Longitudinal Medical Image Analysis

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10 papers in the last four weeks, up 67% on the four weeks before. 0.1% of all new papers.

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Patient, Place, Prior (P $^3$ ): What Counts as Personalization in Medical World Models?
Oct 6, 2026Xingrui Gu, Hanxue Gu, Yuxiang Zhang +1Longitudinal Medical Image Analysis Predictive Representation Learning
University of California, Berkeley · University of California, San Francisco · Southern Methodist University
RT-Super: Learning Tumor Segmentation from Longitudinal Images and Reports
Sep 28, 2026Pedro R. A. S. Bassi, Wenxuan Li, Hanxue Gu +11Weakly Supervised Image Segmentation Longitudinal Medical Image Analysis
Johns Hopkins University · Harvard Medical School · Massachusetts General Hospital +4
Clinical Trajectory Alignment for Medical Vision-Language Pre-training
Sep 28, 2026Huimin Yan, Xian Yang, Zhi Wang +1Multimodal Pretraining Longitudinal Medical Image Analysis
Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China · Alliance Manchester Business School, The University of Manchester, Manchester, UK
Is your uncertainty map wrong, or is its target? Exact diagnostics for the Tweedie diagonal, and a gradient-free alternative
Sep 27, 2026Vicent Ribas, Anna Oliveras TousUncertainty Quantification Bayesian Inference
Eurecat · University of Barcelona
Foundation model embeddings capture pre-diagnostic changes on screening mammograms
Sep 22, 2026Kalina P. Slavkova, Eric Brattain, Aditya Gowd +6Breast Cancer Medical Imaging Foundation Models
HOPPR, Chicago, IL, USA · University of Utah School of Medicine, Salt Lake City, UT, USA · 4DMedical, Woodland Hills, CA, USA +1
MUMINS: Metadata-conditioned Uncertainty-aware Medical Image Next-state Synthesis
Sep 15, 2026Anna Oliveras, Roger Marí, Rafael Redondo +7Medical Image Analysis Longitudinal Medical Image Analysis
Eurecat, Centre Tecnol`ogic de Catalunya, Barcelona, Spain · Dept. de Matem`atiques i Inform`atica, Universitat de Barcelona, Barcelona, Spain · Barcelona Supercomputing Center (BSC), Barcelona, Spain +1
Temporally Consistent Graph Extraction and Matching for Longitudinal Angiographic Images
Sep 15, 2026Linus Kreitner, Laurin Lux, Carmen Baumann +2Longitudinal Medical Image Analysis Graph Matching
Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany · Ophthalmology, Technical University of Munich, Munich, Germany +1
Observation-Anchored Selective Assimilation for Longitudinal Tumor-State Proxy Forecasting in Post-Treatment Glioma
Sep 14, 2026Yeonjae Jung, Minwoo ShinTime Series Forecasting Longitudinal Medical Image Analysis
Department of Software, Yonsei University, Wonju, 26493, Republic of Korea
Self-supervised Pre-training Helps Retinal Disease Progression Modelling Most When Data Is Scarce
Sep 14, 2026Ifeoma Veronica Nwabufo, Julius Gervelmeyer, Sarah Müller +1Self-Supervised Pre-Training Longitudinal Medical Image Analysis
Hertie Institute for AI in Brain Health, Faculty of Medicine, University of Tübingen, Germany · Tübingen AI Center, University of Tübingen, Germany
Brain-PACE: A Deep Siamese MRI Framework for Modelling Longitudinal Brain Acceleration
Sep 11, 2026Samuel Maddox (School of Computing Sciences, University of East Anglia), Jacob Newman (School of Computing Sciences +8Alzheimer's Disease Brain Age Prediction
School of Computing Sciences, University of East Anglia Norwich Research Park, Norwich, NR4 7TJ, UK · Norwich Medical School, University of East Anglia Norwich Research Park, Norwich, NR4 7TJ, UK
Longitudinal tracking of multiple sclerosis lesions in the spinal cord: A validation study
Sep 8, 2026Pierre-Louis Benveniste, Julian McGinnis, Shannon Kolind +11Longitudinal Medical Image Analysis Neuroimaging
Polytechnique Montreal, Montreal, QC, Canada · TUM University Hospital, Munich, Germany · University of British Columbia, Vancouver, BC, Canada +4
Tensor-based Brain Surface Modeling and Analysis
Sep 3, 2026Moo K. Chung, Keith J. Worsley, Steve Robbins +1Medical Image Analysis Longitudinal Medical Image Analysis
Department of Statistics, Department of Biostatistics and Medical Informatics Keck Laboratory for Functional Brain Imaging and Behavior University of Wisconsin-Madison Madison, WI 53706. USA · Montreal Neurological Institute, McGill University, Canada
BrainDiff: Longitudinal Report Generation for Multimodal Brain MRI
Sep 1, 2026Krish Patel, Peirong LiuRadiology Report Generation Longitudinal Medical Image Analysis
Department of Electrical and Computer Engineering, Data Science and AI Institute, Johns Hopkins University
CheXGround: Anatomical Region Tokens for Grounded Longitudinal Chest X-ray Interpretation
Aug 31, 2026Adonay Demewez Gebremedhin, Wessam Shehieb, Sara Alansari +4Radiology Report Generation Radiology VLMs
Ajman University Ajman, United Arab Emirates · University of Birmingham Birmingham, United Kingdom · Khalifa University Abu Dhabi, United Arab Emirates +1
How Good are Foundation Models in Longitudinal MRI Disease Progression Reasoning?
Aug 13, 2026Wafa Al Ghallabi, Ritesh Thawkar, Sara Ghaboura +6Radiology VLMs Medical Image Analysis
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE · Department of Health Abu Dhabi, Abu Dhabi, UAE · Fatima College of Health Sciences, Abu Dhabi, UAE +1
