Medical Image Representation Learning

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20 papers in the last four weeks, up 233% on the four weeks before. 0.2% of all new papers.

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Metadata Supervised Imaging Representations for Modelling and Controlling Acquisition Variability
Jul 13, 2026Mehmet Yigit Avci, Pedro Borges, Virginia Fernandez +5Disentangled Representation Learning Medical Image Analysis
School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK. · University College London, London, UK. · deepc GMBH, Munich, Germany.
Learning Anatomy-Grounded CT Vision-Language Representations with Organ-Hierarchical Report Knowledge
Jul 12, 2026Guoliang You, Hongming Li, Yuanwang Zhang +1Radiology VLMs Medical VLMs
Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA · School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
Contrastive Joint-Embedding Prediction for Representation Learning in Structural MRI
Jul 12, 2026Fabian Mager, Lars Kai HansenContrastive Learning Brain Age Prediction
Department of Applied Mathematics and Computer Science Technical University of Denmark
TVT-PAPD: Pathology-Aware Prototype Distillation for Self-Supervised Whole Slide Image Classification
Jul 11, 2026Ramesh Naidu Laveti, Jaya Sreevalsan-Nair, T K SrikanthPrototype Learning Histopathology Image Classification
E-Health Research Center, International Institute of Information Technology Bangalore, Karnataka 560100, India.
CHM-Net: Center Heatmap-driven Macro-Micro Modeling Network for MRI-based Microbial Density Stratification
Jul 10, 2026Jiaming Liang, Haolin Chen, Tingting Li +7Medical Image Classification Medical Image Representation Learning
School of Computer Science and Engineering South China University of Technology Guangzhou, China · School of Future Technology South China University of Technology Guangzhou, China · Department of Medical Imaging Affiliated Cancer Hospital, Guangzhou Medical University Guangzhou, China
Progression as Latent Drift: Generative Forecasting of Slow-Evolving Pathologies
Jul 9, 2026Yuxiang Feng, Juncheng Wang, Chao Xu +7Latent Dynamics Modeling Longitudinal Medical Image Analysis
Zhejiang University, Hangzhou, China · IROOTECH TECHNOLOGY, China · The Hong Kong Polytechnic University, Hong Kong, China +1
ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification
Jul 9, 2026Anna Jung, Kyeonghun Kim, Youngung Han +6Computational Pathology Masked Autoencoders
SNU · OUTTA · GIST +1
VCDP: Variation-Conditioned Distributional Proxy Learning for Semi-Supervised Medical Image Segmentation
Jul 8, 2026Zimu Zhang, Yiheng Zhong, Zhuoru Zhang +4Prototype Learning Semi-Supervised Medical Image Segmentation
2Xi’an Jiaotong-Liverpool University, China · 1Yale University, United States
SHTA: Semantic Hard Token Correction and Center Alignment for Semi-Supervised Medical Image Segmentation
Jul 8, 2026Zhuoru Zhang, Yiheng Zhong, Zimu Zhang +1Semi-Supervised Medical Image Segmentation Medical Image Representation Learning
Xi’an Jiaotong-Liverpool University, China · Yale University, United States
KOAL: Knowledge-Driven Prostate Cancer Grading with Ordinal-Aware Learning
Jul 7, 2026Zheng Guo, Jiaqi Cui, Haocheng Xiong +5Medical Image Classification Ordinal Regression
School of Computer Science, Sichuan University, China · China Mobile (Suzhou) Software Technology Company Limited, China · Shanghai Changhai Hospital, Naval Medical University, China +1
Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction
Jul 6, 2026Johannes Kiechle, Richard Osuala, Daniel M. Lang +5Graph Representation Learning 3D Medical Imaging
Technical University of Munich · TUM University Hospital Rechts der Isar · Helmholtz Munich +4
HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopy
Jul 5, 2026Julius Riel, Vishwa Mohan Singh, Sai Anirudh Aryasomayajula +10Contrastive Learning Hierarchical Representation Learning
TUM.ai, Munich, Germany · Ludwig-Maximilian-University, Munich, Germany · Technical University of Munich, Munich, Germany +6
NeuroBridge: Bridging Multi-Task MRI Knowledge for Neurodegenerative Disease Diagnosis
Jul 1, 2026Mengyu Li, Guoyao Shen, Chad W. Farris +1Alzheimer's Disease Medical Diagnosis
Department of Mechanical Engineering, Boston University, Boston, MA 02215, United States · The Photonics Center, Boston University, Boston, MA 02215, United States · Rafik B. Hariri Institute for Computing and Computational Science & Engineering, Boston University, Boston, MA, 02215, United States +5
Mirror-Fusion Attention for Reflection-Aware Self-Supervised Representation Learning
Jul 1, 2026Ruixin Li, Jin Liu, Yuling Shi +1Representation Learning Vision Transformer
Department of Computer Science and Engineering, University of Bologna, Bologna, Italy · Jilin University, Changchun, China · Shanghai Jiao Tong University, Shanghai, China
BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure
Jul 1, 2026Zijian Dong, Yi Lin, Ji Fang +3Disentangled Representation Learning Medical Imaging Foundation Models
National University of Singapore, Singapore
ReMAP-PET: Beyond Visual Understanding -- Learning Region-Guided Metabolic Alignment Semantics from Brain PET
Jun 28, 2026Dasen Dai, Yanteng Zhang, Shuoqi Li +6Representation Learning PET/CT Imaging
