping and Liu, Shuai and Zhang, Yudong},
TITLE = {A Review of Deep-Learning-Based Medical Image Segmentation Methods},
JOURNAL = {Sustainability},
VOLUME = {13},
YEAR = {2021},
NUMBER = {3},
ARTICLE-NUMBER = {1224},
URL = {https://www.mdpi.com/2071-1050/13/3/1224},
ISSN = {2071-1050}}

@article{hofman2007rotterdam,
  title={The Rotterdam Study: objectives and design update},
  author={Hofman, Albert and Breteler, Monique MB and van Duijn, Cornelia M and Krestin, Gabriel P and Pols, Huibert A and Stricker, Bruno H Ch and Tiemeier, Henning and Uitterlinden, Andr{\'e} G and Vingerling, Johannes R and Witteman, Jacqueline CM},
  journal={European journal of epidemiology},
  volume={22},
  pages={819--829},
  year={2007},
  publisher={Springer}
}



@article{todorich2012treatment,
  title={Treatment of pigment epithelial detachments in age-related macular degeneration},
  author={Todorich, BOZHO and Pepple, KATHRYN and Mruthyunjaya, PRITHVI},
  journal={Retin Physician},
  volume={9},
  pages={30--37},
  year={2012}
}

@article{10.1109/isbi.2019.8759329, author = {Abraham, N. and Khan, N.}, title = {A novel focal tversky loss function with improved attention u-net for lesion segmentation}, year = {2019}, doi = {10.1109/isbi.2019.8759329} }

@article{ngo2019deep,
  title={Deep neural network regression for automated retinal layer segmentation in optical coherence tomography images},
  author={Ngo, Lua and Cha, Jaepyeong and Han, Jae-Ho},
  journal={IEEE transactions on image processing},
  volume={29},
  pages={303--312},
  year={2019},
  publisher={IEEE}
}


@article{Kendall2017-fa,
  title={What uncertainties do we need in bayesian deep learning for computer vision?},
  author={Kendall, Alex and Gal, Yarin},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}


@article{gawlikowski2021survey,
  title={A survey of uncertainty in deep neural networks},
  author={Gawlikowski, Jakob and Tassi, Cedrique Rovile Njieutcheu and Ali, Mohsin and Lee, Jongseok and Humt, Matthias and Feng, Jianxiang and Kruspe, Anna and Triebel, Rudolph and Jung, Peter and Roscher, Ribana and others},
  journal={arXiv preprint arXiv:2107.03342},
  year={2021}
}

@article{de2023uncertainty,
  title={Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography},
  author={de Vente, Coen and van Ginneken, Bram and Hoyng, Carel B and Klaver, Caroline CW and S{\'a}nchez, Clara I},
  journal={arXiv preprint arXiv:2302.03116},
  year={2023}
}

@inproceedings{abraham2019novel,
  title={A novel focal tversky loss function with improved attention u-net for lesion segmentation},
  author={Abraham, Nabila and Khan, Naimul Mefraz},
  booktitle={2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019)},
  pages={683--687},
  year={2019},
  organization={IEEE}
}

@inproceedings{Xue2020-dk,
  title={Shape-aware organ segmentation by predicting signed distance maps},
  author={Xue, Yuan and Tang, Hui and Qiao, Zhi and Gong, Guanzhong and Yin, Yong and Qian, Zhen and Huang, Chao and Fan, Wei and Huang, Xiaolei},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={07},
  pages={12565--12572},
  year={2020}
}


@article{curatolo2013speckle,
  title={Speckle in optical coherence tomography},
  author={Curatolo, Andrea and Kennedy, Brendan F and Sampson, David D and Hillman, TR},
  journal={Advanced Biophotonics: Tissue Optical Sectioning},
  pages={211--277},
  year={2013},
  publisher={Taylor \& Francis}
}