CT- $Δ$ Bench: A Benchmark for Longitudinal 3D Medical Imaging Difference Reporting with Vision-Language Models
Aug 12, 2026Kegeng Tang, Jingbo Wang, Shaogang Ren +1Radiology Report Generation Longitudinal Medical Image Analysis
University of Tennessee at Chattanooga
Modelling Geographic Atrophy Progression using Implicit Neural Representations
Aug 11, 2026Simone Sarrocco, Paul Friedrich, Florentin Bieder +4Longitudinal Medical Image Analysis Medical Image Segmentation
Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland · Department of Ophthalmology, University Hospital Basel, Basel, Switzerland · Vienna University of Natural Resources and Life Sciences, Vienna, Austria +1
Parcel2Progression: An Anatomy-aware Longitudinal Framework for Alzheimer's Disease Diagnosis
Aug 9, 2026Madhumitha Venkatesh, Shanawaj S Madarkar, Konda Reddy MopuriLongitudinal Medical Image Analysis Alzheimer's Disease Classification
Indian Institute of Technology Hyderabad, India
$\texttt{DisMorph}$ : learning to disentangle technical distortions from true biological change
Aug 8, 2026Jingru Fu, Kathleen E. Larson, Douglas N. Greve +2Longitudinal Medical Image Analysis Medical Image Registration
Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, USA · Department of Radiology, Massachusetts General Hospital, Boston, USA · Department of Radiology, Harvard Medical School, Boston, USA
Longitudinal 3D Foundation Modeling for Neoadjuvant Breast Cancer Response Prediction from Serial DCE-MRI
Aug 7, 2026Fidel Omar Tito Cruz, Neda Ghafouri, Zengyan Wang +3Breast Cancer Longitudinal Medical Image Analysis
University of Central Florida, Orlando, FL, USA
Algorithmic statistics of retinal images
Aug 6, 2026Loan Huynh, Ronald Zambrano, Layton Aho +4Medical Imaging Longitudinal Medical Image Analysis
Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA · Glaucoma Service, Wills Eye Hospital, Philadelphia, PA, USA · School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA +2
ALTER: Modeling Longitudinal Changes via Regional Differencing for 3D CT Report Generation
Aug 6, 2026Dongchen Li, Jitao Liang, Wei LiRadiology Report Generation 3D Medical Imaging
College of Computer Science and Engineering, Northeastern University, Shenyang, China · National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, China · Key Laboratory of Intelligent Computing in Medical Image (MIIC), Northeastern University, Shenyang, China
Predicting Brain Morphometry with MT-GNN: Mesh Evolution in Continuous Time with Graph-Based Metric Tensor Embeddings
Aug 5, 2026Hao Ding, Daniel Semchin, Paul M. Thompson +1Graph Neural Networks Longitudinal Medical Image Analysis
Illinois Institute of Technology · University of Southern California
Implicit Neural Representations for Multimodal Longitudinal Image Imputation and Interpolation
Aug 3, 2026Sina Wendrich, Lukas Förner, Zoe Reinke +5Implicit Neural Representations Longitudinal Medical Image Analysis
Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Augsburg, Germany · Digital Medicine, University Hospital Augsburg, Augsburg, Germany · Chair for Computer-Aided Medical Procedures and Augmented Reality, Technical University of Munich, Garching bei München, Germany +3
Anticipatory Digital Twins for Online Head-and-Neck Adaptive Proton Therapy via Foundation-Model Registration
Aug 1, 2026Yizhou Wu, Yuheng Li, Xiaofeng Yang +1Longitudinal Medical Image Analysis Digital Twins
Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30308, USA · Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL 60637, USA
LoMeVQA: A Comprehensive Benchmark for Longitudinal Medical VQA
Jul 30, 2026Zhilin Wu, Zhangkai Ni, Chengmei Yang +4Longitudinal Medical Image Analysis Medical VQA
Tongji University Shanghai, China · East China Normal University Shanghai, China
ProgFormer: Hierarchical Voxel Diffusion Transformer for Longitudinal Brain MRI Prediction
Jul 30, 2026Dexuan Ding, Yuankai Qi, Luping Zhou +3Diffusion Transformer Longitudinal Medical Image Analysis
Macquarie University · University of Sydney · University of California Merced
Beyond Random Partitioning: Unsupervised Spatio-Temporal Stratification for Cohort Balancing in Longitudinal Medical Imaging
Jul 29, 2026Qinghui Liu, Jon André Ottesen, Atle Bjørnerud +1Longitudinal Medical Image Analysis Covariate Shift
Department of Physics and Computational Radiology, Oslo University Hospital, Norway
Inverse Bayesian Inference for Extracting Lesion Dynamics from Longitudinal Spectral CT
Jul 25, 2026Lukas Förner, Melina Wördehoff, Julian Steffens +6Latent Dynamics Modeling Bayesian Inverse Problems
Dept. of diagnostic and interventional Radiology and Neuroradiology, University Hospital Augsburg, Germany · Digital Medicine, University Hospital Augsburg, Germany · Chair for Computer-Aided Medical Procedures and Augmented Reality, Technical University of Munich, Germany +5
TRACE-PCa: Predicting Prostate Cancer Progression from Longitudinal MRI During Active Surveillance
Jul 15, 2026Hongye Zeng, Shreeram Athreya, Dingyuan Dai +4Longitudinal Medical Image Analysis Clinical Outcome Prediction
Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, USA · Department of Electrical & Computer Engineering, University of California, Los Angeles, Los Angeles, USA · Department of Urology, University of California, Los Angeles, Los Angeles, USA +2

