Awesome Diffusion Models in Medical Imaging

:fire::fire: This is a collection of awesome articles about diffusion models in medical imaging:fire::fire:

• Our survey paper on MedIA: Diffusion Models in Medical Imaging: A Comprehensive Survey :heart:
• Our survey paper on arXiv: Diffusion Models for Medical Image Analysis: A Comprehensive Survey :heart:

Citation

@article{kazerouni2023diffusion,
  title={Diffusion models in medical imaging: A comprehensive survey},
  author={Kazerouni, Amirhossein and Aghdam, Ehsan Khodapanah and Heidari, Moein and Azad, Reza and Fayyaz, Mohsen and Hacihaliloglu, Ilker and Merhof, Dorit},
  journal={Medical Image Analysis},
  pages={102846},
  year={2023},
  publisher={Elsevier}
}

Updates

• We have now achieved more than 1K stars 🌟—thank you community for your support! If you're interested in contributing to this repository, please don't hesitate to send me a message. Thank you!
• Check out our new paper accepted in MICCAI 2023 PRIME Workshop: DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation 🥳
• Third release: June 3, 2023
• :sunglasses: April 8, 2023: Our paper is accepted for publication in the Medical Image Analysis Journal (IF: 13.83) :sunglasses:
• Second release: March 29, 2023
• First release: November 14, 2022

Contents

• Survey Papers

• Challenge Reports

• Papers

  • Anomaly Detection
  • Denoising
  • Segmentation
  • Image-to-Image Translation
  • Reconstruction
  • Image Generation
  • Text-to-Image
  • Registration
  • Classification
  • Object Detection
  • Image Restoration
    • Inpainting
    • Super Resolution
    • Enhancement
  • Editing
  • Adversarial Attacks
  • Fairness
  • Time Series
  • Audio
  • Other Applications
  • Multi-task
  • Multimodal Generation & Reconstruction

Survey Papers

Generative Artificial Intelligence in Medical Imaging: Foundations, Progress, and Clinical Translation
Xuanru Zhou, Cheng Li, Shuqiang Wang, Ye Li, Tao Tan, Hairong Zheng, Shanshan Wang
[07th Aug., 2025] [arXiv, 2025]
[Paper]

Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review
Abdullah, Tao Huang, Ickjai Lee, Euijoon Ahn
[09th May, 2025] [arXiv, 2025]
[Paper]

Diffusion Models in 3D Vision: A Survey
Zhen Wang, Dongyuan Li, Yaozu Wu, Tianyu He, Jiang Bian, Renhe Jiang
[07th Oct., 2024] [arXiv, 2024]
[Paper]

Foundation Models for Music: A Survey
Yinghao Ma, Anders Øland, Anton Ragni, Bleiz MacSen Del Sette, Charalampos Saitis, Chris Donahue, Chenghua Lin, Christos Plachouras, Emmanouil Benetos, Elona Shatri, Fabio Morreale, Ge Zhang, György Fazekas, Gus Xia, Huan Zhang, Ilaria Manco, Jiawen Huang, Julien Guinot, Liwei Lin, Luca Marinelli, Max W. Y. Lam, Megha Sharma, Qiuqiang Kong, Roger B. Dannenberg, Ruibin Yuan, Shangda Wu, Shih-Lun Wu, Shuqi Dai, Shun Lei, Shiyin Kang, Simon Dixon, Wenhu Chen, Wenhao Huang, Xingjian Du, Xingwei Qu, Xu Tan, Yizhi Li, Zeyue Tian, Zhiyong Wu, Zhizheng Wu, Ziyang Ma, Ziyu Wang
[26th Aug., 2024] [arXiv, 2024]
[Paper] [GitHub] [Music Generation - Music Therapy & Medical Applications]

A Comprehensive Survey on Diffusion Models and Their Applications
Md Manjurul Ahsan, Shivakumar Raman, Yingtao Liu, Zahed Siddique
[1st Jul., 2024] [arXiv, 2024]
[Paper]

Physics-Inspired Generative Models in Medical Imaging: A Review
Dennis Hein, Afshin Bozorgpour, Dorit Merhof, Ge Wang
[15th Jul., 2024] [arXiv, 2024]
[Paper]

Diffusion Models in Low-Level Vision: A Survey
Chunming He, Yuqi Shen, Chengyu Fang, Fengyang Xiao, Longxiang Tang, Yulun Zhang, Wangmeng Zuo, Zhenhua Guo, Xiu Li
[16th Jun., 2024] [arXiv, 2024]
[Paper] [GitHub]

Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning -- A Review
Mohammadreza Amirian, Daniel Barco, Ivo Herzig, Frank-Peter Schilling
[27th Mar., 2024] [arXiv, 2024]
[Paper]

A Survey of Emerging Applications of Diffusion Probabilistic Models in MRI
Yuheng Fan, Hanxi Liao, Shiqi Huang, Yimin Luo, Huazhu Fu, Haikun Qi
[18th Nov., 2023] [arXiv, 2023]
[Paper]

A Comprehensive Review of Generative AI in Healthcare
Yasin Shokrollahi, Sahar Yarmohammadtoosky, Matthew M. Nikahd, Pengfei Dong, Xianqi Li, Linxia Gu
[24th Jul., 2023] [arXiv, 2023]
[Paper]

Generative AI for Medical Imaging: extending the MONAI Framework :fire:
Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot, Petru-Daniel Tudosiu, Jessica Dafflon, Virginia Fernandez, Pedro Sanchez, Julia Wolleb, Pedro F. da Costa, Ashay Patel, Hyungjin Chung, Can Zhao, Wei Peng, Zelong Liu, Xueyan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardoso
[27th Jul., 2023] [arXiv, 2023]
[Paper] [Github]

Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan
[24th Jul., 2023] [Journal of Imaging, 2023]
[Paper]

A Comprehensive Survey on Generative Diffusion Models for Structured Data
Heejoon Koo, To Eun Kim
[7th Jun., 2023] [arXiv, 2023]
[Paper]

Diffusion Models for Time Series Applications: A Survey
Lequan Lin, Zhengkun Li, Ruikun Li, Xuliang Li, Junbin Gao
[1st May, 2023] [arXiv, 2023]
[Paper]

A Comprehensive Survey on Knowledge Distillation of Diffusion Models
Weijian Luo
[9th Apr., 2023] [arXiv, 2023]
[Paper]

A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material
Mengchun Zhang, Maryam Qamar, Taegoo Kang, Yuna Jung, Chenshuang Zhang, Sung-Ho Bae, Chaoning Zhang
[4th Apr., 2023] [arXiv, 2023]
[Paper]

