{"total":99,"rows":[{"id":"2406.04449","title":"MAIRA-2: Grounded Radiology Report Generation","created":"2024-06-06","cited_by_count":145,"area":null},{"id":"2410.06542","title":"MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging","created":"2024-10-09","cited_by_count":46,"area":null},{"id":"2411.19378","title":"Libra: Leveraging Temporal Images for Biomedical Radiology Analysis","created":"2024-11-28","cited_by_count":29,"area":null},{"id":"2509.18030","title":"RadEval: A framework for radiology text evaluation","created":"2025-09-22","cited_by_count":22,"area":null},{"id":"2408.12880","title":"Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey","created":"2024-08-23","cited_by_count":20,"area":null},{"id":"2405.01469","title":"Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning","created":"2024-05-02","cited_by_count":18,"area":null},{"id":"2412.12001","title":"LLM-RG4: Flexible and Factual Radiology Report Generation across Diverse Input Contexts","created":"2024-12-16","cited_by_count":13,"area":null},{"id":"2503.07667","title":"CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models","created":"2025-03-09","cited_by_count":13,"area":null},{"id":"2509.10620","title":"Building a General SimCLR Self-Supervised Foundation Model Across Neurological Diseases to Advance 3D Brain MRI Diagnoses","created":"2025-09-12","cited_by_count":10,"area":null},{"id":"2508.05353","title":"PriorRG: Prior-Guided Contrastive Pre-training and Coarse-to-Fine Decoding for Chest X-ray Report Generation","created":"2025-08-07","cited_by_count":9,"area":null},{"id":"2506.09095","title":"Foundation Models in Medical Imaging: A Review and Outlook","created":"2025-06-10","cited_by_count":8,"area":null},{"id":"2509.06617","title":"MM-DINOv2: Adapting Foundation Models for Multi-Modal Medical Image Analysis","created":"2025-09-08","cited_by_count":7,"area":null},{"id":"2403.06567","title":"Leveraging Foundation Models for Content-Based Image Retrieval in Radiology","created":"2024-03-11","cited_by_count":6,"area":null},{"id":"2502.05142","title":"Chest X-ray Foundation Model with Global and Local Representations Integration","created":"2025-02-07","cited_by_count":6,"area":null},{"id":"2505.10496","title":"CheXGenBench: A Unified Benchmark For Fidelity, Privacy and Utility of Synthetic Chest Radiographs","created":"2025-05-15","cited_by_count":5,"area":null},{"id":"2506.08990","title":"Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models","created":"2025-06-10","cited_by_count":5,"area":null},{"id":"2506.22900","title":"MOTOR: Multimodal Optimal Transport via Grounded Retrieval in Medical Visual Question Answering","created":"2025-06-28","cited_by_count":5,"area":null},{"id":"2509.12818","title":"Data Scaling Laws for Radiology Foundation Models","created":"2025-09-16","cited_by_count":5,"area":null},{"id":"2402.15534","title":"DiCoM -- Diverse Concept Modeling towards Enhancing Generalizability in Chest X-Ray Studies","created":"2024-02-22","cited_by_count":4,"area":null},{"id":"2412.03192","title":"Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging","created":"2024-12-04","cited_by_count":4,"area":null},{"id":"2503.04522","title":"ConfIC-RCA: Statistically Grounded Efficient Estimation of Segmentation Quality","created":"2025-03-06","cited_by_count":4,"area":null},{"id":"2503.14998","title":"Tables Guide Vision: Learning to See the Heart through Tabular Data","created":"2025-03-19","cited_by_count":4,"area":null},{"id":"2504.07416","title":"RadZero: Similarity-Based Cross-Attention for Explainable Vision-Language Alignment in Chest X-ray with Zero-Shot Multi-Task Capability","created":"2025-04-10","cited_by_count":4,"area":null},{"id":"2506.11777","title":"Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation","created":"2025-06-13","cited_by_count":4,"area":null},{"id":"2504.02351","title":"Agglomerating Large Vision Encoders via Distillation for VFSS Segmentation","created":"2025-04-03","cited_by_count":3,"area":null},{"id":"2505.10823","title":"From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification","created":"2025-05-16","cited_by_count":3,"area":null},{"id":"2508.10794","title":"VasoMIM: Vascular Anatomy-Aware Masked Image Modeling for Vessel Segmentation","created":"2025-08-14","cited_by_count":3,"area":null},{"id":"2502.19577","title":"Tell me why: Visual foundation models as self-explainable classifiers","created":"2025-02-26","cited_by_count":2,"area":null},{"id":"2506.10825","title":"Generalist Models in Medical Image Segmentation: A Survey and Performance Comparison with Task-Specific Approaches","created":"2025-06-12","cited_by_count":2,"area":null},{"id":"2509.01360","title":"M3Ret: Unleashing Zero-shot Multimodal Medical Image Retrieval via Self-Supervision","created":"2025-09-01","cited_by_count":2,"area":null},{"id":"2511.14918","title":"X-WIN: Building Chest Radiograph World Model via Predictive Sensing","created":"2025-11-18","cited_by_count":2,"area":null},{"id":"2512.00872","title":"TAP-CT: 3D Task-Agnostic Pretraining of Computed Tomography Foundation Models","created":"2025-11-30","cited_by_count":2,"area":null},{"id":"2512.15808","title":"Foundation Models in Biomedical Imaging: Turning Hype into