Medical Image Synthesis

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25 papers in the last four weeks, up 92% on the four weeks before. 0.2% of all new papers.

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Latest papers 185

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A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgery
May 30, 2026Olga Esteban-Sinovas, Santiago Cepeda, Ignacio Arrese +1Ultrasound Imaging Medical Image Synthesis
Department of Neurosurgery, Neurovascular Unit Río Hortega University Hospital, Valladolid, Spain · Specialized Group in Biomedical Imaging and Computational Analysis (GEIBAC) Instituto de Investigación Biosanitaria de Valladolid (IBioVALL), Valladolid, Spain
Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generation
May 29, 2026Qi Chen, Shuhan Ding, Yu Gu +5Variational Autoencoders Medical Imaging Foundation Models
Department of Computer Science, Johns Hopkins University · 2Duke-NUS Medical School · 3Microsoft Research
Controllable Lung Nodule Synthesis via Histogram-Regularized Latent Diffusion Models
May 28, 2026Arunkumar Kannan, Yanbo Zhang, Han Liu +5Synthetic Data Augmentation Latent Diffusion Models
aDigital Technology and Innovation, Siemens Healthineers, Princeton, NJ, USA · bJohns Hopkins University, Baltimore, MD, USA · cDigital Technology and Innovation, Siemens Healthineers, Erlangen, Germany +1
Treatment-Conditioned Diffusion for Forecasting Neurodegenerative Disease Progression
May 28, 2026Danylo Boiko, Viktoriia MishkurovaLongitudinal Medical Image Analysis Clinical Outcome Prediction
Innoloft Inc. 701 Brazos Street, Austin, TX 78701, USA · Bogomolets National Medical University Beresteiskyi Avenue, 34, Kyiv, 03057, Ukraine
A unified deeplearning framework for contrast-phase-specific virtual monochromatic imaging
May 28, 2026Antony Jerald, Hemant K Aggarwal, Brian Nett +4Conditional Image Generation Image Reconstruction
Science and Technology Organization, GE HealthCare, Bangalore, INDIA · CT Engineering, GE HealthCare, Waukesha, USA · Science and Technology Organization, GE HealthCare, San Ramon, USA +1
DefSynUS: Real-time Patient-specific Intrahepatic Vessel Identification via Deformation-Aware CT-US Domain Adaptation
May 28, 2026Karl-Philippe Beaudet, Yordanka Velikova, Sidaty El Hadramy +4Synthetic-to-Real Domain Adaptation Data Augmentation
MIMESIS, UNISTRA · Inria, Strasbourg, France. · TUM +7
Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?
May 27, 2026Thierry Judge, Nicolas Duchateau, Andreas Østvik +13Medical Image Analysis Echocardiography
Dept. of Computer Science, University of Sherbrooke, Sherbrooke, Canada · INSA, Universit´e Lyon 1, CNRS UMR 5220, Inserm U1206, CREATIS, Villeurbanne, France · Institut Universitaire de France (IUF) +7
Enhancing Ultra-low-field MRI with Segmentation-guided Adversarial Learning
May 27, 2026James Grover, Andrew Phair, Michael Ferraro +1Image Enhancement Magnetic Resonance Imaging
Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney
VDSB-GWSyn: Diffusion Schrödinger Bridge for Controllable and Anatomically Feasible Guidewire Synthesis in Coronary Angiography
May 27, 2026Haoyuan Tang, Zhuo Zhang, Jialin Li +2Medical Imaging Coronary Angiography
Tianjin University, Tianjin, China
FM-fMRI: Event Conditioned Flow Matching for Rest-to-Task fMRI Time-Series Synthesis
May 26, 2026Peiyu Duan, Jiyao Wang, Nicha C. Dvornek +4Flow Matching Synthetic Data Generation
Department of Biomedical Engineering, Yale University, New Haven, CT, USA · Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA · Department of Electrical Engineering, Yale University, New Haven, CT, USA
SAFE-Diff: Scale-Aware Attention and Feature-Dispersive Diffusion with Uncertainty Estimation for Contrast-Enhanced Breast MRI Synthesis
May 25, 2026Tianyu Zhang, Xinglong Liang, Jarek van Dijk +13Magnetic Resonance Imaging Medical Image Synthesis
Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands · Department of Radiology, Netherlands Cancer Institute, Plesmanlaan 121, 1066May CX, Amsterdam, The Netherlands · Maastro Clinic, Dr. Tanslaan 12, 6229 ET, Maastricht, The Netherlands +2
Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering
May 24, 2026Ojonugwa Oluwafemi Ejiga Peter, Frederick Akor Ejiga, Fahmi Khalifa +1Endoscopy Medical Imaging
Computer Science Department, Morgan State University, Baltimore, USA. · International Organization for Migration (IOM), Geneva, Switzerland. · Electrical & Computer Engineering Department, Morgan State University, Baltimore, USA.
ULF-Synth: Physics-Guided Ultra-Low-Field MRI Enhancement for Pediatric Neuroimaging
May 23, 2026Toufiq Musah, Salvatore Calcagno, Federica Proietto Salanitri +3Medical Image Super-Resolution Magnetic Resonance Imaging
Kwame Nkrumah University of Science and Technology, Kumasi, Ghana · University of Catania, Catania, Italy · The Hong Kong University of Science and Technology, Hong Kong SAR, China +1
GMENet: Generative Mixture of Experts Network for Multi-Center Glioma Diagnosis with Incomplete Imaging Sequences
May 22, 2026Pengfei Song, Fangjin Liu, Wenwen Zeng +5Missing-Modality Learning Medical Diagnosis
School of Biomedical Engineering and Technology Innovation, Fudan University · Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University · 3Intelligent Diagnosis and Treatment Laboratory for Brain Diseases, Joint Laboratory of Neurosurgery Department of Huashan Hospital and School of Information Science and Technology, Fudan University
Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025
May 21, 2026José Rafael Noriega CedeñoSynthetic Data Augmentation Medical Image Classification
Faculty of Applied Sciences and Technology
