@inproceedings{ref_segmentation_guided,
  author = {Konz, Nicholas and others},
  title = {Anatomically-controllable medical image generation with segmentation-guided diffusion models},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2024},
  publisher = {Springer Nature Switzerland},
  address = {Cham}
}

@inproceedings{ref_gan,
  author = {Goodfellow, Ian and others},
  title = {Generative adversarial nets},
  booktitle = {Advances in neural information processing systems},
  volume = {27},
  year = {2014}
}

@inproceedings{ref_datasetgan,
  author = {Zhang, Yuxuan and others},
  title = {Datasetgan: Efficient labeled data factory with minimal human effort},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year = {2021}
}

@article{ref_generatect,
  author = {Hamamci, Ibrahim Ethem and others},
  title = {GenerateCT: Text-guided 3D chest CT generation},
  journal = {CoRR},
  year = {2023}
}

@inproceedings{reference_medgen3d,
  author = {Han, Kun and others},
  title = {MedGen3D: A deep generative framework for paired 3D image and mask generation},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2023},
  publisher = {Springer Nature Switzerland},
  address = {Cham}
}

@inproceedings{ref_fid,
  author = {Heusel, Martin and Ramsauer, Hubert and Unterthiner, Thomas and Nessler, Bernhard and Hochreiter, Sepp},
  title = {GANs trained by a two time-scale update rule converge to a local Nash equilibrium},
  booktitle = {Advances in neural information processing systems},
  volume = {30},
  year = {2017}
}

@inproceedings{ref_maisi,
  author = {Guo, Pengfei and others},
  title = {MAISI: Medical AI for Synthetic Imaging},
  booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  year = {2025}
}

@inproceedings{ref_DiffTumor,
  author = {Chen, Qi and others},
  title = {Towards generalizable tumor synthesis},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year = {2024}
}

@article{ref_ddpm,
  author = {Ho, Jonathan and Jain, Ajay and Abbeel, Pieter},
  title = {Denoising diffusion probabilistic models},
  journal = {Advances in neural information processing systems},
  volume = {33},
  pages = {6840--6851},
  year = {2020}
}

@inproceedings{ref_ldm,
  author = {Rombach, Robin and others},
  title = {High-resolution image synthesis with latent diffusion models},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year = {2022}
}

@article{ref_hagan,
  author = {Sun, Li and others},
  title = {Hierarchical amortized GAN for 3D high-resolution medical image synthesis},
  journal = {IEEE Journal of Biomedical and Health Informatics},
  volume = {26},
  number = {8},
  pages = {3966--3975},
  year = {2022}
}

@inproceedings{ref_segthor,
  author = {Lambert, Zoé and others},
  title = {SegTHOR: Segmentation of thoracic organs at risk in CT images},
  booktitle = {2020 Tenth International Conference on Image Processing Theory, Tools and Applications (IPTA)},
  year = {2020},
  publisher = {IEEE}
}


@misc{ref_AbdomenCT,
  author = "{Sage Bionetworks}",
  title = "{NCS Homepage}",
  year = "2025",
  url = "https://www.synapse.org/Synapse:syn3193805/wiki/217789",
  note = "Last accessed: 2025-02-01"
}


@article{ref_VQGAN,
  author = {Khader, Firas and others},
  title = {Denoising diffusion probabilistic models for 3D medical image generation},
  journal = {Scientific Reports},
  volume = {13},
  number = {1},
  pages = {7303},
  year = {2023}
}

@inproceedings{ref_SwinUnet,
  author = {Cao, Hu and others},
  title = {Swin-Unet: UNet-like pure transformer for medical image segmentation},
  booktitle = {European Conference on Computer Vision},
  year = {2022},
  publisher = {Springer Nature Switzerland},
  address = {Cham}
}

@inproceedings{ref_unetr,
  author = {Hatamizadeh, Ali and others},
  title = {UNETR: Transformers for 3D medical image segmentation},
  booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  year = {2022}
}
@inproceedings{controlnet,
  title={Adding conditional control to text-to-image diffusion models},
  author={Zhang, Lvmin and Rao, Anyi and Agrawala, Maneesh},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={3836--3847},
  year={2023}
}

@article{ref_pix2pix,
  title={Pix2pix gan for image-to-image translation},
  author={Henry, Joyce and Natalie, Terry and Madsen, Den},
  journal={Research Gate Publication},
  pages={1--5},
  year={2021}
}

@inproceedings{ref_pix2pixhd,
  title={High-resolution image synthesis and semantic manipulation with conditional gans},
  author={Wang, Ting-Chun and Liu, Ming-Yu and Zhu, Jun-Yan and Tao, Andrew and Kautz, Jan and Catanzaro, Bryan},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={8798--8807},
  year={2018}
}

@article{ref_3D_MedDiffusion,
  title={3d meddiffusion: A 3d medical diffusion model for controllable and high-quality medical image generation},
  author={Wang, Haoshen and Liu, Zhentao and Sun, Kaicong and Wang, Xiaodong and Shen, Dinggang and Cui, Zhiming},
  journal={arXiv preprint arXiv:2412.13059},
  year={2024}
}