Reality","created":"2025-12-17","cited_by_count":2,"area":null},{"id":"2601.10124","title":"VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation","created":"2026-01-15","cited_by_count":2,"area":null},{"id":"2602.22843","title":"A data- and compute-efficient chest X-ray foundation model beyond aggressive scaling","created":"2026-02-26","cited_by_count":2,"area":null},{"id":"2505.03380","title":"Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks","created":"2025-05-06","cited_by_count":1,"area":null},{"id":"2505.15248","title":"VET-DINO: Learning Anatomical Understanding Through Multi-View Distillation in Veterinary Imaging","created":"2025-05-21","cited_by_count":1,"area":null},{"id":"2506.08915","title":"Two-stage Vision Transformers and Hard Masking offer Robust Object Representations","created":"2025-06-10","cited_by_count":1,"area":null},{"id":"2508.04955","title":"AdvDINO: Domain-Adversarial Self-Supervised Representation Learning for Spatial Proteomics","created":"2025-08-07","cited_by_count":1,"area":null},{"id":"2509.12146","title":"Multi Anatomy X-Ray Foundation Model","created":"2025-09-15","cited_by_count":1,"area":null},{"id":"2510.01683","title":"Uncovering Overconfident Failures in CXR Models via Augmentation-Sensitivity Risk Scoring","created":"2025-10-02","cited_by_count":1,"area":null},{"id":"2511.09742","title":"Feature Quality and Adaptability of Medical Foundation Models: A Comparative Evaluation for Radiographic Classification and Segmentation","created":"2025-11-12","cited_by_count":1,"area":null},{"id":"2511.19889","title":"LiMT: A Multi-task Liver Image Benchmark Dataset","created":"2025-11-25","cited_by_count":1,"area":null},{"id":"2603.09374","title":"MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification","created":"2026-03-10","cited_by_count":1,"area":null},{"id":"2603.13660","title":"Learning Generalizable 3D Medical Image Representations from Mask-Guided Self-Supervision","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2603.27519","title":"SPROUT: A Scalable Diffusion Foundation Model for Multi-Crop Plant Phenotyping","created":"2026-03-29","cited_by_count":1,"area":null},{"id":"2605.19374","title":"Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings","created":"2026-05-19","cited_by_count":1,"area":null},{"id":"2606.11606","title":"Frozen Foundation-Model Embeddings Discard Small-Lesion Signal in Chest Radiography: Implications for Pre-Deployment Evaluation","created":"2026-06-10","cited_by_count":1,"area":null},{"id":"2607.04199","title":"Topology-Driven Transferability Estimation for 3D Medical Vision Foundation Models","created":"2026-07-05","cited_by_count":1,"area":null},{"id":"2607.10358","title":"Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift","created":"2026-07-11","cited_by_count":1,"area":null},{"id":"2609.24879","title":"Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models","created":"2026-09-21","cited_by_count":1,"area":null},{"id":"2503.04478","title":"Semantic Alignment of Unimodal Medical Text and Vision Representations","created":"2025-03-06","cited_by_count":0,"area":null},{"id":"2505.09329","title":"BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis","created":"2025-05-14","cited_by_count":0,"area":null},{"id":"2505.18958","title":"CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation","created":"2025-05-25","cited_by_count":0,"area":null},{"id":"2507.00185","title":"Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)","created":"2025-06-30","cited_by_count":0,"area":null},{"id":"2507.16623","title":"Automatic Fine-grained Segmentation-assisted Report Generation","created":"2025-07-22","cited_by_count":0,"area":null},{"id":"2509.17660","title":"Development and validation of an AI foundation model for endoscopic diagnosis of esophagogastric junction adenocarcinoma: a cohort and deep learning study","created":"2025-09-22","cited_by_count":0,"area":null},{"id":"2510.05971","title":"Shaken or Stirred? An Analysis of MetaFormer's Token Mixing for Medical Imaging","created":"2025-10-07","cited_by_count":0,"area":null},{"id":"2511.21735","title":"Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting","created":"2025-11-21","cited_by_count":0,"area":null},{"id":"2512.09496","title":"Representation Invariance and Allocation: When Subgroup Balance Matters","created":"2025-12-10","cited_by_count":0,"area":null},{"id":"2512.13608","title":"DBT-DINO: Towards Foundation model based analysis of Digital Breast Tomosynthesis","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2512.22872","title":"Lamps: Learning Anatomy from Multiple Perspectives via Self-supervision in Chest Radiographs","created":"2025-12-28","cited_by_count":0,"area":null},{"id":"2602.10359","title":"Beyond Calibration: Confounding Pathology Limits Foundation Model Specificity in Abdominal Trauma CT","created":"2026-02-10","cited_by_count":0,"area":null},{"id":"2602.11536","title":"Vascular anatomy-aware self-supervised pre-training for X-ray angiogram analysis","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2603.23729","title":"Bi-CRCL: Bidirectional Conservative-Radical Complementary Learning with Pre-trained Foundation Models for Class-incremental Medical Image Analysis","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2604.18967","title":"CXRMate-2: