%==============================================================================================================

@article{denseformer1,
author = {Ding Rizhi and Lu Hui and Liu M.},
title = { DenseFormer-MoE: A Dense Transformer Foundation Model with Mixture of Experts for Multi-Task Brain Image Analysis},
journal = {IEEE TIM},
year = 2025
}
#---------------------------------------------------------------------------------
@Inproceedings{patcher2,
  author       = {Yanglan Ou and Ye Yuan and Xiaolei Huang and Stephen T. C. Wong and John Volpi and James Z. Wang  and Kelvin Wong },
  title        = { Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation},
  booktitle    = {in MICCAI},
  year         = {2022},
  pages        = {475--484},
}


#-------------------------------------------------------------------------------



@article{uncertainty-guided-transformer3,
author = {   Chen Zan and Peng Chenxu and Guo W and Xie L and Wang S  },
title = {   Uncertainty-guided transformer for brain tumor segmentation.},
journal = { Med Biol Eng Comput)   },
year = 2023
}





#-------------------------------------------------------------------------------

@inproceedings{UNETR4,
author = {   Ali Hatamizadeh and Yucheng Tang and Vishwesh Nath and Dong Yang and Andriy Myronenko and Bennett Landman and Holger Roth and Daguang Xu  },
title = {   UNETR: Transformers for 3D Medical Image Segmentation   },
booktitle = { in WACV  },
year = 2022
}


#-------------------------------------------------------------------------------

@inproceedings{   TransResNet5,
author = {  Muhammad Hamza Sharif and Dmitry Demidov and Asif Hanif and Mohammad Yaqub and Min Xu  },
title = {   TransResNet: Integrating the Strengths of ViTs and CNNs for High Resolution Medical Image Segmentation via Feature Grafting   },
booktitle = { in BMVC   },
year = 2022
}



#-------------------------------------------------------------------------------
@inproceedings{  FFR-Unet6,
author = {    Weixin Xu. },
title = {   FFR-UNet: Feature Filter-Refinement UNet for Medical Image Segmentation   },
booktitle = {  in BMVC },
year = 2024
}


#-------------------------------------------------------------------------------

@inproceedings{  Unet7,
author = {  Olaf Ronneberger and  Philipp Fischer and Thomas Brox.   },
title = {     U-Net: Convolutional Networks for Biomedical Image Segmentation },
booktitle = {  in MICCAI  },
year = 2015
}


#-------------------------------------------------------------------------------

@inproceedings{  ViT8,
author = {   Alexey Dosovitskiy and Lucas Beyer and Alexander Kolesnikov and  Dirk Weissenborn and  Xiaohua Zhai and Thomas Unterthiner and Mostafa Dehghani and Matthias Minderer and Georg Heigold and Sylvain Gelly and  Jakob Uszkoreit and   Neil Houlsby.  },
title = {   An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale   },
inproceedings = {  in ICLR  },
year = 2020
}


#-------------------------------------------------------------------------------

@article{ PVT9,
author = {  Wenhai Wang and Enze Xie and Xiang Li and Deng-Ping Fan and Kaitao Song and Ding Liang and Tong Lu and Ping Luo and Ling Shao.   },
title = {   Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions   },
journal = {  ICCV  },
year = 2021
}



#-------------------------------------------------------------------------------

@article{  TransUnet10,
author = {   Jieneng Chen and Yongyi Lu and Qihang Yu and Xiangde Luo and Ehsan Adeli and Yan Wang and Le Lu and Alan L Yuille and Yuyin Zhou.   },
title = {  TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation    },
journal = {arXiv},
year = 2021
}




#-------------------------------------------------------------------------------
@article{swin-unet11,
author = {  Hu Cao and Yueyue Wang and Joy Chen Qi Tian and Manning Wang   },
title = {   Swin-Unet: Unet-Like Pure Transformer for Medical Image Segmentation   },
journal = { in ECCV  },
year = 2022
}


#-------------------------------------------------------------------------------

@article{  MedFuseNet12,
author = {   Ruiyuan Chen and Saiqi He and Hongsheng Lu and Zhaohui Yang  },
title = { MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation },
journal = {Sci Rep},
year = 2025
}