Oct 6, 2026, cs.LGJ/K move · Enter open · S save

Patient, Place, Prior (P $^3$ ): What Counts as Personalization in Medical World Models?

Xingrui Gu, Hanxue Gu, Yuxiang Zhang, Yang Yang

University of California, Berkeley · University of California, San Francisco · Southern Methodist University

Longitudinal Medical Image Analysis Predictive Representation Learning Joint-Embedding Predictive Architecture

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Longitudinal models forecast how a patient's imaging state evolves, but accuracy does not show whether the patient's observed trajectory drives the prediction. A population-average forecast may be useful but cannot establish a patient-specific world-model claim. We introduce Patient, Place, Prior (P

^3

), an audit asking whether a forecast benefits from the patient's longitudinal imaging history (Patient), benefits from patient-matched externally supplied spatial support (Place), and gains predictive value beyond a population-average prediction under matched support and context (Prior). We also propose Cancer JEPA, a one-step model that forecasts frozen representations of future breast dynamic contrast-enhanced MRI examinations during neoadjuvant therapy. It adds a lesion-constrained neural correction, trained with an occlusion-based latent objective, to a patient-conditioned low-complexity reduced-rank regression baseline. This factorization permits a post-hoc P

^3

audit of the frozen model. In a validation cohort previously used in development, forecast error is lower when the neural correction receives the patient's history rather than another patient's and patient-matched lesion occupancy maps rather than substituted maps. However, the descriptive 95% interval comparing the correction computed from patient history with the population-average neural correction includes zero. P

^3

thus separates input use from evidence of patient-specific predictive value beyond a population-level pattern.

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