Structured Multimodal Temporal Embeddings and Tractable Reinforcement Learning for Clinically Acceptable Chest X-ray Radiology Report Generation","created":"2026-04-21","cited_by_count":0,"area":null},{"id":"2604.24597","title":"Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2605.06095","title":"Metonymy in vision models undermines attention-based interpretability","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.09151","title":"MultiMedVision: Multi-Modal Medical Vision Framework","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2605.18974","title":"Harnessing Self-Supervised Features for Art Classification","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2605.30131","title":"CCS: Clinical Consensus Selection for Radiology Report Generation","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.06534","title":"Attention Consistent Longitudinal Medical Visual Question Answering Guided by Vision Foundation Models","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2606.07775","title":"DALE-CT: Depth-Aware 2D Slice Encoders Learn an Anatomical World Model of Chest CT","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2606.08364","title":"Self-Supervised Vision Transformers for CBCT-Based Detection of Temporomandibular Joint Osteoarthritis","created":"2026-06-06","cited_by_count":0,"area":null},{"id":"2606.21290","title":"NoduLoCC2026: Lung Nodule Localization and Classification Contest from Chest X-Ray Images","created":"2026-06-19","cited_by_count":0,"area":null},{"id":"2606.30577","title":"APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2607.02024","title":"Spatio-Temporal and Clinical Conditioning for Fine-Grained Radiology Report Retrieval","created":"2026-07-02","cited_by_count":0,"area":null},{"id":"2607.06268","title":"MAC-XA: Multi-view Anatomy-Correspondence Fusion for Coronary Stenosis Reporting from X-ray Angiography","created":"2026-07-07","cited_by_count":0,"area":null},{"id":"2607.18451","title":"CANDOR: Chance-Calibrated Neighborhood Discordance in Frozen Encoders for Medical Imaging","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2607.27235","title":"RadHarmony: Radiological Data Handling in the Era of Agentic AI","created":"2026-07-24","cited_by_count":0,"area":null},{"id":"2608.08046","title":"JustLLMGRPO: Radiographic Control for Chest X-Ray Generation","created":"2026-08-08","cited_by_count":0,"area":null},{"id":"2608.14763","title":"Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening","created":"2026-08-14","cited_by_count":0,"area":null},{"id":"2608.19078","title":"Subgroup performance analysis of adaptation strategies for chest X-ray foundation models","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2608.19825","title":"Towards Clinically Faithful Medical Image Captioning via Enhanced Vision-Language Alignment","created":"2026-08-20","cited_by_count":0,"area":null},{"id":"2608.22059","title":"CRS-Bench: A Reference-Relative Reliability Benchmark for Medical Image Encoders","created":"2026-08-22","cited_by_count":0,"area":null},{"id":"2608.24364","title":"B-MIM: Biased Masked Image Modeling for Generalizable Segmentation of Fine-Grained Anatomical Structures","created":"2026-08-25","cited_by_count":0,"area":null},{"id":"2608.25981","title":"FRAME: Separating sampling variation from performance disparities in medical image analysis","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2608.30390","title":"Uncertainty of Vision Medical Foundation Models","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.07719","title":"A radiographic world model for clinical reasoning and evidence generation","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.09140","title":"NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.09185","title":"Integrating Unimodal and Vision-Language Representations in Latent Space for Multi-Label Chest X-Ray Classification","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.20826","title":"TALON: A Temporally Aware Longitudinal Framework for Radiology Report Generation","created":"2026-07-22","cited_by_count":0,"area":null},{"id":"2609.32672","title":"STAMP: Predicting Out-of-Distribution Generalization without Target Data","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2609.33520","title":"Anatomy-Structured Hierarchical MIL for Weakly-Supervised Thoracic Disease Detection in Chest X-rays","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.33769","title":"M3-Score: Fidelity, Memorization and Coverage as Separate Axes for Evaluating Generative Radiology Image Models","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.34487","title":"PACER: Progressive Availability-Conditioned Evidence Routing for Radiology Report Generation under Incomplete Clinical Context","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.37682","title":"Med-RADIO: Reducing All Medical Domains Into One via Multi-Teacher Distillation","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.03817","title":"Image-Based Breast Implant Detection for Mammography Dataset Curation and Near-Real-Time Deployment: Comparing Foundation Models and Task-Specific Convolutional Models","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.17354","title":"MID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}