{"total":28,"rows":[{"id":"2409.19483","title":"MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation","created":"2024-09-28","cited_by_count":39,"area":null},{"id":"2511.19046","title":"MedSAM3: Delving into Segment Anything with Medical Concepts","created":"2025-11-24","cited_by_count":26,"area":null},{"id":"2503.04639","title":"Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation","created":"2025-03-06","cited_by_count":12,"area":null},{"id":"2503.06030","title":"Towards Universal Text-driven CT Image Segmentation","created":"2025-03-08","cited_by_count":7,"area":null},{"id":"2507.18082","title":"TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound","created":"2025-07-24","cited_by_count":5,"area":null},{"id":"2506.05221","title":"SAM-aware Test-time Adaptation for Universal Medical Image Segmentation","created":"2025-06-05","cited_by_count":3,"area":null},{"id":"2501.16992","title":"FedEFM: Federated Endovascular Foundation Model with Unseen Data","created":"2025-01-28","cited_by_count":2,"area":null},{"id":"2503.22237","title":"SCHNet: SAM Marries CLIP for Human Parsing","created":"2025-03-28","cited_by_count":2,"area":null},{"id":"2507.09966","title":"Multimodal Fusion at Three Tiers: Physics-Driven Data Generation and Vision-Language Guidance for Brain Tumor Segmentation","created":"2025-07-14","cited_by_count":1,"area":null},{"id":"2511.04255","title":"MedSapiens: Taking a Pose to Rethink Medical Imaging Landmark Detection","created":"2025-11-06","cited_by_count":1,"area":null},{"id":"2408.09886","title":"Improved Baselines with Synchronized Encoding for Universal Medical Image Segmentation","created":"2024-08-19","cited_by_count":0,"area":null},{"id":"2411.15611","title":"If you can describe it, they can see it: Cross-Modal Learning of Visual Concepts from Textual Descriptions","created":"2024-11-23","cited_by_count":0,"area":null},{"id":"2412.19026","title":"Modality-Projection Universal Model for Comprehensive Full-Body Medical Imaging Segmentation","created":"2024-12-26","cited_by_count":0,"area":null},{"id":"2505.17096","title":"TAGS: 3D Tumor-Adaptive Guidance for SAM","created":"2025-05-21","cited_by_count":0,"area":null},{"id":"2505.17931","title":"AutoMiSeg: Automatic Medical Image Segmentation via Test-Time Adaptation of Foundation Models","created":"2025-05-23","cited_by_count":0,"area":null},{"id":"2506.21199","title":"MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification","created":"2025-06-26","cited_by_count":0,"area":null},{"id":"2509.08618","title":"CLAPS: A CLIP-Unified Auto-Prompt Segmentation for Multi-Modal Retinal Imaging","created":"2025-09-10","cited_by_count":0,"area":null},{"id":"2509.09130","title":"ALL-PET: A Low-resource and Low-shot PET Foundation Model in Projection Domain","created":"2025-09-11","cited_by_count":0,"area":null},{"id":"2509.23054","title":"Mask What Matters: Controllable Text-Guided Masking for Self-Supervised Medical Image Analysis","created":"2025-09-27","cited_by_count":0,"area":null},{"id":"2511.05044","title":"Medical Referring Image Segmentation via Next-Token Mask Prediction","created":"2025-11-07","cited_by_count":0,"area":null},{"id":"2511.15411","title":"D4C: Data-Free Quantization for Contrastive Language-Image Pre-training Models","created":"2025-11-19","cited_by_count":0,"area":null},{"id":"2603.21904","title":"SHAPE: Structure-aware Hierarchical Unsupervised Domain Adaptation with Plausibility Evaluation for Medical Image Segmentation","created":"2026-03-23","cited_by_count":0,"area":null},{"id":"2604.10000","title":"SwinTextUNet: Integrating CLIP-Based Text Guidance into Swin Transformer U-Nets for Medical Image Segmentation","created":"2026-04-11","cited_by_count":0,"area":null},{"id":"2605.23068","title":"RoboSurg-VQA: A Multimodal Benchmark for Surgical Segmentation-Aware Visual Question Answering","created":"2026-05-21","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":"2607.17693","title":"Memory-Supported Synergistic Adaptation for Training-Free Test-Time Medical Image Segmentation","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2609.07499","title":"CrACK: Adversarial Attacks on Cross-Model Consistency in Collaborative Vision Foundation Models","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.34472","title":"VL-AcneSeg: A Vision-Language Framework for Region-Aware Acne Lesion Segmentation","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}