#-------------------------------------------------------------------------------


@article{  DTASUnet13,
author = {   Bo Ma and Qian Sun and Ze Ma and Baosheng Li and Qiang Cao and Yungang Wang and Gang Yu.  },
title = { DTASUnet: a local and global dual transformer with the attention supervision U-network for brain tumor segmentation },
journal = {Sci Rep},
year = 2024
}



#-------------------------------------------------------------------------------
@article{  GLFNet14,
author = {   Shiyao Sun and Chong Fu and Sen Xu and Yingyou Wen and Tao Ma. },
title = { GLFNet: Global-local fusion network for the segmentation in ultrasound images },
journal = {Comput Biol Med},
year = 2024
}



#-------------------------------------------------------------------------------
@article{  MoE15,
author = {  Dmitry Lepikhin and HyoukJoong Lee and Yuanzhong Xu and Dehao Chen and Orhan Firat and Yanping Huang and Maxim Krikun and Noam Shazeer and Zhifeng Chen. },
title = { Gshard: Scaling giant models with conditional computation and automatic sharding },
journal = {in ICLR},
year = 2020
}



#-------------------------------------------------------------------------------

@article{  Sparse_MoE16,
author = { Carlos Riquelme and Joan Puigcerver and Basil Mustafa and Maxim Neumann and Rodolphe Jenatton and André Susano Pinto and Daniel Keysers and Neil Houlsby },
title = { Scaling Vision with Sparse Mixture of Experts},
journal = {in NeurIPS},
year = 2021
}






#-------------------------------------------------------------------------------

@article{  M3ViT17,
author = {Hanxue Liang and Zhiwen Fan and Rishov Sarkar and Ziyu Jiang and Tianlong Chen and Kai Zou and Yu Cheng and Cong Hao and Zhangyang Wang. },
title = { M$^3$ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design},
journal = {in NeurIPS},
year = 2022
}
 

#-------------------------------------------------------------------------------
@article{  FuseMoE18,
author = {Xing Han and Huy Nguyen and Carl Harris and Nhat Ho and Suchi Saria. },
title = { FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion},
journal = {in NeurIPS},
year = 2024
}
 

#-------------------------------------------------------------------------------
@article{  Soft-MoE19,
author = {Joan Puigcerver and Carlos Riquelme and Basil Mustafa and Neil Houlsby. },
title = { From Sparse to Soft Mixtures of Experts},
journal = {ICLR},
year = 2024
}
 



#-------------------------------------------------------------------------------
@article{  Swin-smt20,
author = {Szymon Płotka and Maciej Chrabaszcz and Przemyslaw Biecek. },
title = { Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation},
journal = {in MICCAI},
year = 2024
}
 


#-------------------------------------------------------------------------------

@article{  DS-TransUnet21,
author = {Szymon Płotka and Maciej Chrabaszcz and Przemyslaw Biecek. },
title = { DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation},
journal = {IEEE TIM},
volume= {abs/2106.06716},
year = 2022
}
 


#-------------------------------------------------------------------------------
@article{  swinUnetr2_22,
author = { Yufan He and Vishwesh Nath and Dong Yang and Yucheng Tang and Andriy Myronenko and Daguang Xu. },
title = {SwinUNETR-V2: Stronger Swin Transformers with Stagewise Convolutions for 3D Medical Image Segmentation},
journal = {in MICCAI},
year = 2023
}
 





#-------------------------------------------------------------------------------

@article{kvasir23,
author = {Debesh Jha and Pia H Smedsrud and Michael A Riegler and Pål Halvorsen and Thomas de Lange and
 Dag Johansen and Håvard D Johansen. },
title = {Kvasir-seg: A segmented polyp dataset},
journal = {in ICMM},
pages = {451–-462}, 
year = 2020
}







#-------------------------------------------------------------------------------
@article{clinic_DB24,
author = {Jorge Bernal and FJavier Sánchez  and Gloria Fernández-Esparrach and Debora Gil and Cristina Ro
dríguez and Fernando Vilariño. },
title = {Wm-dovamaps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians},
journal = {Computerized medical imaging and graphics},
pages = {99–111}, 
year = 2015
}






