{"total":24,"rows":[{"id":"2410.09890","title":"Large-Scale 3D Medical Image Pre-training with Geometric Context Priors","created":"2024-10-13","cited_by_count":36,"area":null},{"id":"2311.17597","title":"Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning","created":"2023-11-29","cited_by_count":34,"area":null},{"id":"2404.09957","title":"How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model","created":"2024-04-15","cited_by_count":32,"area":null},{"id":"2502.14064","title":"Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging","created":"2025-02-19","cited_by_count":24,"area":null},{"id":"2410.10604","title":"Multi-modal Vision Pre-training for Medical Image Analysis","created":"2024-10-14","cited_by_count":23,"area":null},{"id":"2404.15580","title":"MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysis","created":"2024-04-24","cited_by_count":19,"area":null},{"id":"2501.11253","title":"How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?","created":"2025-01-20","cited_by_count":19,"area":null},{"id":"2401.12215","title":"Less Could Be Better: Parameter-efficient Fine-tuning Advances Medical Vision Foundation Models","created":"2024-01-22","cited_by_count":18,"area":null},{"id":"2303.12484","title":"Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions","created":"2023-03-22","cited_by_count":16,"area":null},{"id":"2312.04964","title":"ZePT: Zero-Shot Pan-Tumor Segmentation via Query-Disentangling and Self-Prompting","created":"2023-12-07","cited_by_count":15,"area":null},{"id":"2404.15672","title":"Representing Part-Whole Hierarchies in Foundation Models by Learning Localizability, Composability, and Decomposability from Anatomy via Self-Supervision","created":"2024-04-24","cited_by_count":13,"area":null},{"id":"2407.06468","title":"AnatoMask: Enhancing Medical Image Segmentation with Reconstruction-guided Self-masking","created":"2024-07-09","cited_by_count":10,"area":null},{"id":"2501.04217","title":"Continual Self-supervised Learning Considering Medical Domain Knowledge in Chest CT Images","created":"2025-01-08","cited_by_count":5,"area":null},{"id":"2507.02581","title":"Structure-aware Semantic Discrepancy and Consistency for 3D Medical Image Self-supervised Learning","created":"2025-07-03","cited_by_count":5,"area":null},{"id":"2411.06106","title":"Towards a Universal 3D Medical Multi-modality Generalization via Learning Personalized Invariant Representation","created":"2024-11-09","cited_by_count":3,"area":null},{"id":"2401.06473","title":"Self-supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation","created":"2024-01-12","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":"2501.10131","title":"ACE: Anatomically Consistent Embeddings in Composition and Decomposition","created":"2025-01-17","cited_by_count":1,"area":null},{"id":"2506.20282","title":"Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration","created":"2025-06-25","cited_by_count":1,"area":null},{"id":"2509.24311","title":"Towards Foundation Models for Cryo-ET Subtomogram Analysis","created":"2025-09-29","cited_by_count":0,"area":null},{"id":"2603.10519","title":"Visually-Guided Controllable Medical Image Generation via Fine-Grained Semantic Disentanglement","created":"2026-03-11","cited_by_count":0,"area":null},{"id":"2605.01874","title":"Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise","created":"2026-05-03","cited_by_count":0,"area":null},{"id":"2605.14654","title":"Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2610.13915","title":"Where to Look Matters: Rethinking Sub-Volume Sampling in 3D Medical Self-supervised Learning","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}