@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--MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18},
  pages={234--241},
  year={2015},
  organization={Springer}
}

@inproceedings{milletari2016v,
  title={V-net: Fully convolutional neural networks for volumetric medical image segmentation},
  author={Milletari, Fausto and Navab, Nassir and Ahmadi, Seyed-Ahmad},
  booktitle={2016 fourth international conference on 3D vision (3DV)},
  pages={565--571},
  year={2016},
  organization={Ieee}
}

@article{gao2023bayeseg,
  title={BayeSeg: Bayesian modeling for medical image segmentation with interpretable generalizability},
  author={Gao, Shangqi and Zhou, Hangqi and Gao, Yibo and Zhuang, Xiahai},
  journal={Medical Image Analysis},
  volume={89},
  pages={102889},
  year={2023},
  publisher={Elsevier}
}

@inproceedings{gao2022joint,
  title={Joint modeling of image and label statistics for enhancing model generalizability of medical image segmentation},
  author={Gao, Shangqi and Zhou, Hangqi and Gao, Yibo and Zhuang, Xiahai},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={360--369},
  year={2022},
  organization={Springer}
}

@inproceedings{chen2019synergistic,
  title={Synergistic image and feature adaptation: Towards cross-modality domain adaptation for medical image segmentation},
  author={Chen, Cheng and Dou, Qi and Chen, Hao and Qin, Jing and Heng, Pheng-Ann},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={33},
  number={01},
  pages={865--872},
  year={2019}
}

@article{chen2020unsupervised,
  title={Unsupervised bidirectional cross-modality adaptation via deeply synergistic image and feature alignment for medical image segmentation},
  author={Chen, Cheng and Dou, Qi and Chen, Hao and Qin, Jing and Heng, Pheng Ann},
  journal={IEEE transactions on medical imaging},
  volume={39},
  number={7},
  pages={2494--2505},
  year={2020},
  publisher={IEEE}
}

@inproceedings{peng2022unsupervised,
  title={Unsupervised domain adaptation for cross-modality retinal vessel segmentation via disentangling representation style transfer and collaborative consistency learning},
  author={Peng, Linkai and Lin, Li and Cheng, Pujin and Huang, Ziqi and Tang, Xiaoying},
  booktitle={2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)},
  pages={1--5},
  year={2022},
  organization={IEEE}
}

@article{gu2023cddsa,
  title={CDDSA: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation},
  author={Gu, Ran and Wang, Guotai and Lu, Jiangshan and Zhang, Jingyang and Lei, Wenhui and Chen, Yinan and Liao, Wenjun and Zhang, Shichuan and Li, Kang and Metaxas, Dimitris N and others},
  journal={Medical Image Analysis},
  volume={89},
  pages={102904},
  year={2023},
  publisher={Elsevier}
}

@article{castro2020causality,
  title={Causality matters in medical imaging},
  author={Castro, Daniel C and Walker, Ian and Glocker, Ben},
  journal={Nature Communications},
  volume={11},
  number={1},
  pages={3673},
  year={2020},
  publisher={Nature Publishing Group UK London}
}

@inproceedings{yang2020fda,
  title={Fda: Fourier domain adaptation for semantic segmentation},
  author={Yang, Yanchao and Soatto, Stefano},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={4085--4095},
  year={2020}
}

@inproceedings{xu2021fourier,
  title={A fourier-based framework for domain generalization},
  author={Xu, Qinwei and Zhang, Ruipeng and Zhang, Ya and Wang, Yanfeng and Tian, Qi},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={14383--14392},
  year={2021}
}

@inproceedings{li2023frequency,
  title={Frequency-mixed single-source domain generalization for medical image segmentation},
  author={Li, Heng and Li, Haojin and Zhao, Wei and Fu, Huazhu and Su, Xiuyun and Hu, Yan and Liu, Jiang},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={127--136},
  year={2023},
  organization={Springer}
}

@inproceedings{zhao2024morestyle,
  title={Morestyle: relax low-frequency constraint of fourier-based image reconstruction in generalizable medical image segmentation},
  author={Zhao, Haoyu and Dong, Wenhui and Yu, Rui and Zhao, Zhou and Du, Bo and Xu, Yongchao},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={434--444},
  year={2024},
  organization={Springer}
}

@inproceedings{zhou2021mixstyle,
  title={Domain Generalization with MixStyle},
  author={Zhou, Kaiyang and Yang, Yongxin and Qiao, Yu and Xiang, Tao},
  booktitle={International Conference on Learning Representations},
  year={2021}
}

@inproceedings{chen2023treasure,
  title={Treasure in distribution: a domain randomization based multi-source domain generalization for 2d medical image segmentation},
  author={Chen, Ziyang and Pan, Yongsheng and Ye, Yiwen and Cui, Hengfei and Xia, Yong},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={89--99},
  year={2023},
  organization={Springer}
}