The Chinese University of Hong Kong, HKSAR · TReNDS Center (Georgia State, Georgia Tech, Emory), Atlanta, USA · ShanghaiTech University, Shanghai, P.R.China +3
Learning from Acquisition: Metadata-driven Multimodal Pre-training for Cardiac MRI
Jun 27, 2026Xueyi Fu, Liwei Hu, Zi Wang +1Medical Image Segmentation Multimodal Contrastive Learning
Department of Surgery & Cancer, Imperial College London, London, UK · Bioengineering Department and Imperial-X, Imperial College London, London, UK · National Heart and Lung Institute, Imperial College London, London, UK +2
Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation
Jun 27, 2026Yishu Zhang, Shushan Wu, Zhenzhong Zhang +8Computational Pathology Pathology Foundation Models
University of North Carolina at Chapel Hill
Revealing Mammographic Phenotypes in Deep Learning Breast Cancer Risk Models
Jun 24, 2026Ruiyu Jia, Yanqi Xu, Yuxuan Chen +2Breast Cancer Medical Image Analysis
Department of Mathematics, New York University Shanghai, China · Center for Data Science, New York University, USA · Perlmutter Cancer Center, NYU Langone Health, New York, USA +1
Transformation Behavior of Images in Latent Space
Jun 23, 2026Christian Zöllner, Mozzam Motiwala, Aysel Ahadova +4Histopathology Image Classification Invariant Representation Learning
Department of Applied Tumor Biology Institute of Pathology Heidelberg University Hospital · Department of Applied Tumor Biology, Institute of Pathology, Heidelberg University Hospital, Im Neuenheimer Feld 224, 69120, Heidelberg, Germany · National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany +5
A Dual Edge Spatial Jacobian Image Graph for Interpretable Diabetic Retinopathy Grading
Jun 23, 2026Inam Ullah, Imran Razzak, Shoaib JameelGraph Representation Learning Diabetic Retinopathy Grading
University of Southampton Southampton, United Kingdom · Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi, United Arab Emirates
BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation
Jun 17, 2026Max Van Puyvelde, Ibrahim Gulluk, Wim Van Criekinge +1Masked Autoencoders Latent Diffusion Models
Department of Biomedical Data Science, Stanford University School of Medicine · Department of Mathematical Modelling, Statistics & Bioinformatics, Ghent University · Department of Electrical Engineering, Stanford University
REVEAL++: Differentiable Phenotypic Grouping for Vision-Language Retinal Modeling of Alzheimer's Disease Risk
Jun 17, 2026Ethan Elio Meidinger, Seowung Leem, Zeyun Zhao +1Contrastive Learning Medical Image Analysis
University of Virginia, Charlottesville, VA, USA · J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
Deep Image Prototype Learning with Geometric Heat-Kernel Priors
Jun 17, 2026Jiarui Xing, Tal Zeevi, Nian Wu +1Medical Image Analysis Prototype Learning
Yale School of Medicine, New Haven CT, 06510, USA · University of Virginia, Charlottesville, VA, 22903, USA · Harvard Medical School, Boston MA, 02115, USA
Recover Semantics First, Generate Better: Improved Latent Modeling for 3D MRI Reconstruction and Cross-Contrast Synthesis
Jun 16, 2026Yonghao Chen, Sicheng Yang, Rui Tang +13D Medical Imaging Magnetic Resonance Imaging
The Hong Kong University of Science and Technology (Guangzhou) · Xi’an Jiaotong University
Geometry-Consistent Endoscopic Representations for Image-Guided Navigation via Structured Foundation Model Adaptation
Jun 15, 2026Hongchao Shu, Roger D. Soberanis-Mukul, Hao Ding +5Endoscopy Monocular Depth Estimation
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21211 USA · Semaphor Surgical · Johnson & Johnson MedTech, Santa Clara, CA 95054 USA
Phenotyping TPF via Self-Supervised Learning: A Label-Agnostic Framework with Expert Validation
Jun 15, 2026Miral Elnakib, Muhammad Saad, Ahmad Al-KabbanySelf-Supervised Learning Medical Image Analysis
Faculty of Sciences Alexandria University · Multimedia Interaction and Communication Lab Wearables, Biosensing, and Biosignal Processing Research Lab Arab Academy for Science and Technology
Landmark-free Assessment of Lower-limb Alignment with Implicit Neural Shape Functions from Knee Radiographs
Jun 13, 2026Zhisen Hu, Antti Kemppainen, David Johnson +5Medical Image Analysis Medical Image Representation Learning
Division of Informatics, Imaging and Data Sciences, The University of Manchester, United Kingdom · Research Unit of Health Sciences and Technology, University of Oulu, Finland · Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Finland +4
EyeMVP: OCT-Informed Fundus Representation Learning via Paired CFP--OCT Pretraining
Jun 13, 2026Zhuo Deng, Ruiheng Zhang, Ziheng Zhang +23Medical Imaging Foundation Models Cross-Modal Representation Learning
Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China · Liangxiang Hospital of Beijing Fangshan District, Capital Medical University, Beijing, China +6
OpenMedQ: Broad Open Pretraining for Medical Vision-Language Models
Jun 11, 2026Ibrahim Gulluk, Max Van Puyvelde, Olivier GevaertMedical VQA Medical Image Classification
Department of Electrical Engineering, Stanford University · Department of Biomedical Data Science, Stanford University School of Medicine · Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University