@article{chhablani2014artifacts,
  title={Artifacts in optical coherence tomography},
  author={Chhablani, Jay and Krishnan, Tandava and Sethi, Vaibhav and Kozak, Igor},
  journal={Saudi Journal of Ophthalmology},
  volume={28},
  number={2},
  pages={81--87},
  year={2014},
  publisher={Elsevier}
}


@book{duker2021handbook,
  title={Handbook of Retinal OCT: Optical Coherence Tomography E-Book},
  author={Duker, Jay S and Waheed, Nadia K and Goldman, Darin},
  year={2021},
  publisher={Elsevier Health Sciences}
}


@article{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  journal={arXiv preprint arXiv:1412.6980},
  year={2014}
}

@INPROCEEDINGS{Liefers2019-md,
  title     = "Dense Segmentation in Selected Dimensions: Application to
               Retinal Optical Coherence Tomography",
  booktitle = "Proceedings of The 2nd International Conference on Medical
               Imaging with Deep Learning",
  author    = "Liefers, Bart and Gonz{\'a}lez-Gonzalo, Cristina and Klaver,
               Caroline and van Ginneken, Bram and S{\'a}nchez, Clara I",
  editor    = "Cardoso, M Jorge and Feragen, Aasa and Glocker, Ben and
               Konukoglu, Ender and Oguz, Ipek and Unal, Gozde and Vercauteren,
               Tom",
  publisher = "PMLR",
  volume    =  102,
  pages     = "337--346",
  series    = "Proceedings of Machine Learning Research",
  year      =  2019
}

@inproceedings{park2019deepsdf,
  title={Deepsdf: Learning continuous signed distance functions for shape representation},
  author={Park, Jeong Joon and Florence, Peter and Straub, Julian and Newcombe, Richard and Lovegrove, Steven},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={165--174},
  year={2019}
}


@article{osher1988fronts,
  title={Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations},
  author={Osher, Stanley and Sethian, James A},
  journal={Journal of computational physics},
  volume={79},
  number={1},
  pages={12--49},
  year={1988},
  publisher={Elsevier}
}


@article{danielsson1980euclidean,
  title={Euclidean distance mapping},
  author={Danielsson, Per-Erik},
  journal={Computer Graphics and image processing},
  volume={14},
  number={3},
  pages={227--248},
  year={1980},
  publisher={Elsevier}
}


@article{zhao1996variational,
  title={A variational level set approach to multiphase motion},
  author={Zhao, Hong-Kai and Chan, Tony and Merriman, Barry and Osher, Stanley},
  journal={Journal of computational physics},
  volume={127},
  number={1},
  pages={179--195},
  year={1996},
  publisher={Elsevier}
}


@Article{s23218739,
AUTHOR = {Cao, Ruifen and Ning, Long and Zhou, Chao and Wei, Pijing and Ding, Yun and Tan, Dayu and Zheng, Chunhou},
TITLE = {CFANet: Context Feature Fusion and Attention Mechanism Based Network for Small Target Segmentation in Medical Images},
JOURNAL = {Sensors},
VOLUME = {23},
YEAR = {2023},
NUMBER = {21},
ARTICLE-NUMBER = {8739},
URL = {https://www.mdpi.com/1424-8220/23/21/8739},
PubMedID = {37960438},
ISSN = {1424-8220},
DOI = {10.3390/s23218739}
}






@misc{Hinton:arXiv:2015:Distilling,
 title={Distilling the knowledge in a neural network},
 author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
 OPTeprinttype={arXiv},
 OPTeprint={1503.02531},
 howpublished={Eprint \href{http://arxiv.org/abs/1503.02531}{arXiv:1503.02531}},
 OPTurl={http://arxiv.org/abs/1503.02531},
 year=2015
}