@inproceedings{chen2025constyx,
  title={ConStyX: Content Style Augmentation for Generalizable Medical Image Segmentation},
  author={Chen, Xi and Shen, Zhiqiang and Cao, Peng and Yang, Jinzhu and Zaiane, Osmar R},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={100--110},
  year={2025},
  organization={Springer}
}

@inproceedings{xu2021robust,
  title={Robust and Generalizable Visual Representation Learning via Random Convolutions},
  author={Zhenlin Xu and Deyi Liu and Junlin Yang and Colin Raffel and Marc Niethammer},
  booktitle={International Conference on Learning Representations},
  year={2021}
}

@inproceedings{choi2023progressive,
  title={Progressive random convolutions for single domain generalization},
  author={Choi, Seokeon and Das, Debasmit and Choi, Sungha and Yang, Seunghan and Park, Hyunsin and Yun, Sungrack},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={10312--10322},
  year={2023}
}

@article{ouyang2022causality,
  title={Causality-inspired single-source domain generalization for medical image segmentation},
  author={Ouyang, Cheng and Chen, Chen and Li, Surui and Li, Zeju and Qin, Chen and Bai, Wenjia and Rueckert, Daniel},
  journal={IEEE Transactions on Medical Imaging},
  volume={42},
  number={4},
  pages={1095--1106},
  year={2022},
  publisher={IEEE}
}

@inproceedings{su2023rethinking,
  title={Rethinking data augmentation for single-source domain generalization in medical image segmentation},
  author={Su, Zixian and Yao, Kai and Yang, Xi and Huang, Kaizhu and Wang, Qiufeng and Sun, Jie},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={37},
  number={2},
  pages={2366--2374},
  year={2023}
}

# MS-CMR
@article{zhuang2018multivariate,
  title={Multivariate mixture model for myocardial segmentation combining multi-source images},
  author={Zhuang, Xiahai},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={41},
  number={12},
  pages={2933--2946},
  year={2018},
  publisher={IEEE}
}

# ACDC
@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}
}

# MMWHS
@article{zhuang2019evaluation,
  title={Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge},
  author={Zhuang, Xiahai and Li, Lei and Payer, Christian and {\v{S}}tern, Darko and Urschler, Martin and Heinrich, Mattias P and Oster, Julien and Wang, Chunliang and Smedby, {\"O}rjan and Bian, Cheng and others},
  journal={Medical image analysis},
  volume={58},
  pages={101537},
  year={2019},
  publisher={Elsevier}
}

# pytorch
@article{paszke2019pytorch,
  title={Pytorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

# adam
@inproceedings{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  booktitle={International Conference on Learning Representations},
  year={2015}
}

# svd
@article{klema1980singular,
  title={The singular value decomposition: Its computation and some applications},
  author={Klema, Virginia and Laub, Alan},
  journal={IEEE Transactions on automatic control},
  volume={25},
  number={2},
  pages={164--176},
  year={1980},
  publisher={IEEE}
}

@incollection{wall2003singular,
  title={Singular value decomposition and principal component analysis},
  author={Wall, Michael E and Rechtsteiner, Andreas and Rocha, Luis M},
  booktitle={A practical approach to microarray data analysis},
  pages={91--109},
  year={2003},
  publisher={Springer}
}

# survey
@article{zhou2022domain,
  title={Domain generalization: A survey},
  author={Zhou, Kaiyang and Liu, Ziwei and Qiao, Yu and Xiang, Tao and Loy, Chen Change},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={45},
  number={4},
  pages={4396--4415},
  year={2022},
  publisher={IEEE}
}

@article{guan2021domain,
  title={Domain adaptation for medical image analysis: a survey},
  author={Guan, Hao and Liu, Mingxia},
  journal={IEEE Transactions on Biomedical Engineering},
  volume={69},
  number={3},
  pages={1173--1185},
  year={2021},
  publisher={IEEE}
}

# t-SNE
@article{van2008visualizing,
  title={Visualizing data using t-SNE.},
  author={Van der Maaten, Laurens and Hinton, Geoffrey},
  journal={Journal of machine learning research},
  volume={9},
  number={11},
  year={2008}
}

# PCA
@article{abdi2010principal,
  title={Principal component analysis},
  author={Abdi, Herv{\'e} and Williams, Lynne J},
  journal={Wiley interdisciplinary reviews: computational statistics},
  volume={2},
  number={4},
  pages={433--459},
  year={2010},
  publisher={Wiley Online Library}
}

@article{hotelling1933analysis,
  title={Analysis of a complex of statistical variables into principal components.},
  author={Hotelling, Harold},
  journal={Journal of educational psychology},
  volume={24},
  number={6},
  pages={417},
  year={1933},
  publisher={Warwick \& York}
}