@inproceedings{ref_Make,
  title={Make-a-volume: Leveraging latent diffusion models for cross-modality 3d brain mri synthesis},
  author={Zhu, Lingting and Xue, Zeyue and Jin, Zhenchao and Liu, Xian and He, Jingzhen and Liu, Ziwei and Yu, Lequan},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={592--601},
  year={2023},
  organization={Springer}
}
@article{ref_medddpm,
  title={Conditional diffusion models for semantic 3D brain MRI synthesis},
  author={Dorjsembe, Zolnamar and Pao, Hsing-Kuo and Odonchimed, Sodtavilan and Xiao, Furen},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={28},
  number={7},
  pages={4084--4093},
  year={2024},
  publisher={IEEE}
}

@inproceedings{ref_controlnet,
  title={Adding conditional control to text-to-image diffusion models},
  author={Zhang, Lvmin and Rao, Anyi and Agrawala, Maneesh},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={3836--3847},
  year={2023}
}

@misc{ref_segfactory,
      title={MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairs}, 
      author={Jiawei Mao and Yuhan Wang and Yucheng Tang and Daguang Xu and Kang Wang and Yang Yang and Zongwei Zhou and Yuyin Zhou},
      year={2025},
      eprint={2504.06897},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2504.06897}, 
}

@misc{ref_simgen,
      title={SimGen: A Diffusion-Based Framework for Simultaneous Surgical Image and Segmentation Mask Generation}, 
      author={Aditya Bhat and Rupak Bose and Chinedu Innocent Nwoye and Nicolas Padoy},
      year={2025},
      eprint={2501.09008},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2501.09008}, 
}

@article{ref_Colon,
   title={The Medical Segmentation Decathlon},
   volume={13},
   ISSN={2041-1723},
   url={http://dx.doi.org/10.1038/s41467-022-30695-9},
   DOI={10.1038/s41467-022-30695-9},
   number={1},
   journal={Nature Communications},
   publisher={Springer Science and Business Media LLC},
   author={Antonelli, Michela and Reinke, Annika and Bakas, Spyridon and Farahani, Keyvan and Kopp-Schneider, Annette and Landman, Bennett A. and Litjens, Geert and Menze, Bjoern and Ronneberger, Olaf and Summers, Ronald M. and van Ginneken, Bram and Bilello, Michel and Bilic, Patrick and Christ, Patrick F. and Do, Richard K. G. and Gollub, Marc J. and Heckers, Stephan H. and Huisman, Henkjan and Jarnagin, William R. and McHugo, Maureen K. and Napel, Sandy and Pernicka, Jennifer S. Golia and Rhode, Kawal and Tobon-Gomez, Catalina and Vorontsov, Eugene and Meakin, James A. and Ourselin, Sebastien and Wiesenfarth, Manuel and Arbeláez, Pablo and Bae, Byeonguk and Chen, Sihong and Daza, Laura and Feng, Jianjiang and He, Baochun and Isensee, Fabian and Ji, Yuanfeng and Jia, Fucang and Kim, Ildoo and Maier-Hein, Klaus and Merhof, Dorit and Pai, Akshay and Park, Beomhee and Perslev, Mathias and Rezaiifar, Ramin and Rippel, Oliver and Sarasua, Ignacio and Shen, Wei and Son, Jaemin and Wachinger, Christian and Wang, Liansheng and Wang, Yan and Xia, Yingda and Xu, Daguang and Xu, Zhanwei and Zheng, Yefeng and Simpson, Amber L. and Maier-Hein, Lena and Cardoso, M. Jorge},
   year={2022},
   month=jul }

@inproceedings{ref_lpips,
  title={The unreasonable effectiveness of deep features as a perceptual metric},
  author={Zhang, Richard and Isola, Phillip and Efros, Alexei A and Shechtman, Eli and Wang, Oliver},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={586--595},
  year={2018}
}
@article{ref_ssim,
  title={Image quality assessment: from error visibility to structural similarity},
  author={Wang, Zhou and Bovik, Alan C and Sheikh, Hamid R and Simoncelli, Eero P},
  journal={IEEE transactions on image processing},
  volume={13},
  number={4},
  pages={600--612},
  year={2004},
  publisher={IEEE}
}

@misc{ref_nnUnet,
      title={nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation}, 
      author={Fabian Isensee and Jens Petersen and Andre Klein and David Zimmerer and Paul F. Jaeger and Simon Kohl and Jakob Wasserthal and Gregor Koehler and Tobias Norajitra and Sebastian Wirkert and Klaus H. Maier-Hein},
      year={2018},
      eprint={1809.10486},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1809.10486}, 
}

@misc{ref_segresnet,
      title={3D MRI brain tumor segmentation using autoencoder regularization}, 
      author={Andriy Myronenko},
      year={2018},
      eprint={1810.11654},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1810.11654}, 
}