Audio Diffusion Model for Speech Synthesis: A Survey on Text To Speech and Speech Enhancement in Generative AI
Chenshuang Zhang, Chaoning Zhang, Sheng Zheng, Mengchun Zhang, Maryam Qamar, Sung-Ho Bae, In So Kweon
[23th Mar., 2023] [arXiv, 2023]
[Paper]

Diffusion Models in NLP: A Survey
Yuansong Zhu, Yu Zhao
[14th Mar., 2023] [arXiv, 2023]
[Paper]

Text-to-image Diffusion Model in Generative AI: A Survey
Chenshuang Zhang, Chaoning Zhang, Mengchun Zhang, In So Kweon
[14th Mar., 2023] [arXiv, 2023]
[Paper]

Diffusion Models for Non-autoregressive Text Generation: A Survey
Yifan Li, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen
[12th Mar., 2023] [arXiv, 2023]
[Paper]

Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Action
Zhiye Guo, Jian Liu, Yanli Wang, Mengrui Chen, Duolin Wang, Dong Xu, Jianlin Cheng
[13th Feb., 2023] [arXiv, 2023]
[Paper]

Generative Diffusion Models on Graphs: Methods and Applications
Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li
[6th Feb., 2023] [arXiv, 2023]
[Paper]

Diffusion Models in Medical Imaging: A Comprehensive Survey :fire:
Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, Dorit Merhof
[14th Nov., 2022] [MedIA Journal, 2023]
[Paper]

Efficient Diffusion Models for Vision: A Survey
Anwaar Ulhaq, Naveed Akhtar, Ganna Pogrebna
[7th Oct., 2022] [arXiv, 2022]
[Paper]

Diffusion Models in Vision: A Survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, Mubarak Shah
[10th Sep., 2022] [arXiv, 2022]
[Paper] [Github]

A Survey on Generative Diffusion Model
Hanqun Cao, Cheng Tan, Zhangyang Gao, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li
[6th Sep., 2022] [arXiv, 2022]
[Paper] [Github]

Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Bin Cui, Ming-Hsuan Yang
[2nd Sep., 2022] [arXiv, 2022]
[Paper] [Github]

Challenge Reports

Federated Learning for Medical Image Classification: A Comprehensive Benchmark
Zhekai Zhou, Guibo Luo, Mingzhi Chen, Zhenyu Weng, Yuesheng Zhu
[07th Apr., 2025] [arXiv, 2025]
[Paper]

Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics
Rucha Deshpande, Varun A. Kelkar, Dimitrios Gotsis, Prabhat Kc, Rongping Zeng, Kyle J. Myers, Frank J. Brooks, Mark A. Anastasio
[2nd May] [arXiv, 2024]
[Paper] [Website]

Papers

Anomaly Detection

Denoising Diffusion Models for Anomaly Localization in Medical Images
Cosmin I. Bercea, Philippe C. Cattin, Julia A. Schnabel, Julia Wolleb
[31th Oct., 2024] [arXiv, 2024]
[Paper]

Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection
Finn Behrendt, Debayan Bhattacharya, Robin Mieling, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer
[03th Oct., 2024] [MICCAI, 2024]
[Paper] [GitHub]

CADD: Context aware disease deviations via restoration of brain images using normative conditional diffusion models
Ana Lawry Aguila, Ayodeji Ijishakin, Juan Eugenio Iglesias, Tomomi Takenaga, Yukihiro Nomura, Takeharu Yoshikawa, Osamu Abe, Shouhei Hanaoka
[05th Aug., 2025] [arXiv, 2025]
[Paper]

Unsupervised anomaly detection using Bayesian flow networks: application to brain FDG PET in the context of Alzheimer's disease
Hugues Roy, Reuben Dorent, Ninon Burgos
[23th Jul., 2025] [arXiv, 2025]
[Paper]

Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays
Harim Kim, Yuhan Wang, Minkyu Ahn, Heeyoul Choi, Yuyin Zhou, Charmgil Hong
[22th May., 2025] [arXiv, 2025]
[Paper]

HDM: Hybrid Diffusion Model for Unified Image Anomaly Detection
Zekang Weng, Jinjin Shi, Jinwei Wang, Zeming Han
[26th Feb., 2025] [arXiv, 2025]
[Paper]

MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection
Farzad Beizaee, Gregory Lodygensky, Christian Desrosiers, Jose Dolz
[24th Feb., 2025] [arXiv, 2025]
[Paper]

Synomaly Noise and Multi-Stage Diffusion: A Novel Approach for Unsupervised Anomaly Detection in Medical Images
Yuan Bi, Lucie Huang, Ricarda Clarenbach, Reza Ghotbi, Angelos Karlas, Nassir Navab, Zhongliang Jiang
[06th Nov., 2024] [arXiv, 2024]
[Paper]

MCDDPM: Multichannel Conditional Denoising Diffusion Model for Unsupervised Anomaly Detection in Brain MRI
Vivek Kumar Trivedi, Bheeshm Sharma, P. Balamurugan
[29th Sep., 2024] [arXiv, 2024]
[Paper] [GitHub]

Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection
Finn Behrendt, Debayan Bhattacharya, Lennart Maack, Julia Krüger, Roland Opfer, Robin Mieling, Alexander Schlaefer
[22nd Aug., 2024] [ISBI, 2024]
[Paper] [Github]

Combining Reconstruction-based Unsupervised Anomaly Detection with Supervised Segmentation for Brain MRIs
Finn Behrendt, Debayan Bhattacharya, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer
[6th Jun., 2024] [MIDL, 2024]
[Paper] [Github]

Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection
Julia Wolleb, Florentin Bieder, Paul Friedrich, Peter Zhang, Alicia Durrer, Philippe C. Cattin
[18th Mar., 2024] [arXiv, 2024]
[Paper] [Github]

Diffusion Models with Implicit Guidance for Medical Anomaly Detection
Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel
[13th Mar., 2024] [arXiv, 2024]
[Paper] [GitHub]

Objective and Interpretable Breast Cosmesis Evaluation with Attention Guided Denoising Diffusion Anomaly Detection Model
Sangjoon Park, Yong Bae Kim, Jee Suk Chang, Seo Hee Choi, Hyungjin Chung, Ik Jae Lee, Hwa Kyung Byun
[28th Feb., 2024] [arXiv, 2024]
[Paper]

MAEDiff: Masked Autoencoder-enhanced Diffusion Models for Unsupervised Anomaly Detection in Brain Images
Rui Xu, Yunke Wang, Bo Du
[19th Jan., 2024] [arXiv, 2024]
[Paper]