#-------------------------------------------------------------------------------
@article{colonDB-25,
author = {Nima Tajbakhsh and Suryakanth R Gurudu and  Jianming Liang.},
title = {Automated polyp detection in colonoscopy videos using shape and context information},
journal = {IEEE TMI},
pages = {630–644}, 
year = 2015
}


#-------------------------------------------------------------------------------

@article{ETIS-26,
author = {Juan Silva and Aymeric Histace and Olivier Romain and Xavier Dray and  Bertrand Granado. },
title = {Toward embedded detection of polyps in wce images for early diagnosis of colorectal cancer},
journal = {International journal of computer assisted radiology and surgery},
pages = {283--293}, 
year = 2014
}


#-------------------------------------------------------------------------------
@article{poly_data_setting1-27,
author = {Jun Wei and Yiwen Hu and Ruimao Zhang and Zhen Li and S Kevin Zhou and and Shuguang Cui.},
title = {Shallow attention network for polyp segmentation},
journal = {in MICCAI},
pages = {699--708}, 
year = 2021
}


#-------------------------------------------------------------------------------
@article{data_setting2-28,
author = {Yundong Zhang and Huiye Liu and Qiang Hu. },
title = {Transfuse: Fusing transformers and cnns for medical image segmentation},
journal = {in MICCAI},
pages = {14--24}, 
year = 2021
}




#-------------------------------------------------------------------------------
@article{ISIC-29,
author = {David Gutman and Noel CFCodella and Emre Celebi and Brian Helba and Michael Marchetti and Nabin
 Mishra and Allan Halpern.},
title = {Skin lesion analysis toward melanoma detection: A challenge at the international symposium on biomedical imaging (isbi) 2016, hosted by the international skin imaging collaboration (isic)},
journal = { arXiv preprint arXiv},
year = 2016
}

#-------------------------------------------------------------------------------

@article{ph2-30,
author = {Teresa Mendonça and Pedro M Ferreira and Jorge S Marques and André RS Marcal and Jorge
 Rozeira. },
title = { Ph 2-a dermoscopic image database for research and benchmarking},
journal = {2013 35th annual international conference of the IEEE EMBC},
year = 2013
}





#-------------------------------------------------------------------------------




#-------------------------------------------------------------------------------

@article{polyp-pvt-32,
  author       = {Bo Dong and Wenhai Wang and Deng-Ping Fan and Jinpeng Li and Huazhu Fu and Ling Shao},
  title        = {Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers},
  journal      = {CAAI Artificial Intelligence Research},
  year         = {2023},

}




#-------------------------------------------------------------------------------
@article{DCRNet33,
  author       = {Zijin Yin and Kongming Liang and Zhanyu Ma and and Jun Guo},
  title        = { Duplex contextual relation network for polyp segmentation},
  journal      = {In 2022 IEEE 19th ISBI},
  year         = {2022},

}






#-------------------------------------------------------------------------------

@article{VM-Unet34,
  author       = {J, Ruan and S, Xiang.},
  title        = { Vm-unet: Vision mamba unet for medical image segmentation},
  journal      = {arXiv preprint arXiv},
  year         = {2024},

}



@inproceedings{pranet35,
  author       = {Deng-Ping Fan and Ge-Peng Ji and Tao Zhou and Geng Chen.},
  title        = { Pranet: Parallel reverse attention network for polyp segmentation},
  booktitle      = {in MICCAI},
  year         = {2020},

}






@article{SANet36,
  author       = {Jun Wei and Yiwen Hu and Ruimao Zhang},
  title        = {  Shallow attention network for polyp segmentation},
  journal      = {in MICCAI},
  year         = {2021},

}




#-------------------------------------------------------------------------------



@article{CANet38,
  author       = {Ran Gu and Guotai Wang and Tao Song and Rui Huang},
  title        = {   Ca-net: Comprehensive attention convolutional neural networks for explainable medical image segmentation.},
  journal      = { IEEE TMI},
  year         = {2021},

}





@article{attention-Unet39,
  author       = {Ozan Oktay and Jo Schlemper and Loic Le Folgoc and et},
  title        = {  Attention u-net: Learning where to look for the pancreas.},
  journal      = { arXiv preprint arXiv:},
  year         = {2018},

