@inproceedings{baumgartner2019phiseg,
  title={{PHiSeg: Capturing uncertainty in medical image segmentation}},
  author={Baumgartner, Christian F and Tezcan, Kerem C and Chaitanya, Krishna and H{\"o}tker, Andreas M and Muehlematter, Urs J and Schawkat, Khoschy and Becker, Anton S and Donati, Olivio and Konukoglu, Ender},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={119--127},
  year={2019},
  organization={Springer}
}
@article{bernard2018deep,
  title={{Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?}},
  author={Bernard, Olivier and Lalande, Alain and Zotti, Clement and Cervenansky, Frederick and Yang, Xin and Heng, Pheng-Ann and Cetin, Irem and Lekadir, Karim and Camara, Oscar and Ballester, Miguel Angel Gonzalez and others},
  journal={IEEE transactions on medical imaging},
  volume={37},
  number={11},
  pages={2514--2525},
  year={2018},
  publisher={ieee}
}
@article{brier1950verification,
  title={{VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY}},
  author={Brier, Glenn W and others},
  journal={Monthly Weather Review},
  volume={78},
  number={1},
  pages={1--3},
  year={1950}
}
@inproceedings{cao2023swin,
  title={{Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation}},
  author={Cao, Hu and Wang, Yueyue and Chen, Joy and Jiang, Dongsheng and Zhang, Xiaopeng and Tian, Qi and Wang, Manning},
  booktitle={European Conference on Computer Vision},
  pages={205--218},
  year={2022},
  organization={Springer}
}
@article{cardoso2022monai,
  title={{MONAI: An open-source framework for deep learning in healthcare}},
  author={Cardoso, M Jorge and Li, Wenqi and Brown, Richard and Ma, Nic and Kerfoot, Eric and Wang, Yiheng and Murrey, Benjamin and Myronenko, Andriy and Zhao, Can and Yang, Dong and others},
  journal={arXiv preprint arXiv:2211.02701},
  year={2022}
}
@article{chen2021transunet,
  title={{TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation}},
  author={Chen, Jieneng and Lu, Yongyi and Yu, Qihang and Luo, Xiangde and Adeli, Ehsan and Wang, Yan and Lu, Le and Yuille, Alan L and Zhou, Yuyin},
  journal={arXiv preprint arXiv:2102.04306},
  year={2021}
}
@inproceedings{clough2020topology,
  title={{A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology}},
  author={Clough, James R and Byrne, Nicholas and Oksuz, Ilkay and Zimmer, Veronika A and Schnabel, Julia A and King, Andrew P},
  booktitle={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={44},
  number={12},
  pages={8766--8778},
  year={2020},
  publisher={IEEE}
}
@inproceedings{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},
  booktitle={International Conference on Learning Representations},
  year={2021}
}
@inproceedings{gal2016dropout,
  title={{Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning}},
  author={Gal, Yarin and Ghahramani, Zoubin},
  booktitle={International Conference on Machine Learning},
  pages={1050--1059},
  year={2016},
  organization={PMLR}
}
@inproceedings{guo2017calibration,
  title={{On Calibration of Modern Neural Networks}},
  author={Guo, Chuan and Pleiss, Geoff and Sun, Yu and Weinberger, Kilian Q},
  booktitle={International Conference on Machine Learning},
  pages={1321--1330},
  year={2017},
  organization={PMLR}
}
@article{hatamizadeh2022unetr,
  title={{UNETR: Transformers for 3D medical image segmentation}},
  author={Hatamizadeh, Ali and Tang, Yucheng and Nath, Vishwesh and Yang, Dong and Myronenko, Andriy and Landman, Bennett and Roth, Holger R and Xu, Daguang},
  journal={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={574--584},
  year={2022}
}
@inproceedings{hu2019topology,
  title={{Topology-Preserving Deep Image Segmentation}},
  author={Hu, Xiaoling and Li, Fuxin and Samaras, Dimitris and Chen, Chao},
  booktitle={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}
@inproceedings{jungo2020assessing,
  title={{Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation}},
  author={Jungo, Alain and Reyes, Mauricio},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={48--56},
  year={2019},
  organization={Springer}
}
@inproceedings{kendall2017uncertainties,
  title={{What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?}},
  author={Kendall, Alex and Gal, Yarin},
  booktitle={Advances in Neural Information Processing Systems},
  volume={30},
  year={2017}
}
@inproceedings{kohl2018probabilistic,
  title={{A Probabilistic U-Net for Segmentation of Ambiguous Images}},
  author={Kohl, Simon and Romera-Paredes, Bernardino and Meyer, Clemens and De Fauw, Jeffrey and Ledsam, Joseph R and Maier-Hein, Klaus and Eslami, SM and Rezende, Danilo Jimenez and Ronneberger, Olaf},
  booktitle={Advances in Neural Information Processing Systems},
  volume={31},
  year={2018}
}
@inproceedings{lakshminarayanan2017simple,
  title={{Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles}},
  author={Lakshminarayanan, Balaji and Pritzel, Alexander and Blundell, Charles},
  booktitle={Advances in Neural Information Processing Systems},
  volume={30},
  year={2017}
}
@inproceedings{landman2015miccai,
  title={Miccai multi-atlas labeling beyond the cranial vault--workshop and challenge},
