{"total":65,"rows":[{"id":"2306.16269","title":"RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model","created":"2023-06-28","cited_by_count":181,"area":null},{"id":"2307.13721","title":"Foundational Models Defining a New Era in Vision: A Survey and Outlook","created":"2023-07-25","cited_by_count":110,"area":null},{"id":"2401.03495","title":"Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directions","created":"2024-01-07","cited_by_count":97,"area":null},{"id":"2404.03264","title":"Foundation Model for Advancing Healthcare: Challenges, Opportunities, and Future Directions","created":"2024-04-04","cited_by_count":77,"area":null},{"id":"2401.17868","title":"Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model","created":"2024-01-31","cited_by_count":69,"area":null},{"id":"2409.19483","title":"MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation","created":"2024-09-28","cited_by_count":39,"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":"2401.07654","title":"Foundation Models for Biomedical Image Segmentation: A Survey","created":"2024-01-15","cited_by_count":28,"area":null},{"id":"2308.14936","title":"AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation","created":"2023-08-28","cited_by_count":19,"area":null},{"id":"2409.00924","title":"MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM","created":"2024-09-02","cited_by_count":17,"area":null},{"id":"2410.04960","title":"On Efficient Variants of Segment Anything Model: A Survey","created":"2024-10-07","cited_by_count":16,"area":null},{"id":"2309.16967","title":"nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance","created":"2023-09-29","cited_by_count":12,"area":null},{"id":"2407.07042","title":"ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models","created":"2024-07-09","cited_by_count":12,"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":"2408.06447","title":"S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation","created":"2024-08-12","cited_by_count":11,"area":null},{"id":"2406.08020","title":"Generalizable Disaster Damage Assessment via Change Detection with Vision Foundation Model","created":"2024-06-12","cited_by_count":10,"area":null},{"id":"2311.10529","title":"Enhancing the Reliability of Segment Anything Model for Auto-Prompting Medical Image Segmentation with Uncertainty Rectification","created":"2023-11-17","cited_by_count":8,"area":null},{"id":"2505.09274","title":"Recent Advances in Medical Imaging Segmentation: A Survey","created":"2025-05-14","cited_by_count":8,"area":null},{"id":"2409.06821","title":"Sam2Rad: A Segmentation Model for Medical Images with Learnable Prompts","created":"2024-09-10","cited_by_count":6,"area":null},{"id":"2311.08891","title":"AdapterShadow: Adapting Segment Anything Model for Shadow Detection","created":"2023-11-15","cited_by_count":5,"area":null},{"id":"2403.13258","title":"SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts","created":"2024-03-20","cited_by_count":5,"area":null},{"id":"2409.20293","title":"Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision","created":"2024-09-30","cited_by_count":5,"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":"2307.12674","title":"Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaul","created":"2023-07-24","cited_by_count":4,"area":null},{"id":"2310.00504","title":"Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology and Pathology","created":"2023-09-30","cited_by_count":4,"area":null},{"id":"2403.14103","title":"MaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation","created":"2024-03-21","cited_by_count":4,"area":null},{"id":"2404.13239","title":"Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models","created":"2024-04-20","cited_by_count":4,"area":null},{"id":"2404.14837","title":"Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images","created":"2024-04-23","cited_by_count":4,"area":null},{"id":"2412.02993","title":"EchoONE: Segmenting Multiple echocardiography Planes in One Model","created":"2024-12-04","cited_by_count":4,"area":null},{"id":"2403.04164","title":"ProMISe: Promptable Medical Image Segmentation using SAM","created":"2024-03-07","cited_by_count":3,"area":null},{"id":"2405.16740","title":"PP-SAM: Perturbed Prompts for Robust Adaptation of Segment Anything Model for Polyp Segmentation","created":"2024-05-27","cited_by_count":3,"area":null},{"id":"2410.09714","title":"AM-SAM: Automated Prompting and Mask Calibration for Segment Anything Model","created":"2024-10-13","cited_by_count":3,"area":null},{"id":"2511.01284","title":"Adaptation of Foundation Models for Medical Image Analysis: Strategies, Challenges, and