}




@article{CE-Net40,
  author       = {Zaiwang Gu and Jun Cheng and HuazhuFu and KangZhou},
  title        = {  Ce-net: Context encoder network for 2d medical image segmentation.},
  journal      = { IEEE TMI},
  year         = {2019},

}



#--------------NEWLY ADDED REFERENCE---------------------------------------------------------------

@article{Yang2025SegDINOV3,
  title={SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3},
  author={Sicheng Yang and Hongqiu Wang and Zhaohu Xing and Sixiang Chen and Lei Zhu},
  journal={ArXiv},
  year={2025},
  volume={abs/2509.00833},
  url={https://api.semanticscholar.org/CorpusID:281081098}
}

@article{Gao2025DinoUE,
  title={Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation},
  author={Yifan Gao and Haoyue Li and Feng Yuan and Xiaosong Wang and Xin Gao},
  journal={ArXiv},
  year={2025},
  volume={abs/2508.20909},
  url={https://api.semanticscholar.org/CorpusID:280949513}
}

@misc{siméoni2025dinov3,
      title={DINOv3}, 
      author={Oriane Siméoni and Huy V. Vo and Maximilian Seitzer and Federico Baldassarre and Maxime Oquab and Cijo Jose and Vasil Khalidov and Marc Szafraniec and Seungeun Yi and Michaël Ramamonjisoa and Francisco Massa and Daniel Haziza and Luca Wehrstedt and Jianyuan Wang and Timothée Darcet and Théo Moutakanni and Leonel Sentana and Claire Roberts and Andrea Vedaldi and Jamie Tolan and John Brandt and Camille Couprie and Julien Mairal and Hervé Jégou and Patrick Labatut and Piotr Bojanowski},
      year={2025},
      eprint={2508.10104},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2508.10104}, 
}



@misc{wang2025dinov3,
      title={DINOv3 with Test-Time Training for Medical Image Registration}, 
      author={Shansong Wang and Mojtaba Safari and Mingzhe Hu and Qiang Li and Chih-Wei Chang and Richard LJ Qiu and Xiaofeng Yang},
      year={2025},
      eprint={2508.14809},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2508.14809}, 
}



% --- newly added dataset reference ---
@article{staal2004ridge,
  title={Ridge-based vessel segmentation in color images of the retina},
  author={Staal, Joes and Abràmoff, Michael D and Niemeijer, Meindert and Viergever, Max A and van Ginneken, Bram},
  journal={IEEE Transactions on Medical Imaging},
  volume={23},
  number={4},
  pages={501--509},
  year={2004}
}
@article{hoover2000locating,
  title={Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response},
  author={Hoover, Adam and Kouznetsova, Valentina and Goldbaum, Michael},
  journal={IEEE Transactions on Medical Imaging},
  volume={19},
  number={3},
  pages={203--210},
  year={2000}
}
@article{chen2021transunet,
  title={TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation},
  author={Chen, Jieneng and others},
  journal={arXiv preprint arXiv:2102.04306},
  year={2021}
}
@article{fang2022refuge2,
  title={REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screening},
  author={Fang, Haoran and others},
  journal={arXiv preprint arXiv:2202.08994},
  year={2022}
}
@inproceedings{kumar2019monuseg,
  title={A Multi-Organ Nucleus Segmentation Challenge},
  author={Kumar, Neeraj and others},
  booktitle={IEEE Transactions on Medical Imaging},
  volume={39},
  number={5},
  pages={1380--1391},
  year={2020}
}
@article{mahbod2021cryonuseg,
  title={CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H\&E-stained histological images},
  author={Mahbod, Amirreza and others},
  journal={Computers in Biology and Medicine},
  volume={132},
  pages={104349},
  year={2021}
}







@article{Wu2023ScaleawareDR,
  title={Scale-aware dense residual retinal vessel segmentation network with multi-output weighted loss},
  author={Jiwei, Wu and Shi-bin, Xuan},
  journal={BMC Medical Imaging},
  year={2023},
  volume={23},
  url={https://api.semanticscholar.org/CorpusID:260291524}
}


@article{2015U,
  title={U-Net: Convolutional Networks for Biomedical Image Segmentation},
  author={ Ronneberger, Olaf  and  Fischer, Philipp  and  Brox, Thomas },
  journal={Springer, Cham},
  year={2015},
}