Unsupervised Anomaly Detection using Aggregated Normative Diffusion
Alexander Frotscher, Jaivardhan Kapoor, Thomas Wolfers, Christian F. Baumgartner
[4th Dec., 2023] [arXiv, 2023]
[Paper] [Github]

DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection
Sergio Naval Marimont, Matthew Baugh, Vasilis Siomos, Christos Tzelepis, Bernhard Kainz, Giacomo Tarroni
[26th Nov., 2023] [arXiv, 2023]
[Paper]

Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs
Finn Behrendt, Debayan Bhattacharya, Robin Mieling, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer
[7th Dec., 2023] [arXiv, 2023]
[Paper] [Github]

Histogram- and Diffusion-Based Medical Out-of-Distribution Detection
Evi M.C. Huijben, Sina Amirrajab, Josien P.W. Pluim
[12th Oct., 2023] [arXiv, 2023]
[Paper] [Github]

AnoDODE: Anomaly Detection with Diffusion ODE
Xianyao Hu, Congming Jin
[10th Aug., 2023] [arXiv, 2023]
[Paper]

Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
Ziyun Liang, Harry Anthony, Felix Wagner, Konstantinos Kamnitsas
[30th Aug., 2023] [arXiv, 2023]
[Paper] [Github]

Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images
Alessandro Fontanella, Grant Mair, Joanna Wardlaw, Emanuele Trucco, Amos Storkey
[3rd Aug., 2023] [arXiv, 2023]
[Paper] [Github]

SANO: Score-Based Diffusion Model for Anomaly Localization in Dermatology
Alvaro Gonzalez-Jimenez, Simone Lionetti, Marc Pouly, Alexander A. Navarini
[18th Jun., 2023] [CVPR Workshop, 2023]
paper]

Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models
Cosmin I. Bercea, Michael Neumayr, Daniel Rueckert, Julia A. Schnabel
[31st May, 2023] [arXiv, 2023]
[Paper]

Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model
Hasan Iqbal, Umar Khalid, Jing Hua, Chen Chen
[31st May, 2023] [MICCAI MLMI Workshop, 2023]
[Paper] [Github]

Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection
Cosmin I Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A Schnabel
[15th Mar., 2023] [arXiv, 2023]
[Paper]

Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI
Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer
[7th Mar., 2023] [MIDL, 2023]
[Paper] [Github]

Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection
Jian Shi, Pengyi Zhang, Ni Zhang, Hakim Ghazzai, Yehia Massoud
[28th Feb., 2023] [arXiv, 2023]
[Paper]

The role of noise in denoising models for anomaly detection in medical images
Antanas Kascenas, Pedro Sanchez, Patrick Schrempf, Chaoyang Wang, William Clackett, Shadia S. Mikhael, Jeremy P. Voisey, Keith Goatman, Alexander Weir, Nicolas Pugeault, Sotirios A. Tsaftaris, Alison Q. O'Neil
[19th Jan., 2023] [MedIA Journal, 2023]
[Paper] [Github]

What is Healthy? Generative Counterfactual Diffusion for Lesion Localization
Pedro Sanchez, Antanas Kascenas, Xiao Liu, Alison Q. O'Neil, Sotirios A. Tsaftaris
[25th Jul., 2022] [MICCAI Workshop, 2022]
[Paper] [Github]

AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise
Julian Wyatt, Adam Leach, Sebastian M. Schmon, Chris G. Willcocks
[1st Jun., 2022] [CVPR Workshop, 2022]
[Paper] [Github]

The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models
Julia Wolleb, Robin Sandkühler, Florentin Bieder, Philippe C. Cattin
[6th Apr., 2022] [arXiv, 2022]
[Paper]

Diffusion Models for Medical Anomaly Detection
Julia Wolleb, Florentin Bieder, Robin Sandkühler, Philippe C. Cattin
[8th Mar., 2022] [MICCAI, 2022]
[Paper] [Github]

Denoising

DiffDenoise: Self-Supervised Medical Image Denoising with Conditional Diffusion Models
Basar Demir, Yikang Liu, Xiao Chen, Eric Z. Chen, Lin Zhao, Boris Mailhe, Terrence Chen, Shanhui Sun
[31st Mar., 2025] [arXiv, 2025]
[Paper]

Ultrasound Imaging based on the Variance of a Diffusion Restoration Model
Yuxin Zhang, Clément Huneau, Jérôme Idier, Diana Mateus
[17th Jun., 2024] [EUSIPCO]
[Paper] [Github]

Dose-aware Diffusion Model for 3D Low-dose PET: Multi-institutional Validation with Reader Study and Real Low-dose Data
Huidong Xie, Weijie Gan, Bo Zhou, Ming-Kai Chen, Michal Kulon, Annemarie Boustani, Benjamin A. Spencer, Reimund Bayerlein, Xiongchao Chen, Qiong Liu, Xueqi Guo, Menghua Xia, Yinchi Zhou, Hui Liu, Liang Guo, Hongyu An, Ulugbek S. Kamilov, Hanzhong Wang, Biao Li, Axel Rominger, Kuangyu Shi, Ge Wang, Ramsey D. Badawi, Chi Liu
[2nd May, 2024] [arXiv, 2024]
[Paper]

Implicit Image-to-Image Schrodinger Bridge for CT Super-Resolution and Denoising
Yuang Wang, Siyeop Yoon, Pengfei Jin, Matthew Tivnan, Zhennong Chen, Rui Hu, Li Zhang, Zhiqiang Chen, Quanzheng Li, Dufan Wu
[10th Mar., 2024] [arXiv, 2024]
[Paper]

SDDPM: Speckle Denoising Diffusion Probabilistic Models
Soumee Guha, Scott T. Acton
[17th Nov., 2023] [arXiv, 2023]
[Paper]

Deep Ultrasound Denoising Using Diffusion Probabilistic Models
Hojat Asgariandehkordi, Sobhan Goudarzi, Adrian Basarab, Hassan Rivaz
[12th Jun., 2023] [arXiv, 2023]
[Paper]

A Diffusion Probabilistic Prior for Low-Dose CT Image Denoising
Xuan Liu, Yaoqin Xie, Songhui Diao, Shan Tan, Xiaokun Liang
[25th May, 2023] [arXiv, 2023]
[Paper]

CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization
Qi Gao, Zilong Li, Junping Zhang, Yi Zhang, Hongming Shan
[4th Apr., 2023] [arXiv, 2023]
[Paper]

DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
Tiange Xiang, Mahmut Yurt, Ali B Syed, Kawin Setsompop, Akshay Chaudhari
[6th Feb., 2023] [ICLR, 2023]
[Paper] [Github]

Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20× Speedup
Wenjun Xia, Qing Lyu, Ge Wang
[29th Sep., 2022] [arXiv, 2022]
[Paper]

PET image denoising based on denoising diffusion probabilistic models
Kuang Gong, Keith A. Johnson, Georges El Fakhri, Quanzheng Li, Tinsu Pan
[13th Sep., 2022] [European Journal of Nuclear Medicine and Molecular Imaging, 2022]
[Paper]

Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model
Dewei Hu, Yuankai K. Tao, Ipek Oguz
[27th Jan., 2022] [Medical Imaging 2022: Image Processing]
[Paper] [Github]

Segmentation

Aleatoric Uncertainty Medical Image Segmentation Estimation via Flow Matching
Phi Van Nguyen, Ngoc Huynh Trinh, Duy Minh Lam Nguyen, Phu Loc Nguyen, Quoc Long Tran
[30th Jul., 2025] [arXiv, 2025]
[Paper] [Github]

Flow Stochastic Segmentation Networks
Fabio De Sousa Ribeiro, Omar Todd, Charles Jones, Avinash Kori, Raghav Mehta, Ben Glocker
[24th Jul., 2025] [arXiv, 2025]
[Paper] [Github]

LEAF: Latent Diffusion with Efficient Encoder Distillation for Aligned Features in Medical Image Segmentation
Qilin Huang, Tianyu Lin, Zhiguang Chen, Fudan Zheng
[24th Jul., 2025] [arXiv, 2025]
[Paper] [Github]

Robust Noisy Pseudo-label Learning for Semi-supervised Medical Image Segmentation Using Diffusion Model
Lin Xi, Yingliang Ma, Cheng Wang, Sandra Howell, Aldo Rinaldi, Kawal S. Rhode
[22nd Jul., 2025] [arXiv, 2025]
[Paper]

Latent Space Synergy: Text-Guided Data Augmentation for Direct Diffusion Biomedical Segmentation
Muhammad Aqeel, Maham Nazir, Zanxi Ruan, Francesco Setti
[21st Jul., 2025] [arXiv, 2025]
[Paper]

SegDT: A Diffusion Transformer-Based Segmentation Model for Medical Imaging
Salah Eddine Bekhouche, Gaby Maroun, Fadi Dornaika, Abdenour Hadid
[21st Jul., 2025] [arXiv, 2025]
[Paper] [Github]

DiffOSeg: Omni Medical Image Segmentation via Multi-Expert Collaboration Diffusion Model
Han Zhang, Xiangde Luo, Yong Chen, Kang Li
[17th Jul., 2025] [arXiv, 2025]
[Paper] [Github]

Diffusion Model-based Data Augmentation Method for Fetal Head Ultrasound Segmentation
Fangyijie Wang, Kevin Whelan, Félix Balado, Kathleen M. Curran, Guénolé Silvestre
[30th Jun., 2025] [arXiv, 2025]
[Paper]

Contrastive Learning with Diffusion Features for Weakly Supervised Medical Image Segmentation
Dewen Zeng, Xinrong Hu, Yu-Jen Chen, Yawen Wu, Xiaowei Xu, Yiyu Shi
[30th Jun., 2025] [arXiv, 2025]
[Paper]

Inpainting is All You Need: A Diffusion-based Augmentation Method for Semi-supervised Medical Image Segmentation
Xinrong Hu, Yiyu Shi
[28th Jun., 2025] [arXiv, 2025]
[Paper]

CLAIM: Clinically-Guided LGE Augmentation for Realistic and Diverse Myocardial Scar Synthesis and Segmentation
Farheen Ramzan, Yusuf Kiberu, Nikesh Jathanna, Shahnaz Jamil-Copley, Richard H. Clayton, Chen Chen
[18th Jun., 2025] [arXiv, 2025]
[Paper] [Github]

Echo-DND: A dual noise diffusion model for robust and precise left ventricle segmentation in echocardiography
Abdur Rahman, Keerthiveena Balraj, Manojkumar Ramteke, Anurag Singh Rathore
[18th Jun., 2025] [Discover Applied Sciences (Springer Nature), 2025]
[Paper] [Github] [Project Page]

Unleashing Diffusion and State Space Models for Medical Image Segmentation
Rong Wu, Ziqi Chen, Liming Zhong, Heng Li, Hai Shu
[15th Jun., 2025] [arXiv, 2025]
[Paper] [Github]

Enhancing Privacy: The Utility of Stand-Alone Synthetic CT and MRI for Tumor and Bone Segmentation
André Ferreira, Kunpeng Xie, Caroline Wilpert, Gustavo Correia, Felix Barajas Ordonez, Tiago Gil Oliveira, Maike Bode, Robert Siepmann, Frank Hölzle, Rainer Röhrig, Jens Kleesiek, Daniel Truhn, Jan Egger, Victor Alves, Behrus Puladi
[13th Jun., 2025] [arXiv, 2025]
[Paper] [Github]

TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matching
Shengyuan Liu, Wenting Chen, Boyun Zheng, Wentao Pan, Xiang Li, Yixuan Yuan
[30th May, 2025] [arXiv, 2025]
[Paper]

Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization
Abderrachid Hamrani, Daniela Leizaola, Renato Sousa, Jose P. Ponce, Stanley Mathis, David G. Armstrong, Anuradha Godavarty
[24th Apr., 2025] [IEEE Journal of Biomedical and Health Informatics, 2025]
[Paper]

TextDiffSeg: Text-guided Latent Diffusion Model for 3d Medical Images Segmentation
Kangbo Ma
[16th Apr., 2025] [arXiv, 2025]
[Paper]

Diffusion Based Ambiguous Image Segmentation
Jakob Lønborg Christensen, Morten Rieger Hannemose, Anders Bjorholm Dahl, Vedrana Andersen Dahl
[08th Apr., 2025] [arXiv, 2025]
[Paper]

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training
Luca Ciampi, Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi
[2nd Apr., 2025] [arXiv, 2025] \ [Paper] [GitHub]

Diff-CL: A Novel Cross Pseudo-Supervision Method for Semi-supervised Medical Image Segmentation
Xiuzhen Guo, Lianyuan Yu, Ji Shi, Na Lei, Hongxiao Wang
[12th Mar., 2025] [arXiv, 2025]
[Paper]

DiffAtlas: GenAI-fying Atlas Segmentation via Image-Mask Diffusion
Hantao Zhang, Yuhe Liu, Jiancheng Yang, Weidong Guo, Xinyuan Wang, Pascal Fua
[09th Mar., 2025] [arXiv, 2025]
[Paper] [GitHub]