@article{gabriele2011optical,
  title={Optical coherence tomography: history, current status, and laboratory work},
  author={Gabriele, Michelle L and Wollstein, Gadi and Ishikawa, Hiroshi and Kagemann, Larry and Xu, Juan and Folio, Lindsey S and Schuman, Joel S},
  journal={Investigative ophthalmology \& visual science},
  volume={52},
  number={5},
  pages={2425--2436},
  year={2011},
  publisher={The Association for Research in Vision and Ophthalmology}
}


@article{liu2024simultaneous,
  title={Simultaneous alignment and surface regression using hybrid 2D--3D networks for 3D coherent layer segmentation of retinal OCT images with full and sparse annotations},
  author={Liu, Hong and Wei, Dong and Lu, Donghuan and Tang, Xiaoying and Wang, Liansheng and Zheng, Yefeng},
  journal={Medical Image Analysis},
  volume={91},
  pages={103019},
  year={2024},
  publisher={Elsevier}
}

@article{kugelman2022comparison,
  title={A comparison of deep learning U-Net architectures for posterior segment OCT retinal layer segmentation},
  author={Kugelman, Jason and Allman, Joseph and Read, Scott A and Vincent, Stephen J and Tong, Janelle and Kalloniatis, Michael and Chen, Fred K and Collins, Michael J and Alonso-Caneiro, David},
  journal={Scientific reports},
  volume={12},
  number={1},
  pages={14888},
  year={2022},
  publisher={Nature Publishing Group UK London}
}


@article{morelle2023accurate,
  title={Accurate drusen segmentation in optical coherence tomography via order-constrained regression of retinal layer heights},
  author={Morelle, Olivier and Wintergerst, Maximilian WM and Finger, Robert P and Schultz, Thomas},
  journal={Scientific Reports},
  volume={13},
  number={1},
  pages={8162},
  year={2023},
  publisher={Nature Publishing Group UK London}
}

@article{he2021structured,
  title={Structured layer surface segmentation for retina OCT using fully convolutional regression networks},
  author={He, Yufan and Carass, Aaron and Liu, Yihao and Jedynak, Bruno M and Solomon, Sharon D and Saidha, Shiv and Calabresi, Peter A and Prince, Jerry L},
  journal={Medical image analysis},
  volume={68},
  pages={101856},
  year={2021},
  publisher={Elsevier}
}


@article{shah2018multiple,
  title={Multiple surface segmentation using convolution neural nets: application to retinal layer segmentation in OCT images},
  author={Shah, Abhay and Zhou, Leixin and Abr{\'a}moff, Michael D and Wu, Xiaodong},
  journal={Biomedical optics express},
  volume={9},
  number={9},
  pages={4509--4526},
  year={2018},
  publisher={Optica Publishing Group}
}

@article{ZOU2023100003,
title = {A review of uncertainty estimation and its application in medical imaging},
journal = {Meta-Radiology},
volume = {1},
number = {1},
pages = {100003},
year = {2023},
issn = {2950-1628},
doi = {https://doi.org/10.1016/j.metrad.2023.100003},
url = {https://www.sciencedirect.com/science/article/pii/S2950162823000036},
author = {Ke Zou and Zhihao Chen and Xuedong Yuan and Xiaojing Shen and Meng Wang and Huazhu Fu},
keywords = {Deep learning, Uncertainty estimation, Medical image analysis}
}

@inproceedings{raju2022deep,
  title={Deep implicit statistical shape models for 3d medical image delineation},
  author={Raju, Ashwin and Miao, Shun and Jin, Dakai and Lu, Le and Huang, Junzhou and Harrison, Adam P},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={36-2},
  pages={2135--2143},
  year={2022}
}

@inproceedings{xue2020shape,
  title={Shape-aware organ segmentation by predicting signed distance maps},
  author={Xue, Yuan and Tang, Hui and Qiao, Zhi and Gong, Guanzhong and Yin, Yong and Qian, Zhen and Huang, Chao and Fan, Wei and Huang, Xiaolei},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34-7},
  pages={12565--12572},
  year={2020}
}