@article{2018UNet,
  title={UNet++: A Nested U-Net Architecture for Medical Image Segmentation},
  author={ Zhou, Zongwei  and  Siddiquee, Md Mahfuzur Rahman  and  Tajbakhsh, Nima  and  Liang, Jianming },
  year={2018},
}

@article{2022UNETR,
  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={2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
  pages={1748-1758},
  year={2022},
}

@misc{hatamizadeh2022swinunetrswintransformers,
      title={Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images}, 
      author={Ali Hatamizadeh and Vishwesh Nath and Yucheng Tang and Dong Yang and Holger Roth and Daguang Xu},
      year={2022},
      eprint={2201.01266},
      archivePrefix={arXiv},
      primaryClass={eess.IV},
      url={https://arxiv.org/abs/2201.01266}, 
}

@article{2021TransBTS,
  title={TransBTS: Multimodal Brain Tumor Segmentation Using Transformer},
  author={ Wang, Wenxuan  and  Chen, Chen  and  Ding, Meng  and  Li, Jiangyun  and  Zha, Sen },
  year={2021},
}

@article{0MedFuseNet,
  title={MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation},
  author={ Chen, Ruiyuan  and  He, Saiqi  and  Xie, Junjie  and  Wang, Tao  and  Xu, Yingying  and  Fang, Jiangxiong  and  Zhao, Xiaoming  and  Zhang, Shiqing  and  Wang, Guoyu  and  Lu, Hongsheng },
  journal={Scientific Reports},
}

@misc{chen2021transunettransformersmakestrong,
      title={TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation}, 
      author={Jieneng Chen and Yongyi Lu and Qihang Yu and Xiangde Luo and Ehsan Adeli and Yan Wang and Le Lu and Alan L. Yuille and Yuyin Zhou},
      year={2021},
      eprint={2102.04306},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2102.04306}, 
}

@article{2024ViM,
  title={ViM-UNet: Vision Mamba for Biomedical Segmentation},
  author={ Archit, Anwai  and  Pape, Constantin },
  year={2024},
}


@article{2021Cellpose,
  title={Cellpose: a generalist algorithm for cellular segmentation},
  author={ Stringer, Carsen  and  Wang, Tim  and  Michaelos, Michalis  and  Pachitariu, Marius },
  journal={Springer Science and Business Media LLC},
  number={1},
  year={2021},
}

@article{lu2023smile,
  title = {{{SMILE}}: {{Cost-sensitive}} Multi-Task Learning for Nuclear Segmentation and Classification with Imbalanced Annotations},
  author = {Lu, Cheng and Feng, Zhe and Liu, Zhihua and Cheng, Jun and Han, Chu and Li, Li and Hou, Feng and Liang, Cheng and Wang, Hao and Liu, Zhenbing and Pan, Xipeng and Chen, Xiang and Lan, Rushi},
  year = {2023},
  journal = {Medical Image Analysis},
  volume = {88},
  pages = {102867},
  issn = {1361-8415},
  doi = {10.1016/j.media.2023.102867},
}


@article{2021HDNet,
  title={HDNet: Hybrid Distance Network for Semantic Segmentation},
  author={ Li, Chunpeng  and  Kang, Xuejing  and  Zhu, Lei  and  Ye, Lizhu  and  Ming, Anlong },
  journal={Neurocomputing},
  volume={447},
  number={4},
  year={2021},
}

@article{2022DenseRes,
  title={DenseRes-Unet: Segmentation of overlapped/clustered nuclei from multi organ histopathology images},
  author={ Kiran, Iqra  and  Raza, Basit  and  Ijaz, Areesha  and  Khan, Muazzam A. },
  journal={Computers in Biology and Medicine},
  volume={143},
  pages={105267-},
  year={2022},
}

@article{2024Cup,
  title={Cup and Disc Segmentation Algorithm Based on Improved Swin-UNet Model},
  author={ Peng, Hao  and  Wang, Ge },
  journal={2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)},
  pages={485-488},
  year={2024},
}