  author={Landman, Bennett and Xu, Zhoubing and Igelsias, Juan and Styner, Martin and Langerak, Thomas and Klein, Arno},
  booktitle={Proc. MICCAI multi-atlas labeling beyond cranial vault—workshop challenge},
  volume={5},
  pages={12},
  year={2015},
  organization={Munich, Germany}
}
@article{maier2022metrics,
  title={{Metrics reloaded: Recommendations for image analysis validation}},
  author={Maier-Hein, Lena and Reinke, Annika and Godau, Patrick and Tizabi, Minu D and Buettner, Florian and Christodoulou, Evangelia and Glocker, Ben and Isensee, Fabian and Kleesiek, Jens and Kozubek, Michal and others},
  journal={Nature methods},
  volume={21},
  number={2},
  pages={195--212},
  year={2024},
  publisher={Nature Publishing Group US New York}
}
@inproceedings{agarwal2024tcpnet,
  title={{TCPNet: A Novel Tumor Contour Prediction Network Using MRIs}},
  author={Agarwal, Shraddha and Kurmi, Vinod K and Banerjee, Abhirup and Basu, Tanmay},
  booktitle={2024 IEEE 12th International Conference on Healthcare Informatics (ICHI)},
  pages={183--188},
  year={2024},
  organization={IEEE}
}
@inproceedings{dhor2026topo,
  title={{Topo-GraT: Learning to Grow with Causal Graph Transformers (Student Abstract)}},
  author={Dhor, Ashim and Bharadwaj, Smily},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={40},
  number={48},
  pages={41191--41193},
  year={2026}
}
@article{maria2014gudhi,
  title={{The GUDHI library: Simplicial complexes and persistent homology}},
  author={Maria, Cl{\'e}ment and Boissonnat, Jean-Daniel and Glisse, Marc and Yvinec, Mariette},
  journal={International Congress on Mathematical Software},
  pages={167--174},
  year={2014},
  organization={Springer}
}
@article{munkres1957algorithms,
  title={{Algorithms for the Assignment and Transportation Problems}},
  author={Munkres, James},
  journal={Journal of the Society for Industrial and Applied Mathematics},
  volume={5},
  number={1},
  pages={32--38},
  year={1957},
  publisher={SIAM}
}
@article{nikolov2021deep,
  title={Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy},
  author={Nikolov, Stanislav and Blackwell, Sam and Zverovitch, Alexei and Mendes, Ruheena and Livne, Michelle and De Fauw, Jeffrey and Patel, Yojan and Meyer, Clemens and Askham, Harry and Romera-Paredes, Bernardino and others},
  journal={arXiv preprint arXiv:1809.04430},
  year={2018}
}
@inproceedings{ronneberger2015u,
  title={{U-Net: Convolutional Networks for Biomedical Image Segmentation}},
  author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
  booktitle={Medical Image Computing and Computer-Assisted Intervention},
  pages={234--241},
  year={2015},
  organization={Springer}
}
@article{roy2019bayesian,
  title={{Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control}},
  author={Roy, Abhijit Guha and Conjeti, Sailesh and Navab, Nassir and Wachinger, Christian and Alzheimer's Disease Neuroimaging Initiative and others},
  journal={NeuroImage},
  volume={195},
  pages={11--22},
  year={2019},
  publisher={Elsevier}
}
@article{shaker2024unetr++,
  title={{UNETR++: Delving into efficient and accurate 3D medical image segmentation}},
  author={Shaker, Abdelrahman and Maaz, Muhammad and Rasheed, Hanoona and Khan, Salman and Yang, Ming-Hsuan and Khan, Fahad Shahbaz},
  journal={IEEE Transactions on Medical Imaging},
  volume={43},
  number={9},
  pages={3377--3390},
  year={2024},
  publisher={IEEE}
}
@article{shit2021cldice,
  title={{clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation}},
  author={Shit, Suprosanna and Paetzold, Johannes C and Sekuboyina, Anjany and Ezhov, Ivan and Unger, Alexander and Zhylka, Andrey and Pluim, Josien PW and Bauer, Ulrich and Menze, Bjoern H},
  journal={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={16560--16569},
  year={2021}
}
@article{stucki2023topologically,
  title={{Topologically Faithful Image Segmentation via Induced Matching of Persistence Barcodes}},
  author={Stucki, Nico and Paetzold, Johannes C and Shit, Suprosanna and Menze, Bjoern and Bauer, Ulrich},
  journal={International Conference on Machine Learning},
  pages={32698--32727},
  year={2023},
  organization={PMLR}
}
@inproceedings{tang2022self,
  title={{Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis}},
  author={Tang, Yucheng and Yang, Dong and Li, Wenqi and Roth, Holger R and Landman, Bennett and Xu, Daguang and Nath, Vishwesh and Hatamizadeh, Ali},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={20730--20740},
  year={2022}
}
@article{wang2019aleatoric,
  title={{Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks}},
  author={Wang, Guotai and Li, Wenqi and Aertsen, Michael and Deprest, Jan and Ourselin, S{\'e}bastien and Vercauteren, Tom},
  journal={Neurocomputing},
  volume={338},
  pages={34--45},
  year={2019},
  publisher={Elsevier}
}
@article{zhou2023nnformer,
  title={{nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer}},
  author={Zhou, Hong-Yu and Guo, Jiansen and Zhang, Yinghao and Han, Xiaoguang and Yu, Lequan and Wang, Liansheng and Yu, Yizhou},
  journal={IEEE transactions on image processing},
  volume={32},
  pages={4036--4045},
  year={2023},
  publisher={IEEE}
}