Conditional diffusion model with spatial attention and latent embedding for medical image segmentation
Behzad Hejrati, Soumyanil Banerjee, Carri Glide-Hurst, Ming Dong
[10th Feb., 2025] [MICCAI, 2024]
[Paper] [GitHub]

Medical Semantic Segmentation with Diffusion Pretrain
David Li, Anvar Kurmukov, Mikhail Goncharov, Roman Sokolov, Mikhail Belyaev
[31st Jan., 2025] [arXiv, 2025]
[Paper]

MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation
Avni Mittal, John Kalkhof, Anirban Mukhopadhyay, Arnav Bhavsar
[05th Jan., 2025] [arXiv, 2025]
[Paper]

Bridging Classification and Segmentation in Osteosarcoma Assessment via Foundation and Discrete Diffusion Models
Manh Duong Nguyen, Dac Thai Nguyen, Trung Viet Nguyen, Homi Yamada, Huy Hieu Pham, Phi Le Nguyen
[03rd Jan., 2025] [ISBI, 2025]
[Paper] [Github]

Structure-Aware Stylized Image Synthesis for Robust Medical Image Segmentation
Jie Bao, Zhixin Zhou, Wen Jung Li, Rui Luo
[05th Dec., 2024] [arXiv, 2024]
[Paper] [Github]

vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation
Bastian Wittmann, Yannick Wattenberg, Tamaz Amiranashvili, Suprosanna Shit, Bjoern Menze
[26th Nov., 2024] [CVPR, 2025]
[Paper] [Github]

ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection
Tao Wang, Xinlin Zhang, Yuanbin Chen, Yuanbo Zhou, Longxuan Zhao, Tao Tan, Tong Tong
[15th Nov., 2024] [arXiv, 2024]
[Paper] [GitHub]

Comparative Study of Probabilistic Atlas and Deep Learning Approaches for Automatic Brain Tissue Segmentation from MRI Using N4 Bias Field Correction and Anisotropic Diffusion Pre-processing Techniques
Mohammad Imran Hossain, Muhammad Zain Amin, Daniel Tweneboah Anyimadu, Taofik Ahmed Suleiman
[08th Nov., 2024] [arXiv, 2024]
[Paper] [GitHub]

Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal Mechanisms
Boqi Chen, Yuanzhi Zhu, Yunke Ao, Sebastiano Caprara, Reto Sutter, Gunnar Rätsch, Ender Konukoglu, Anna Susmelj
[07th Nov., 2024] [WACV, 2025] \ [Paper] [GitHub]

Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models
Houze Liu, Tong Zhou, Yanlin Xiang, Aoran Shen, Jiacheng Hu, Junliang Du
[21th Nov., 2024] [arXiv, 2024]
[Paper]

PGDiffSeg: Prior-Guided Denoising Diffusion Model with Parameter-Shared Attention for Breast Cancer Segmentation
Feiyan Feng, Tianyu Liu, Hong Wang, Jun Zhao, Wei Li, Yanshen Sun
[23th Oct., 2024] [arXiv, 2024]
[Paper]

AdaptDiff: Cross-Modality Domain Adaptation via Weak Conditional Semantic Diffusion for Retinal Vessel Segmentation
Dewei Hu, Hao Li, Han Liu, Jiacheng Wang, Xing Yao, Daiwei Lu, Ipek Oguz
[06th Oct., 2024] [SASHIMI, 2024]
[Paper] [GitHub]

Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models
Haifan Gong, Yitao Wang, Yihan Wang, Jiashun Xiao, Xiang Wan, Haofeng Li
[12th Aug., 2024] [arXiv, 2024]
[Paper]

Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion Transformer
Sungmin Kang, Jaeha Song, Jihie Kim
[1st Aug., 2024] [BMVC, 2024]
[Paper]

FDiff-Fusion:Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation
Weiping Ding, Sheng Geng, Haipeng Wang, Jiashuang Huang, Tianyi Zhou
[21st Jul., 2024] [arXiv, 2024]
[Paper]

Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Model
Kun Zhao, Jakub Prokop, Javier Montalt Tordera, Sadegh Mohammadi
[19th Jul., 2024] [DGM4MICCAI, 2024]
[Paper] [GitHub]

Denoising Diffusions in Latent Space for Medical Image Segmentation
Fahim Ahmed Zaman, Mathews Jacob, Amanda Chang, Kan Liu, Milan Sonka, Xiaodong Wu
[17th Jul., 2024] [arXiv, 2024]
[Paper] [GitHub]

DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation
Xinyu Liu, Wuyang Li, Yixuan Yuan
[13th Jul., 2024] [MICCAI, 2024]
[Paper] [GitHub]

FairDiff: Fair Segmentation with Point-Image Diffusion
Wenyi Li, Haoran Xu, Guiyu Zhang, Huan-ang Gao, Mingju Gao, Mengyu Wang, Hao Zhao
[8th Jul., 2024] [MICCAI, 2024]
[Paper] [GitHub]

Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models
Chun-Mei Feng
[7th Jul., 2024] [MICCAI, 2024]
[Paper] [GitHub]

HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation
Tao Chen, Chenhui Wang, Zhihao Chen, Yiming Lei, Hongming Shan
[3rd Jul., 2024] [IEEE TMI, 2024]
[Paper] [GitHub]

Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process
Tianyu Lin, Zhiguang Chen, Zhonghao Yan, Weijiang Yu, Fudan Zheng
[26th Jun., 2024] [MICCAI, 2024]
[Paper] [GitHub]

CriDiff: Criss-cross Injection Diffusion Framework via Generative Pre-train for Prostate Segmentation
Tingwei Liu, Miao Zhang, Leiye Liu, Jialong Zhong, Shuyao Wang, Yongri Piao, Huchuan Lu
[20th Jun., 2024] [arXiv, 2024]
[Paper] [GitHub]

Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models
Reza Babaei, Samuel Cheng, Theresa Thai, Shangqing Zhao
[4th Jun., 2024] [arXiv, 2024]
[Paper]

Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation
Hongye Zeng, Ke Zou, Zhihao Chen, Rui Zheng, Huazhu Fu
[25th May, 2024] [arXiv, 2024]
[Paper] [GitHub]

CTS: A Consistency-Based Medical Image Segmentation Model
Kejia Zhang, Lan Zhang, Haiwei Pan, Baolong Yu
[14th May, 2024] [arXiv, 2024]
[Paper] [GitHub]

FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms
Lea Bogensperger, Dominik Narnhofer, Alexander Falk, Konrad Schindler, Thomas Pock
[28th May, 2024] [IJCV, 2024]
[Paper] [GitHub]