From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder
May 21, 2026Yilin Zhang, Nicholas C. Harvey, Nicholas R. Fuggle +1Medical Imaging Image Generation
School of Electronics and Computer Science University of Southampton Southampton, UK · MRC Lifecourse Epidemiology Centre University of Southampton, Southampton General Hospital Southampton, UK
MRecover: A Conditional Generative Model for Recovering Motion-Corrupted MR images Using AI Generated Contrast
May 20, 2026Jinghang Li, Tales Santini, Courtney Clark +13Conditional Image Generation Magnetic Resonance Imaging
Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA · School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA · Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA +1
RePCM: Region-Specific and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis
May 20, 2026Xuan Yang, Xiaohan Yuan, Hao Li +3Medical Image Synthesis
School of Biomedical Engineering, National University of Singapore, Singapore · School of Automation, Southeast University, Nanjing, China · School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China +1
EPC-3D-Diff: Equivariant Physics Consistent Conditional 3D Latent Diffusion for CBCT to CT Synthesis
May 19, 2026Alzahra Altalib, Chunhui Li, Haytham Ahmad Alewaidat +3Physics-Informed Diffusion Models Cone-Beam CT
School of Science and Engineering, University of Dundee UK · Faculty of Applied Medical Sciences, Jordan University of Science and Technology · Experia Healthcare, Jordan +1
Generation of Heterogeneous PET Images from Uniform Organ Activity Maps Using a Pretrained Domain-Adapted Diffusion Model
May 18, 2026Suya Li, Kaushik Dutta, Debojyoti Pal +2PET/CT Imaging Diffusion-Based Image Generation
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, USA · Imaging Science Program, McKelvey School of Engineering, Washington University in St Louis, St. Louis, USA · Department of Surgery, Washington University School of Medicine, St. Louis, USA +1
LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators
May 18, 2026Xinhe Zhang, Yuyang Zhang, Pengfei Jin +3Image-to-Image Translation Medical Image Synthesis
∗School of Engineering and Applied Sciences, Harvard University · ‡Kempner Institute, Harvard University · †Center for Advanced Medical Computing and Analysis, Massachusetts General Hospital and Harvard Medical School
Flow Matching with Optimized Subclass Priors for Medical Image Augmentation
May 15, 2026Felix Nützel, Mischa Dombrowski, Bernhard KainzFlow Matching Synthetic Data Augmentation
Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany · Department of Computing, Imperial College London, London SW7 2AZ, UK
SynVA: A Modular Toolkit for Vessel Generation and Aneurysm Editing
May 13, 2026Marten J. Finck, Niklas C. Koser, Sarker M. Mahfuz +73D Mesh Generation Synthetic Data Generation
Visual Computing and Artificial Intelligence, Kiel University, Germany · Institute for Medical Informatics and Statistics, Kiel University, Germany · Clinic for Neuroradiology, Medical Faculty, Magdeburg University, Germany +2
Cross Modality Image Translation In Medical Imaging Using Generative Frameworks
May 13, 2026Giulia Romoli, Filippo Ruffini, Francesco Di Feola +20Image-to-Image Translation Medical Image Synthesis
Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Universitetstorget, 4, Umeå, 90187, Sweden · Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, Roma, 00128, Italy · Università Cattolica del Sacro Cuore, Largo Francesco Vito, 1, Roma, 00168, Italy +12
Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report
May 13, 2026Viktor Rogowski, Maarten L. Terpstra, Niklas Wahl +30Cone-Beam CT Medical Image Synthesis
Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden · Medical Radiation Physics, Department of Clinical Sciences Lund, Lund University, Lund, Sweden · Radiotherapy Department, University Medical Center Utrecht, Utrecht, The Netherlands +20
A General Bézier Tree Encoding Counterfactual Framework for Retinal-Vessel-Mediated Disease Analysis
May 13, 2026Tan Su, Ethan Elio Meidinger, Lin Gu +1Medical Image Analysis Causal Counterfactual Generation
Department of Electronic and Electrical Engineering, Southern University of Science and Technology · School of Data Science,University of Virginia, Charlottesville · Research Institute of Electrical Communication, Tohoku University +1
CRAFT: Clinical Reward-Aligned Finetuning for Medical Image Synthesis
May 12, 2026Yunsung Chung, Alex El Darzi, Carlo El Khoury +3Diffusion Model Alignment Healthcare
Department of Computer Science, Tulane University, New Orleans, LA 70118 · School of Medicine, Tulane University, New Orleans, LA 70112
H3D-MarNet: Wavelet-Guided Dual-Path Learning for Metal Artifact Suppression and CT Modality Transformation for Radiotherapy Workflows
May 12, 2026Mubashara Rehman, Niki Martinel, Michele Avanzo +2Image Enhancement Image-to-Image Translation
Machine Learning and Perception Lab, Università degli Studi di Udine, 33100 Udine, Italy · Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy
When Brains Disagree: Biological Ambiguity Underlies the Challenge of Amyloid PET Synthesis from Structural MRI
May 12, 2026Louise E. G. Baron, Ross Callaghan, David M. Cash +3Alzheimer's Disease Medical Image Synthesis
Hawkes Institute, University College London, UK · Department of Medical Physics and Biomedical Engineering, University College London, UK · AINOSTICS Ltd, Manchester, UK +3
Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport
May 9, 2026Jialin Li, Zhuo Zhang, Yue Cao +4Synthetic Data Augmentation Medical Imaging
School of Electrical and Information Engineering, Tianjin University, Tianjin, China.