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Metadata Supervised Imaging Representations for Modelling and Controlling Acquisition Variability

Mehmet Yigit Avci, Pedro Borges, Virginia Fernandez, Natalia Glazman+4

School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK. · University College London, London, UK. · deepc GMBH, Munich, Germany.

Disentangled Representation Learning Medical Image Analysis Magnetic Resonance Imaging Medical Image Synthesis Medical Image Representation Learning

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Biomedical imaging data exhibit substantial acquisition variability, where identical biological structures can appear markedly different due to differences in imaging devices, acquisition protocols, sites, and reconstruction settings. Consequently, learned representations often entangle underlying biological information with acquisition-dependent appearance, limiting interpretability, generalisation, and clinical deployment. We show that these sources of variation can be disentangled by jointly modelling medical images and acquisition metadata. Using large-scale clinical brain MRI data as a case study, we learn representations that disentangle anatomical structure from contrast-dependent appearance. The resulting framework enables the organisation of heterogeneous imaging protocols, sequence understanding, the detection of image-metadata inconsistencies and imaging artifacts, while preserving biologically relevant anatomical features across diverse acquisitions. Building on these disentangled representations, it further supports generative and translational capabilities, performing both metadata-conditioned synthesis of realistic 3D brain MRIs and anatomy-preserving harmonisation for cross-modality and cross-site adaptation. Our findings demonstrate that acquisition variability is a structured component of the imaging process that can be modeled, audited, synthesised, and controlled, establishing a foundation for acquisition-aware representation learning in large-scale biomedical imaging.

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