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ORCID5th DGM4MICCAI@MICCAI 2025: Daejeon, South Korea
- Anirban Mukhopadhyay
, Ilkay Öksüz, Sandy Engelhardt, Dorit Merhof, Yixuan Yuan:
Deep Generative Models - 5th MICCAI Workshop, DGM4MICCAI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings. Lecture Notes in Computer Science 16128, Springer 2026, ISBN 978-3-032-05471-5 - Raman Dutt:
The Devil is in the Prompts: De-identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray Generation. 1-11 - Lin Xi, YingLiang Ma, Cheng Wang, Sandra Howell, C. Aldo Rinaldi, Kawal S. Rhode:
Robust Noisy Pseudo-Label Learning for Semi-supervised Medical Image Segmentation Using Diffusion Model. 12-23 - Peng Zhang, Haowen Pang, Xinru Zhang, Xin Gao, Chenghao Liu, Xiaoming Hong, Runze Jiang, Yaou Liu, Chuyang Ye:
Unsupervised Brain Tumor Segmentation via Bi-Level Optimization Guided by Radiological Reports. 24-34 - Francisco Caetano, Lemar Abdi, Christiaan G. A. Viviers, M. M. Amaan Valiuddin, Fons van der Sommen:
MedSymmFlow: Bridging Generative Modeling and Classification in Medical Imaging Through Symmetrical Flow Matching. 35-45 - Pengwei Sun, Wei Peng, Lun Yu Li, Yixin Wang, Kilian M. Pohl:
Evaluation of 3D Counterfactual Brain MRI Generation. 46-56 - Changlu Guo, Anders Nymark Christensen, Morten Rieger Hannemose:
Med-Art: Diffusion Transformer for 2D Medical Text-to-Image Generation. 57-66 - Ana Lawry Aguila, Peirong Liu, Oula Puonti, Juan Eugenio Iglesias:
Conditional Diffusion Models for Guided Anomaly Detection in Brain MRI Using Fluid-Driven Anomaly Randomization. 67-77 - Dou Hoon Kwark, Shirui Luo, Xiyue Zhu, Yudu Li, Zhi-Pei Liang, Volodymyr V. Kindratenko:
Hierarchical Diffusion Framework for Pseudo-healthy Brain MRI Inpainting with Enhanced 3D Consistency. 78-88 - Mayssa Soussia, Yijun Lin, Mohamed Ali Mahjoub, Islem Rekik:
CogGNN: Cognitive Graph Neural Networks in Generative Connectomics. 89-98 - Gauthier Piat, Léa Gazeau, Thang Nguyen, Marwan Ajem, Pierre Gilibert, Zung Nguyen, Hang Nguyen:
ACNEDIT: Acne Creation and Non-Destructive Editing with Dynamic Intensity Tuning Using Deep Learning on Facial Images for Dermatological Application. 99-108 - Hongyou Zhou, Cederic Aßmann, Alaa Bejaoui, Heiko Tzschätzsch, Mark Heyland, Julian Zierke, Niklas Tuttle, Sebastian Hölzl, Timo Auer, David A. Back, Marc Toussaint:
Masked Registration and Autoencoding of CT Images for Predictive Tibia Reconstruction. 109-119 - Pascal Klöckner, José Teixeira, Diana Montezuma, Jaime S. Cardoso, Hugo M. Horlings, Sara Pires de Oliveira:
GANs vs. Diffusion Models for Virtual Staining with the HER2match Dataset. 120-130 - Evandros Kaklamanos, Kristjana Kristinsdottir, Jonathan Huang, Dustin A. Carlson, Rajesh Keswani, John E. Pandolfino, Mozziyar Etemadi:
From Scope to Script: An Automated Report Generation Model for Gastrointestinal Endoscopy. 131-140 - Sachin Kumar Danisetty, Alexandros Graikos, Srikar Yellapragada, Dimitris Samaras:
PathSegDiff: Pathology Segmentation Using Diffusion Model Representations. 141-150 - Shen Zhu, Yinzhu Jin, Tyler A. Spears, Ifrah Zawar, P. Thomas Fletcher:
RealDeal: Enhancing Realism and Details in Brain Image Generation via Image-to-Image Diffusion Models. 151-160 - Ashay Patel, Michela Antonelli, Sébastien Ourselin, M. Jorge Cardoso:
