{"total":41,"rows":[{"id":"2401.10815","title":"Exploring scalable medical image encoders beyond text supervision","created":"2024-01-19","cited_by_count":132,"area":null},{"id":"2402.07595","title":"Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging Classification","created":"2024-02-12","cited_by_count":14,"area":null},{"id":"2410.01665","title":"Towards a vision foundation model for comprehensive assessment of Cardiac MRI","created":"2024-10-02","cited_by_count":14,"area":null},{"id":"2411.15802","title":"Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2","created":"2024-11-24","cited_by_count":13,"area":null},{"id":"2410.14707","title":"FACMIC: Federated Adaptative CLIP Model for Medical Image Classification","created":"2024-10-08","cited_by_count":7,"area":null},{"id":"2506.19552","title":"General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound","created":"2025-06-24","cited_by_count":7,"area":null},{"id":"2504.08584","title":"Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representations","created":"2025-04-11","cited_by_count":6,"area":null},{"id":"2407.21739","title":"A Federated Learning-Friendly Approach for Parameter-Efficient Fine-Tuning of SAM in 3D Segmentation","created":"2024-07-31","cited_by_count":5,"area":null},{"id":"2409.18536","title":"How Effective is Pre-training of Large Masked Autoencoders for Downstream Earth Observation Tasks?","created":"2024-09-27","cited_by_count":5,"area":null},{"id":"2405.03762","title":"Swin transformers are robust to distribution and concept drift in endoscopy-based longitudinal rectal cancer assessment","created":"2024-05-06","cited_by_count":4,"area":null},{"id":"2407.17219","title":"Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification?","created":"2024-07-24","cited_by_count":4,"area":null},{"id":"2503.24298","title":"Order Matters: On Parameter-Efficient Image-to-Video Probing for Recognizing Nearly Symmetric Actions","created":"2025-03-31","cited_by_count":3,"area":null},{"id":"2509.12512","title":"DinoAtten3D: Slice-Level Attention Aggregation of DinoV2 for 3D Brain MRI Anomaly Classification","created":"2025-09-15","cited_by_count":3,"area":null},{"id":"2405.14788","title":"Masked Image Modelling for retinal OCT understanding","created":"2024-05-23","cited_by_count":2,"area":null},{"id":"2409.02729","title":"Can language-guided unsupervised adaptation improve medical image classification using unpaired images and texts?","created":"2024-09-03","cited_by_count":2,"area":null},{"id":"2503.07958","title":"Pre-trained Models Succeed in Medical Imaging with Representation Similarity Degradation","created":"2025-03-11","cited_by_count":2,"area":null},{"id":"2503.23819","title":"Conformal uncertainty quantification to evaluate predictive fairness of foundation AI model for skin lesion classes across patient demographics","created":"2025-03-31","cited_by_count":2,"area":null},{"id":"2511.01610","title":"DINO-MX: A Modular & Flexible Framework for Self-Supervised Learning","created":"2025-11-03","cited_by_count":2,"area":null},{"id":"2512.17080","title":"Interpretable Similarity of Synthetic Image Utility","created":"2025-12-18","cited_by_count":2,"area":null},{"id":"2407.13311","title":"General Vision Encoder Features as Guidance in Medical Image Registration","created":"2024-07-18","cited_by_count":1,"area":null},{"id":"2407.18100","title":"DINOv2 Rocks Geological Image Analysis: Classification, Segmentation, and Interpretability","created":"2024-07-25","cited_by_count":1,"area":null},{"id":"2409.20253","title":"Medical Image Segmentation with SAM-generated Annotations","created":"2024-09-30","cited_by_count":1,"area":null},{"id":"2505.19779","title":"Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation Models","created":"2025-05-26","cited_by_count":1,"area":null},{"id":"2505.23040","title":"Deep Modeling and Optimization of Medical Image Classification","created":"2025-05-29","cited_by_count":1,"area":null},{"id":"2510.00520","title":"CardioBench: Do Echocardiography Foundation Models Generalize Beyond the Lab?","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2511.09605","title":"TomoGraphView: 3D Medical Image Classification with Omnidirectional Slice Representations and Graph Neural Networks","created":"2025-11-12","cited_by_count":1,"area":null},{"id":"2601.12382","title":"A Hierarchical Benchmark of Foundation Models for Dermatology","created":"2026-01-18","cited_by_count":1,"area":null},{"id":"2604.19350","title":"Attend what matters: Leveraging vision foundational models for breast cancer classification using mammograms","created":"2026-04-21","cited_by_count":1,"area":null},{"id":"2605.30893","title":"Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generation","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2404.06080","title":"Using Few-Shot Learning to Classify Primary Lung Cancer and Other Malignancy with Lung Metastasis in Cytological Imaging via Endobronchial Ultrasound Procedures","created":"2024-04-09","cited_by_count":0,"area":null},{"id":"2404.09406","title":"Human-in-the-Loop Segmentation of Multi-species Coral Imagery","created":"2024-04-15","cited_by_count":0,"area":null},{"id":"2501.12023","title":"Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis","created":"2025-01-21","cited_by_count":0,"area":null},{"id":"2503.18873","title":"Efficient Self-Supervised Adaptation for Medical Image Analysis","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2503.24138","title":"AI-Assisted Colonoscopy: Polyp Detection and Segmentation using Foundation Models","created":"2025-03-31","cited_by_count":0,"area":null},{"id":"2512.00489","title":"Learning What Helps: Task-Aligned Context Selection for Vision Tasks","created":"2025-11-29","cited_by_count":0,"area":null},{"id":"2602.15913","title":"Foundation Models for Medical Imaging: Status, Challenges, and Directions","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2603.16370","title":"FederatedFactory: Generative One-Shot Learning for Extremely Non-IID Distributed Scenarios","created":"2026-03-17","cited_by_count":0,"area":null},{"id":"2604.22557","title":"Are Natural-Domain Foundation Models Effective for Accelerated Cardiac MRI Reconstruction?","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2605.18491","title":"Benchmarking transferability of SSL pretraining to same and different modality segmentation tasks","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2606.18707","title":"PEFT-MedSAM: Efficient Fine-Tuning of Medical Foundation Models for Explainable Skin Lesion Segmentation","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2610.18543","title":"Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}