@article{2018REFUGE,
  title={REFUGE CHALLENGE 2018-Task 2:Deep Optic Disc and Cup Segmentation in Fundus Images Using U-Net and Multi-scale Feature Matching Networks},
  author={ Singh, Vivek Kumar  and  Rashwan, Hatem A.  and  Saleh, Adel  and  Akram, Farhan  and  Sarker, Md Mostafa Kamal  and  Pandey, Nidhi  and  Abdulwahab, Saddam },
  year={2018},
}

@article{2020Optic,
  title={Optic Disc, Cup and Fovea Detection from Retinal Images Using U-Net++ with EfficientNet Encoder},
  author={ Kamble, Ravi  and  Samanta, Pranab  and  Singhal, Nitin },
  year={2020},
}

@article{2021MedFuseNet,
  title={MedFuseNet:Anattention-based multimodal deep learning model for visual question answering in the medical domain},
  author={ Sharma, Dhruv  and  Purushotham, Sanjay  and  Reddy, Chandan K. },
  journal={Scientific Reports},
  volume={11},
  number={1},
  pages={1-18},
  year={2021},
}



@InProceedings{nucleiSeg,
  title = 	 {Nuclei Segmentation in Histopathological Images with  Enhanced U-Net3+},
  author =       {Swain, Bishal Ranjan and Cheoi, Kyung Joo and Ko, Jaepil},
  booktitle = 	 {Proceedings of The 7nd International Conference on Medical Imaging with Deep Learning},
  pages = 	 {1513--1530},
  year = 	 {2024},
  volume = 	 {250},
  
}




@article{DUNet,
  title = 	 {DUNet: A deformable network for retinal vessel segmentation.},
  author =       {Jin Qiangguo and Zhaopeng Meng and Tuan D. Pham and Qi Chen and Leyi Wei and and Ran Su.},
  journal = 	 {Knowledge-Based Systems},
  pages = 	 {149-162},
  year = 	 {2019},
  volume = 	 {178},
  
}


@article{tcddu,
  title = 	 {TCDDU-Net: combining transformer and convolutional dual-path decoding U-Net for retinal vessel segmentation.},
  author =       {Lv Nianzhu and Xu Li. and Chen.},
  journal = 	 {Sci Rep 14},
  pages = 	 {149-162},
  year = 	 {2024},
  volume = 	 {25978},
  
}

@InProceedings{MoE,
  title = 	 {Tutel: Adaptive mixture-of-experts at scale.},
  author =       {Hwang, Changho and Wei Cui and Yifan Xiong and Ziyue Yang and Ze Liu and Han Hu and Zilong Wang.},
  booktitle = 	 {Proceedings of Machine Learning and Systems 5},
  pages = 	 {269-287},
  year = 	 {2023},
  
}





@misc{segdinov3,
      title = 	 {Segdino: An efficient design for medical and natural image segmentation with dino-v3.},
      author =       {Yang, Sicheng and Hongqiu, Wang and Zhaohu Xing, Sixiang Chen, and Lei Zhu.},
      year={2025},
      eprint={2509.00833},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2509.00833}, 
}



@inproceedings{paan,
title={{PAAN}: Pyramid Attention Augmented Network for polyp segmentation},
author={Sida Yi and Yuesheng Zhu and Guibo Luo},
booktitle={Medical Imaging with Deep Learning},
year={2024},
url={https://openreview.net/forum?id=sz9baxSuxF}
}



@InProceedings{QueryNet,
        author = { Chai, Jiaxing and Luo, Zhiming and Gao, Jianzhe and Dai, Licun and Lai, Yingxin and Li, Shaozi},
        title = { { QueryNet: A Unified Framework for Accurate Polyp Segmentation and Detection } },
        booktitle = {proceedings of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
        year = {2024},
        publisher = {Springer Nature Switzerland},
        volume = {LNCS 15008},
        page = {544 -- 554}
}




@inproceedings{ssformer,
  title={Stepwise Feature Fusion: Local Guides Global},
  author={Jinfeng Wang and Qiming Huang and Feilong Tang and Jia Meng and Jionglong Su and Sifan Song},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2022},
}