Resolution Invariant Autoencoder. 161-170 - Alicia Durrer, Florentin Bieder, Paul Friedrich, Bjoern H. Menze, Philippe C. Cattin, Florian Kofler:
fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting. 171-181 - Alexandre G. Leclercq, Sébastien Bougleux, Noémie N. Moreau, Alexis Desmonts, Romain Hérault, Aurélien Corroyer-Dulmont:
Pre to Post-treatment Glioblastoma MRI Prediction Using a Latent Diffusion Model. 182-191 - Wei Peng, Tian Xia, Fabio De Sousa Ribeiro, Tomas M. Bosschieter, Ehsan Adeli, Qingyu Zhao, Ben Glocker, Kilian M. Pohl:
Latent Causal Modeling for 3D Brain MRI Counterfactuals. 192-201 - José Teixeira, Pascal Klöckner, Diana Montezuma, Melis Erdal Cesur, João Fraga, Hugo M. Horlings, Jaime S. Cardoso, Sara Pires de Oliveira:
Leveraging Adversarial Learning for Pathological Fidelity in Virtual Staining. 202-212 - Junde Wu, Renee Miller, Jurica Sprem, Vicente Grau:
EchoAdapter: Adapting Pretrained Image Diffusion Models for Cardiac Ultrasound Video Generation. 213-222 - Janluka Janelidze, Lukas Folle, Nassir Navab, Mohammad Farid Azampour:
Tubular Anatomy-Aware 3D Semantically Conditioned Image Synthesis. 223-232 - Zaixin Ou, Caiwen Jiang, Yuxiao Liu, Kaicong Sun, Dinggang Shen:
Uncovering Aβ Accumulation Patterns via Multi-modal Latent Space Clustering Using Residual Diffusion Model. 233-243 - Susanne Schaub, Florentin Bieder, Matheus L. Oliveira, Yulan Wang, Dorothea Dagassan-Berndt, Michael M. Bornstein, Philippe C. Cattin:
3D CBCT Artefact Removal Using Perpendicular Score-Based Diffusion Models. 244-253 - Hugues Roy, Reuben Dorent, Ninon Burgos:
Unsupervised Anomaly Detection Using Bayesian Flow Networks: Application to Brain FDG PET in the Context of Alzheimer's Disease. 254-264 - Niklas Bubeck, Yundi Zhang, Suprosanna Shit, Daniel Rueckert, Jiazhen Pan:
Reconstruct or Generate: Exploring the Spectrum of Generative Modeling for Cardiac MRI. 265-276 - Zahra Tehraninasab, Hujun Ni, Amar Kumar, Tal Arbel:
Pixel Perfect MegaMed: A Megapixel-Scale Vision-Language Foundation Model for Generating High Resolution Medical Images. 277-287 - Claudia L. Giardina, Sigrid Vila-Bagaria, Carlos Albornés, Montse Pardàs, Verónica Vilaplana:
Anatomically Guided 3D Diffusion Models for Synthetic Prostate MRI Generation. 288-297 - Xinkai Zhao, Yuta Tokuoka, Junichiro Iwasawa, Keita Oda:
Frequency-Calibrated Membership Inference Attacks on Medical Image Diffusion Models. 298-307 - Zhenshan Xie, Levente Baljer, M. Jorge Cardoso, Emma C. Robinson:
Controllable Surface Diffusion Generative Model for Neurodevelopmental Trajectories. 308-318 - Rayan Albokhari, Bappaditya Debnath, Darrien Henry, Michael Johnson, Adam Bailey, James E. East, Jens Rittscher:
CtrlEndoDiff: Diffusion-Based Synthetic Image Generation for Enhanced ACF Segmentation. 319-329 - Tyler A. Spears, Shen Zhu, Yinzhu Jin, Aman Shrivastava, P. Thomas Fletcher:
MedIL: Generating Arbitrary-Resolution Medical Images with Implicit Latent Spaces. 330-340 - Ridvan Yesiloglu, Wei Peng, Md Tauhidul Islam, Ehsan Adeli:
Neural Autoregressive Modeling of Brain Aging. 341-350
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