May 30, 2026, cs.CVJ/K move · Enter open · S save

A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgery

Olga Esteban-Sinovas, Santiago Cepeda, Ignacio Arrese, Rosario Sarabia

Department of Neurosurgery, Neurovascular Unit Río Hortega University Hospital, Valladolid, Spain · Specialized Group in Biomedical Imaging and Computational Analysis (GEIBAC) Instituto de Investigación Biosanitaria de Valladolid (IBioVALL), Valladolid, Spain

Ultrasound Imaging Medical Image Synthesis Medical Image Benchmarks

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Intraoperative ultrasound (ioUS) is a versatile, cost-effective modality in brain tumour surgery, but its interpretation is difficult: acquisition planes are non-standard, artefacts are modality-specific, and its appearance differs markedly from the preoperative MRI on which surgical-planning tools, segmentation models and the surgeon's experience rely. Synthesising MRI-like images from ioUS could let this MRI-based infrastructure be reused intraoperatively without an extra scan. Most prior work evaluates a single architecture in isolation; to our knowledge, no benchmark has spanned architectural paradigms, inference regimes and downstream-task endpoints under a common protocol. We address this gap on the public ReMIND data set (76 patients; 153 paired ioUS/T2w and 104 paired ioUS/FLAIR studies; 60/16 patient-level train/held-out split). Six generators (four GAN baselines: Pix2Pix, SwinPix2Pix, CycleGAN, CUT; the transformer-augmented ResViT; and the few-step diffusion model SynDiff) were each trained under four inference regimes (2D, 2.5D, 2D + 3D-refinement, full-3D) and two targets (T2w only; T2w + FLAIR multi-task), yielding 48 experiments. Image-fidelity metrics (SSIM, PSNR, MAE, LPIPS) were complemented by an nnU-Net v2 downstream segmentation evaluation (tumour and resection cavity) and by subgroup analyses by histological grade and reoperation. No architecture dominated every axis, and, critically, perceptual quality tracked downstream utility most closely (LPIPS, r=-0.66, p<0.001), whereas higher SSIM was associated with worse utility (r=-0.64, p<0.001); SynDiff-2.5D best preserved downstream segmentation (U_Dice=0.55). Perceptual and downstream-task metrics should therefore be reported alongside or in preference to global SSIM, and architecture choice conditioned on surgical phase, patient history and clinical objective.

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Latest papers 185