@article{ColnNet,
  author={Jain, Samir and Atale, Rohan and Gupta, Anubhav and Mishra, Utkarsh and Seal, Ayan and Ojha, Aparajita and Jaworek-Korjakowska, Joanna and Krejcar, Ondrej},
  journal={IEEE Transactions on Medical Imaging}, 
  title={CoInNet: A Convolution-Involution Network With a Novel Statistical Attention for Automatic Polyp Segmentation}, 
  year={2023},
  volume={42},
  pages={3987-4000},
  doi={10.1109/TMI.2023.3320151}
}





@misc{attnunet,
      title = 	 {Attention u-net: Learning where to look for the pancreas.},
      author =       {Oktay, Ozan and Jo Schlemper and Loic Le Folgoc and Matthew Lee and Mattias Heinrich and Kazunari Misawa and Kensaku Mori.},
      year={2018},
      eprint={1804.03999},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/1804.03999}, 
}





@inproceedings{swinunet,
  author={Cao, Hu and Yueyue Wang and Joy Chen and Dongsheng Jiang and Xiaopeng Zhang and Qi Tian and Manning Wang},
  title={Swin-unet: Unet-like pure transformer for medical image segmentation.}, 
  booktitle={In European conference on computer vision}, 
  year={2022},
  pages={205-218},
}




@inproceedings{pvtcascade,
  author={Titoriya, A. K. and Singh, M. P.},
  booktitle={8th International Conference on Computing in Engineering and Technology (ICCET 2023)}, 
  title={PVT-CASCADE network on skin cancer dataset}, 
  year={2023},
  volume={2023},
  pages={480-486},
  doi={10.1049/icp.2023.1536}
}



@inproceedings{transcascade,
  author={Rahman, Md Mostafijur and Marculescu, Radu},
  booktitle={2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, 
  title={Medical Image Segmentation via Cascaded Attention Decoding}, 
  year={2023},
  pages={6211-6220},
  doi={10.1109/WACV56688.2023.00616}
}


@inproceedings{pvtemcad,
  title={Emcad: Efficient multi-scale convolutional attention decoding for medical image segmentation},
  author={Rahman, Md Mostafijur and Munir, Mustafa and Marculescu, Radu},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={11769--11779},
  year={2024}
}


@article{fcv-swinv2,
  author={Fitzgerald, Kerr and Bernal, Jorge and Histace, Aymeric and Matuszewski, Bogdan J.},
  journal={IEEE Access}, 
  title={Polyp Segmentation With the FCB-SwinV2 Transformer}, 
  year={2024},
  volume={12},
  pages={38927-38943},

}


@article{sam2-unext,
  title={Sam2-unext: an improved high-resolution baseline for adapting foundation models to downstream segmentation tasks},
  author={Xiong, Xinyu and Wu, Zihuang and Zhang, Lei and Lu, Lei and Li, Ming and Li, Guanbin},
  journal={arXiv preprint arXiv:2508.03566},
  year={2025}
}



@inproceedings{dsu-net,
  author={Xu, Yimin and Yang, Fan and Xu, Bin},
  booktitle={2025 8th International Conference on Artificial Intelligence and Big Data (ICAIBD)}, 
  title={DSU-Net: An Improved U-Net Model Based on DINOv2 and SAM2 with Multi-scale Cross-model Feature Enhancement}, 
  year={2025},
  pages={625-632},
  }


@article{sam2,
  title={SAM 2: Segment Anything in Images and Videos},
  author={Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and Hu, Ronghang and Ryali, Chaitanya and Ma, Tengyu and Khedr, Haitham and R{\"a}dle, Roman and Rolland, Chloe and Gustafson, Laura and Mintun, Eric and Pan, Junting and Alwala, Kalyan Vasudev and Carion, Nicolas and Wu, Chao-Yuan and Girshick, Ross and Doll{\'a}r, Piotr and Feichtenhofer, Christoph},
  journal={arXiv preprint arXiv:2408.00714},
  url={https://arxiv.org/abs/2408.00714},
  year={2024}
}


@misc{dinov2,
  title={DINOv2: Learning Robust Visual Features without Supervision},
  author={Oquab, Maxime and Darcet, Timothée and Moutakanni, Theo and Vo, Huy V. and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and Howes, Russell and Huang, Po-Yao and Xu, Hu and Sharma, Vasu and Li, Shang-Wen and Galuba, Wojciech and Rabbat, Mike and Assran, Mido and Ballas, Nicolas and Synnaeve, Gabriel and Misra, Ishan and Jegou, Herve and Mairal, Julien and Labatut, Patrick and Joulin, Armand and Bojanowski, Piotr},
  journal={arXiv:2304.07193},
  year={2023}
}