Discrepancy-based Diffusion Models for Lesion Detection in Brain MRI
Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
[8th May, 2024] [arXiv, 2024]
[Paper]

DiffSeg: A Segmentation Model for Skin Lesions Based on Diffusion Difference
Zhihao Shuai, Yinan Chen, Shunqiang Mao, Yihan Zho, Xiaohong Zhang
[25th Apr., 2024] [arXiv, 2024]
[Paper]

Analysing Diffusion Segmentation for Medical Images
Mathias Öttl, Siyuan Mei, Frauke Wilm, Jana Steenpass, Matthias Rübner, Arndt Hartmann, Matthias Beckmann, Peter Fasching, Andreas Maier, Ramona Erber, Katharina Breininger
[21st Mar., 2024] [arXiv, 2024]
[Paper]

Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation
Kevin Lin, Donald Brown, Sana Syed, Adam Greene
[17th Mar., 2024] [arXiv, 2024]
[Paper]

Polyp-DDPM: Diffusion-Based Semantic Polyp Synthesis for Enhanced Segmentation
Zolnamar Dorjsembe, Hsing-Kuo Pao, Furen Xiao
[6th Feb., 2024] [arXiv, 2024]
[Paper] [Github]

Surf-CDM: Score-Based Surface Cold-Diffusion Model For Medical Image Segmentation
Fahim Ahmed Zaman, Mathews Jacob, Amanda Chang, Kan Liu, Milan Sonka, Xiaodong Wu
[19th Dec., 2023] [arXiv, 2023]
[Paper]

LSegDiff: A Latent Diffusion Model for Medical Image Segmentation
Fahim Ahmed Zaman, Mathews Jacob, Amanda Chang, Kan Liu, Milan Sonka, Xiaodong Wu
[7th Dec., 2023] [SOICT, 2023]
[Paper]

Robust semi-supervised segmentation with timestep ensembling diffusion models
Margherita Rosnati, Melanie Roschewitz, Ben Glocker
[13th Nov., 2023] [arXiv, 2023]
[Paper]

A 3D generative model of pathological multi-modal MR images and segmentations
Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Mark S. Graham, Tom Vercauteren, M. Jorge Cardoso
[8th Nov., 2023] [arXiv, 2023]
[Paper] [Github]

One-shot Localization and Segmentation of Medical Images with Foundation Models
Deepa Anand, Gurunath Reddy M, Vanika Singhal, Dattesh D. Shanbhag, Shriram KS, Uday Patil, Chitresh Bhushan, Kavitha Manickam, Dawei Gui, Rakesh Mullick, Avinash Gopal, Parminder Bhatia, Taha Kass-Hout
[28th Oct., 2023] [arXiv, 2023]
[Paper]

Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
Haonan Wang, Xiaomeng Li
[17th Oct., 2023] [NeurIPS, 2023]
[Paper] [Github]

Certification of Deep Learning Models for Medical Image Segmentation
Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Nikos Paragios, Marie-Pierre Revel, Maria Vakalopoulou
[5th Oct., 2023] [MICCAI, 2023]
[Paper] [Github]

Introducing Shape Prior Module in Diffusion Model for Medical Image Segmentation
Zhiqing Zhang, Guojia Fan, Tianyong Liu, Nan Li, Yuyang Liu, Ziyu Liu, Canwei Dong, Shoujun Zhou
[12th Aug., 2023] [arXiv, 2023]
[Paper]

A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models
Yunguan Fu, Yiwen Li, Shaheer U Saeed, Matthew J Clarkson, Yipeng Hu
[30th Aug., 2023] [arXiv, 2023]
[Paper] [Github]

Masked Diffusion as Self-supervised Representation Learner
Zixuan Pan, Jianxu Chen, Yiyu Shi
[10th Aug., 2023] [arXiv, 2023]
[Paper]

DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation
Afshin Bozorgpour, Yousef Sadegheih, Amirhossein Kazerouni, Reza Azad, Dorit Merhof
[5th Aug., 2023] [MICCAI Workshop, 2023]
[Paper] [Github]

C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation
Boah Kim, Yujin Oh, Bradford J. Wood, Ronald M. Summers, Jong Chul Ye
[31st Jul., 2023] [arXiv, 2023]
[Paper]

Pre-Training with Diffusion models for Dental Radiography Segmentation
Jérémy Rousseau, Christian Alaka, Emma Covili, Hippolyte Mayard, Laura Misrachi, Willy Au
[26th Jul., 2023] [arXiv, 2023]
[Paper]

FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification
Héctor Carrión, Narges Norouzi
[21st Jul., 2023] [MICCAI, 2023]
[Paper] [Github]

Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Models
Tomer Amit, Shmuel Shichrur, Tal Shaharbany, and Lior Wolf
[15th Jun., 2023] [arXiv, 2023]
[Paper] [Github]

Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation
Xinrong Hu, Yu-Jen Chen, Tsung-Yi Ho, Yiyu Shi
[6th Jun., 2023] [arXiv, 2023]
[Paper] [Github]

Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion models
Muhammad Usman Akbar, Måns Larsson, and Anders Eklund
[5th Jun., 2023] [arXiv, 2023]
[Paper]

Semi-supervised Brain Tumor Segmentation Using Diffusion Models
Ahmed Alshenoudy, Bertram Sabrowsky-Hirsch, Stefan Thumfart, Michael Giretzlehner, Erich Kobler
[1st Jun., 2023] [AIAI, 2023]
[Paper] [Github]

Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model
Fenghe Tang, Jianrui Ding, Lingtao Wang, Min Xian, Chunping Ning
[16th May, 2023] [arXiv, 2023]
[Paper] [Github]

Unsupervised Discovery of 3D Hierarchical Structure with Generative Diffusion Features
Nurislam Tursynbek, Marc Niethammer
[28th Apr., 2023] [arXiv, 2023]
[Paper]

DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models
Shitong Shao, Xiaohan Yuan, Zhen Huang, Ziming Qiu, Shuai Wang, Kevin Zhou
[26th Apr., 2023] [arXiv, 2023]
[Paper] [Github]

Ambiguous Medical Image Segmentation using Diffusion Models
Aimon Rahman, Jeya Maria Jose Valanarasu, Ilker Hacihaliloglu, Vishal M Patel
[10th Apr., 2023] [CVPR, 2023]
[Paper] [Github]

BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation
Tao Chen, Chenhui Wang, Hongming Shan
[10th Apr., 2023] [arXiv, 2023]
[Paper]