@article{kim2005iterative,
  title={Iterative kernel principal component analysis for image modeling},
  author={Kim, Kwang In and Franz, Matthias O and Scholkopf, Bernhard},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={27},
  number={9},
  pages={1351--1366},
  year={2005},
  publisher={IEEE}
}

@article{candes2011robust,
  title={Robust principal component analysis?},
  author={Cand{\`e}s, Emmanuel J and Li, Xiaodong and Ma, Yi and Wright, John},
  journal={Journal of the ACM (JACM)},
  volume={58},
  number={3},
  pages={1--37},
  year={2011},
  publisher={ACM New York, NY, USA}
}

@article{pei2021disentangle,
  title={Disentangle domain features for cross-modality cardiac image segmentation},
  author={Pei, Chenhao and Wu, Fuping and Huang, Liqin and Zhuang, Xiahai},
  journal={Medical Image Analysis},
  volume={71},
  pages={102078},
  year={2021},
  publisher={Elsevier}
}


@article{andrews2003singular,
  title={Singular value decomposition (SVD) image coding},
  author={Andrews, H and Patterson, CLIII},
  journal={IEEE transactions on Communications},
  volume={24},
  number={4},
  pages={425--432},
  year={2003},
  publisher={IEEE}
}

@article{ranade2007variation,
  title={A variation on SVD based image compression},
  author={Ranade, Abhiram and Mahabalarao, Srikanth S and Kale, Satyen},
  journal={Image and Vision computing},
  volume={25},
  number={6},
  pages={771--777},
  year={2007},
  publisher={Elsevier}
}

@article{zhu2014fast,
  title={Fast single image super-resolution via self-example learning and sparse representation},
  author={Zhu, Zhiliang and Guo, Fangda and Yu, Hai and Chen, Chen},
  journal={IEEE Transactions on Multimedia},
  volume={16},
  number={8},
  pages={2178--2190},
  year={2014},
  publisher={IEEE}
}

@article{guo2015efficient,
  title={An efficient SVD-based method for image denoising},
  author={Guo, Qiang and Zhang, Caiming and Zhang, Yunfeng and Liu, Hui},
  journal={IEEE transactions on Circuits and Systems for Video Technology},
  volume={26},
  number={5},
  pages={868--880},
  year={2015},
  publisher={IEEE}
}

@article{gao2020rank,
  title={Rank-one network: An effective framework for image restoration},
  author={Gao, Shangqi and Zhuang, Xiahai},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={44},
  number={6},
  pages={3224--3238},
  year={2020},
  publisher={IEEE}
}


# REFUGE
@article{orlando2020refuge,
  title={Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs},
  author={Orlando, Jos{\'e} Ignacio and Fu, Huazhu and Breda, Jo{\~a}o Barbosa and Van Keer, Karel and Bathula, Deepti R and Diaz-Pinto, Andr{\'e}s and Fang, Ruogu and Heng, Pheng-Ann and Kim, Jeyoung and Lee, JoonHo and others},
  journal={Medical image analysis},
  volume={59},
  pages={101570},
  year={2020},
  publisher={Elsevier}
}

# ORIGA
@inproceedings{zhang2010origa,
  title={Origa-light: An online retinal fundus image database for glaucoma analysis and research},
  author={Zhang, Zhuo and Yin, Feng Shou and Liu, Jiang and Wong, Wing Kee and Tan, Ngan Meng and Lee, Beng Hai and Cheng, Jun and Wong, Tien Yin},
  booktitle={2010 Annual international conference of the IEEE engineering in medicine and biology},
  pages={3065--3068},
  year={2010},
  organization={IEEE}
}

# Drishti-gs
@inproceedings{sivaswamy2014drishti,
  title={Drishti-gs: Retinal image dataset for optic nerve head (onh) segmentation},
  author={Sivaswamy, Jayanthi and Krishnadas, SR and Joshi, Gopal Datt and Jain, Madhulika and Tabish, A Ujjwaft Syed},
  booktitle={2014 IEEE 11th international symposium on biomedical imaging (ISBI)},
  pages={53--56},
  year={2014},
  organization={IEEE}
}

# RIGA
@inproceedings{almazroa2018retinal,
  title={Retinal fundus images for glaucoma analysis: the RIGA dataset},
  author={Almazroa, Ahmed and Alodhayb, Sami and Osman, Essameldin and Ramadan, Eslam and Hummadi, Mohammed and Dlaim, Mohammed and Alkatee, Muhannad and Raahemifar, Kaamran and Lakshminarayanan, Vasudevan},
  booktitle={Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications},
  volume={10579},
  pages={55--62},
  year={2018},
  organization={SPIE}
}