@article{sam2-unet,
  title={Sam2-unet: Segment anything 2 makes strong encoder for natural and medical image segmentation},
  author={Xiong, Xinyu and Wu, Zihuang and Tan, Shuangyi and Li, Wenxue and Tang, Feilong and Chen, Ying and Li, Siying and Ma, Jie and Li, Guanbin},
  journal={Visual Intelligence},
  volume={4},
  pages={2},
  year={2026},
}




@misc{SAM3,
      title={SAM 3: Segment Anything with Concepts},
      author={Nicolas Carion and Laura Gustafson and Yuan-Ting Hu and Shoubhik Debnath and Ronghang Hu and Didac Suris and Chaitanya Ryali and Kalyan Vasudev Alwala and Haitham Khedr and Andrew Huang and Jie Lei and Tengyu Ma and Baishan Guo and Arpit Kalla and Markus Marks and Joseph Greer and Meng Wang and Peize Sun and Roman Rädle and Triantafyllos Afouras and Effrosyni Mavroudi and Katherine Xu and Tsung-Han Wu and Yu Zhou and Liliane Momeni and Rishi Hazra and Shuangrui Ding and Sagar Vaze and Francois Porcher and Feng Li and Siyuan Li and Aishwarya Kamath and Ho Kei Cheng and Piotr Dollár and Nikhila Ravi and Kate Saenko and Pengchuan Zhang and Christoph Feichtenhofer},
      year={2025},
      eprint={2511.16719},
      url={https://arxiv.org/abs/2511.16719},
}



@article{samed,
  title={Customized Segment Anything Model for Medical Image Segmentation},
  author={Kaidong Zhang and Dong Liu},
  journal={arXiv preprint arXiv:2304.13785},
  year={2023}
}



@inproceedings{samed2,
  title={SAMed-2: Selective Memory Enhanced Medical Segment Anything Model},
  author={Yan, Zhiling and Song, Sifan and Song, Dingjie and Li, Yiwei and Zhou, Rong and Sun, Weixiang and Chen, Zhennong and Kim, Sekeun and Ren, Hui and Liu, Tianming and others},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).},
  year={2025}
}




@InProceedings{SAMUS,
        author = {Lin, Xian and Xiang, Yangyang and Yu, Li and Yan, Zengqiang},
        title = {Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting },
        booktitle = {proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI)},
        year = {2024},
        page = {24-34}
}





@article{nusegdg,
  title={NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation},
  author={Lou, Zhenye and Xu, Qing and Jiang, Zekun and He, Xiangjian and Chen, Zhen and Wang, Yi and Li, Chenxin and He, Maggie M and Duan, Wenting},
  journal={arXiv preprint arXiv:2408.11787},
  year={2024}
}



@article{mambaunet,
  title={Mamba-unet: Unet-like pure visual mamba for medical image segmentation},
  author={Wang, Ziyang and Zheng, Jian-Qing and Zhang, Yichi and Cui, Ge and Li, Lei},
  journal={arXiv preprint arXiv:2402.05079},
  year={2024}
}



@misc{AttUKAN,
      title={Novel Extraction of Discriminative Fine-Grained Feature to Improve Retinal Vessel Segmentation}, 
      author={Shuang Zeng and Chee Hong Lee and Micky C Nnamdi and Wenqi Shi and J Ben Tamo and Lei Zhu and Hangzhou He and Xinliang Zhang and Qian Chen and May D. Wang and Yanye Lu and Qiushi Ren},
      year={2025},
      eprint={2505.03896},
      url={https://arxiv.org/abs/2505.03896}, 
}




@misc{sam3-unet,
      title={SAM3-UNet: Simplified Adaptation of Segment Anything Model 3}, 
      author={Xinyu Xiong and Zihuang Wu and Lei Lu and Yufa Xia},
      year={2025},
      eprint={2512.01789},
      url={https://arxiv.org/abs/2512.01789}, 
}