Diffusion Models for Memory-efficient Processing of 3D Medical Images
Florentin Bieder, Julia Wolleb, Alicia Durrer, Robin Sandkühler, Philippe C. Cattin
[27th Mar., 2023] [MIDL, 2023]
[Paper]

Distribution Aligned Diffusion and Prototype-guided network for Unsupervised Domain Adaptive Segmentation
Haipeng Zhou, Lei Zhu, Yuyin Zhou
[22nd Mar., 2023] [arXiv, 2023]
[Paper] [Github]

Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation
Zhaohu Xing, Liang Wan, Huazhu Fu, Guang Yang, Lei Zhu
[18th Mar., 2023] [arXiv, 2023]
[Paper] [Github]

Stochastic Segmentation with Conditional Categorical Diffusion Models
Lukas Zbinden, Lars Doorenbos, Theodoros Pissas, Raphael Sznitman, Pablo Márquez-Neila
[15th Mar., 2023] [ICCV, 2023]
[Paper] [Github]

Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation
Yunguan Fu, Yiwen Li, Shaheer U. Saeed, Matthew J. Clarkson, Yipeng Hu
[10th Mar., 2023] [arXiv, 2023]
[Paper] [Github]

Score-Based Generative Models for Medical Image Segmentation using Signed Distance Functions
Lea Bogensperger, Dominik Narnhofer, Filip Ilic, Thomas Pock
[10th Mar., 2023] [arXiv, 2023]
[Paper]

MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer
Junde Wu, Rao Fu, Huihui Fang, Yu Zhang, Yanwu Xu
[19th Jan., 2023] [arXiv, 2023]
[Paper] [Github]

Improved HER2 Tumor Segmentation with Subtype Balancing using Deep Generative Networks
Mathias Öttl, Jana Mönius, Matthias Rübner, Carol I. Geppert, Jingna Qiu, Frauke Wilm, Arndt Hartmann, Matthias W. Beckmann, Peter A. Fasching, Andreas Maier, Ramona Erber, Katharina Breininger
[11th Nov., 2022] [ISBI, 2023]
[Paper]

MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model
Junde Wu, Huihui Fang, Yu Zhang, Yehui Yang, Yanwu Xu
[1st Nov., 2022] [MIDL, 2023]
[Paper] [Github]

Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation
Xutao Guo, Yanwu Yang, Chenfei Ye, Shang Lu, Yang Xiang, Ting Ma
[27th Oct., 2022] [ISBI, 2023]
[Paper]

Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation
Boah Kim, Yujin Oh, Jong Chul Ye
[19th Sep., 2022] [ICLR, 2023]
[Paper]

Can segmentation models be trained with fully synthetically generated data?
Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Petru-Daniel Tudosiu, Mark S Graham, Tom Vercauteren, M Jorge Cardoso
[17th Sep., 2022] [MICCAI Workshop, 2022]
[Paper]

Diffusion Models for Implicit Image Segmentation Ensembles
Julia Wolleb, Robin Sandkühler, Florentin Bieder, Philippe Valmaggia, Philippe C. Cattin
[6th Dec., 2021] [MIDL, 2022]
[Paper] [Github]

Image-to-Image Translation

Benchmarking GANs, Diffusion Models, and Flow Matching for T1w-to-T2w MRI Translation
Andrea Moschetto, Lemuel Puglisi, Alec Sargood, Pierluigi Dell'Acqua, Francesco Guarnera, Sebastiano Battiato, Daniele Ravì
[19th Jul., 2025] [arXiv, 2025]
[Paper] [Github]

Human-Guided Shade Artifact Suppression in CBCT-to-MDCT Translation via Schrödinger Bridge with Conditional Diffusion
Sung Ho Kang, Hyun-Cheol Park
[15th Jul., 2025] [arXiv, 2025]
[Paper]

Regression is all you need for medical image translation
Sebastian Rassmann, David Kügler, Christian Ewert, Martin Reuter
[04th May, 2025] [arXiv, 2025]
[Paper]

Diffusion Bridge Models for 3D Medical Image Translation
Shaorong Zhang, Tamoghna Chattopadhyay, Sophia I. Thomopoulos, Jose-Luis Ambite, Paul M. Thompson, Greg Ver Steeg
[21st Apr., 2025] [arXiv, 2025]
[Paper]

Structure-Accurate Medical Image Translation via Dynamic Frequency Balance and Knowledge Guidance
Jiahua Xu, Dawei Zhou, Lei Hu, Zaiyi Liu, Nannan Wang, Xinbo Gao
[13th Apr., 2025] [arXiv, 2025]
[Paper]

seg2med: a bridge from artificial anatomy to multimodal medical images
Zeyu Yang, Zhilin Chen, Yipeng Sun, Anika Strittmatter, Anish Raj, Ahmad Allababidi, Johann S. Rink, Frank G. Zöllner
[12th Apr., 2025] [arXiv, 2025]
[Paper]

Translation of Fetal Brain Ultrasound Images into Pseudo-MRI Images using Artificial Intelligence
Naomi Silverstein, Efrat Leibowitz, Ron Beloosesky, Haim Azhari
[03rd Apr., 2025] [arXiv, 2025]
[Paper]

Deterministic Medical Image Translation via High-fidelity Brownian Bridges
Qisheng He, Nicholas Summerfield, Peiyong Wang, Carri Glide-Hurst, Ming Dong
[28th Mar., 2025] [CVPR, 2025]
[Paper]

VasTSD: Learning 3D Vascular Tree-state Space Diffusion Model for Angiography Synthesis
Zhifeng Wang, Renjiao Yi, Xin Wen, Chenyang Zhu, Kai Xu
[17th Mar., 2025] [CVPR, 2025]
[Paper] [GitHub]

Geodesic Diffusion Models for Medical Image-to-Image Generation
Teng Zhang, Hongxu Jiang, Kuang Gong, Wei Shao
[2nd Mar., 2025] [arXiv, 2025]
[Paper]

3D Shape-to-Image Brownian Bridge Diffusion for Brain MRI Synthesis from Cortical Surfaces
Fabian Bongratz, Yitong Li, Sama Elbaroudy, Christian Wachinger
[18th Feb., 2025] [arXiv, 2025]
[Paper] [GitHub]

Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios
Ciaran Bench, Emir Ahmed, Spencer A. Thomas
[29th Jan., 2025] [IPMI, 2025]
[Paper]

Introducing 3D Representation for Medical Image Volume-to-Volume Translation via Score Fusion
Xiyue Zhu, Dou Hoon Kwark, Ruike Zhu, Kaiwen Hong, Yiqi Tao, Shirui Luo, Yudu Li, Zhi-Pei Liang, Volodymyr Kindratenko
[13th Jan., 2025] [ICML, 2025]
[Paper] [Project Page]

Multi-Subject Image Synthesis as a Generative Prior for Single-Subject PET Image Reconstruction
George Webber, Yuya Mizuno, Oliver D. Howes, Alexander Hammers, Andrew P. King, Andrew J. Reader
[05th Dec., 2024] [IEEE Symposium on Nuclear Science (NSS/MIC), 2024]
[Paper]

Cross-conditioned Diffusion Model for Medical Image to Image Translation Zhaohu Xing, Sicheng Yang, Sixiang Chen, Tian Ye, Yijun Yang, Jing Qin, Lei Zhu [12th Sep., 2024] [MICCAI, 2024] [Paper]

Bi-modality medical images synthesis by a bi-directional discrete process matching method
Zhe Xiong, Qiaoqiao Ding, Xiaoqun Zhang
[06th Sep., 2024] [arXiv, 2024]
[Paper]

Slice-Consistent 3D Volumetric Brain CT-to-MRI Translation with 2D Brownian Bridge Diffusion Model
Kyobin Choo, Youngjun Jun, Mijin Yun, Seong Jae Hwang
[6th Jul., 2024] [MICCAI, 2024]
[Paper] [GitHub]

Soft Masked Mamba Diffusion Model for CT to MRI Conversion
Zhenbin Wang, Lei Zhang, Lituan Wang, Zhenwei Zhang
[22nd Jun., 2024] [arXiv, 2024]
[Paper] [GitHub]

2.5D Multi-view Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-count PET Reconstruction with CT-less Attenuation Correction
Tianqi Chen, Jun Hou, Yinchi Zhou, Huidong Xie, Xiongchao Chen, Qiong Liu, Xueqi Guo, Menghua Xia, James S. Duncan, Chi Liu, Bo Zhou
[12th Jun., 2024] [arXiv, 2024]
[Paper]

Similarity-aware Syncretic Latent Diffusion Model for Medical Image Translation with Representation Learning
Tingyi Lin, Pengju Lyu, Jie Zhang, Yuqing Wang, Cheng Wang, Jianjun Zhu
[19th Jun., 2024] [arXiv, 2024]
[Paper]

Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation
Hongxu Jiang, Muhammad Imran, Linhai Ma, Teng Zhang, Yuyin Zhou, Muxuan Liang, Kuang Gong, Wei Shao
[23rd May, 2024] [arXiv, 2024]
[Paper] [GitHub]

Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation
Yinchi Zhou, Tianqi Chen, Jun Hou, Huidong Xie, Nicha C. Dvornek, S. Kevin Zhou, David L. Wilson, James S. Duncan, Chi Liu, Bo Zhou
[5th Apr., 2024] [MedIA, 2024]
[Paper]

Diffusion based Zero-shot Medical Image-to-Image Translation for Cross Modality Segmentation
Zihao Wang, Yingyu Yang, Yuzhou Chen, Tingting Yuan, Maxime Sermesant, Herve Delingette, Ona Wu
[1st Apr., 2024] [arXiv, 2024]
[Paper]

Self-Consistent Recursive Diffusion Bridge for Medical Image Translation
Fuat Arslan, Bilal Kabas, Onat Dalmaz, Muzaffer Ozbey, Tolga Çukur
[10th May, 2024] [arXiv, 2024]
[Paper] [GitHub]

Tackling Structural Hallucination in Image Translation with Local Diffusion
Seunghoi Kim, Chen Jin, Tom Diethe, Matteo Figini, Henry F. J. Tregidgo, Asher Mullokandov, Philip Teare, Daniel C. Alexander
[9th Apr., 2024] [arXiv, 2024]
[Paper]

Mitigating analytical variability in fMRI results with style transfer
Elodie Germani, Elisa Fromont, Camille Maumet
[4th Apr., 2024] [arXiv, 2024]
[Paper]

ContourDiff: Unpaired Image Translation with Contour-Guided Diffusion Models
Yuwen Chen, Nicholas Konz, Hanxue Gu, Haoyu Dong, Yaqian Chen, Lin Li, Jisoo Lee, Maciej A. Mazurowski
[16th Mar., 2024] [arXiv, 2024]
[Paper]

FDDM: Unsupervised Medical Image Translation with a Frequency-Decoupled Diffusion Model
Yunxiang Li, Hua-Chieh Shao, Xiaoxue Qian, You Zhang
[19th Nov., 2023] [arXiv, 2023]
[Paper]

Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study
Jonghun Kim, Hyunjin Park
[1st Nov., 2023] [WACV, 2024]
[Paper] [Github]

Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis
Shaoyan Pan, Chih-Wei Chang, Junbo Peng, Jiahan Zhang, Richard L.J. Qiu, Tonghe Wang, Justin Roper, Tian Liu, Hui Mao, Xiaofeng Yang
[28th Apr., 2023] [arXiv, 2023]
[Paper]

Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models
Yunxiang Li, Hua-Chieh Shao, Xiao Liang, Liyuan Chen, Ruiqi Li, Steve Jiang, Jing Wang, You Zhang
[5th Apr., 2023] [arXiv, 2023]
[Paper] [Github]

Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels
Jan Oscar Cross-Zamirski, Praveen Anand, Guy Williams, Elizabeth Mouchet, Yinhai Wang, Carola-Bibiane Schönlieb
[15th Mar., 2023] [arXiv, 2023]
[Paper] [Github]

Diffusion Models for Contrast Harmonization of Magnetic Resonance Images
Alicia Durrer, Julia Wolleb, Florentin Bieder, Tim Sinnecker, Matthias Weigel, Robin Sandkühler, Cristina Granziera, Özgür Yaldizli, Philippe C. Cattin
[14th Mar., 2023] [MIDL, 2023]
[Paper]

Zero-shot-Learning Cross-Modality Data Translation Through Mutual Information Guided Stochastic Diffusion
Zihao Wang, Yingyu Yang, Maxime Sermesant, Hervé Delingette, Ona Wu
[31st Jan., 2023] [arXiv, 2023]
[Paper]

Brain PET Synthesis from MRI Using Joint Probability Distribution of Diffusion Model at Ultrahigh Fields
Xie Taofeng, Cao Chentao, Cui Zhuoxu, Li Fanshi, Wei Zidong, Zhu Yanjie, Li Ye, Liang Dong, Jin Qiyu, Chen Guoqing, Wang Haifeng
[16th Nov., 2022] [arXiv, 2022]
[Paper]

Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models
Qing Lyu, Ge Wang
[24th Sep., 2022] [arXiv, 2022]
[Paper]

Unsupervised Medical Image Translation with Adversarial Diffusion Models \