Future Directions","created":"2025-11-03","cited_by_count":3,"area":null},{"id":"2312.03119","title":"AI-SAM: Automatic and Interactive Segment Anything Model","created":"2023-12-05","cited_by_count":2,"area":null},{"id":"2411.02745","title":"Foundation AI Model for Medical Image Segmentation","created":"2024-11-05","cited_by_count":2,"area":null},{"id":"2507.02743","title":"Prompt learning with bounding box constraints for medical image segmentation","created":"2025-07-03","cited_by_count":2,"area":null},{"id":"2310.10493","title":"Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentation","created":"2023-10-16","cited_by_count":1,"area":null},{"id":"2401.02076","title":"Leveraging SAM for Single-Source Domain Generalization in Medical Image Segmentation","created":"2024-01-04","cited_by_count":1,"area":null},{"id":"2402.11585","title":"PolypNextLSTM: A lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM","created":"2024-02-18","cited_by_count":1,"area":null},{"id":"2403.18114","title":"Segment Any Medical Model Extended","created":"2024-03-26","cited_by_count":1,"area":null},{"id":"2407.02625","title":"Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images","created":"2024-07-02","cited_by_count":1,"area":null},{"id":"2407.08109","title":"Urban Waterlogging Detection: A Challenging Benchmark and Large-Small Model Co-Adapter","created":"2024-07-11","cited_by_count":1,"area":null},{"id":"2409.14095","title":"Foundation Models for Amodal Video Instance Segmentation in Automated Driving","created":"2024-09-21","cited_by_count":1,"area":null},{"id":"2411.16949","title":"A SAM-guided and Match-based Semi-Supervised Segmentation Framework for Medical Imaging","created":"2024-11-25","cited_by_count":1,"area":null},{"id":"2502.03501","title":"Proxy Prompt: Endowing SAM and SAM 2 with Auto-Interactive-Prompt for Medical Segmentation","created":"2025-02-05","cited_by_count":1,"area":null},{"id":"2506.19658","title":"SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting","created":"2025-06-24","cited_by_count":1,"area":null},{"id":"2511.17201","title":"Continual Alignment for SAM: Rethinking Foundation Models for Medical Image Segmentation in Continual Learning","created":"2025-11-21","cited_by_count":1,"area":null},{"id":"2512.08439","title":"LapFM: A Laparoscopic Segmentation Foundation Model via Hierarchical Concept Evolving Pre-training","created":"2025-12-09","cited_by_count":1,"area":null},{"id":"2601.01213","title":"Promptable Foundation Models for SAR Remote Sensing: Adapting the Segment Anything Model for Snow Avalanche Segmentation","created":"2026-01-03","cited_by_count":1,"area":null},{"id":"2604.09814","title":"RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation","created":"2026-04-10","cited_by_count":1,"area":null},{"id":"2608.24541","title":"Hierarchical Prototype-Memory Adaptation of SAM for Surgical Instrument Segmentation","created":"2026-08-25","cited_by_count":1,"area":null},{"id":"2401.05638","title":"MatSAM: Efficient Extraction of Microstructures of Materials via Visual Large Model","created":"2024-01-11","cited_by_count":0,"area":null},{"id":"2505.21644","title":"Geometric Feature Prompting of Image Segmentation Models","created":"2025-05-27","cited_by_count":0,"area":null},{"id":"2508.17408","title":"E-BayesSAM: Efficient Bayesian Adaptation of SAM with Self-Optimizing KAN-Based Interpretation for Uncertainty-Aware Ultrasonic Segmentation","created":"2025-08-24","cited_by_count":0,"area":null},{"id":"2509.18891","title":"Attack for Defense: Adversarial Agents for Point Prompt Optimization Empowering Segment Anything Model","created":"2025-09-23","cited_by_count":0,"area":null},{"id":"2511.21984","title":"PPBoost: Progressive Prompt Boosting for Text-Driven Medical Image Segmentation","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2603.00372","title":"Unsupervised Semantic Segmentation in Synchrotron Computed Tomography with Self-Correcting Pseudo Labels","created":"2026-02-27","cited_by_count":0,"area":null},{"id":"2603.27250","title":"IP-SAM: Rethinking Prompt-Conditioned Segmentation for Prompt-Absent Deployment","created":"2026-03-28","cited_by_count":0,"area":null},{"id":"2604.23314","title":"Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM","created":"2026-04-25","cited_by_count":0,"area":null},{"id":"2606.14755","title":"Where Does Texture Evidence Live in SAM? Features, Proposal Masks, and Texture Segmentation","created":"2026-06-07","cited_by_count":0,"area":null},{"id":"2606.21108","title":"SARIF: Segment Anything for Robust Image Forensics","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":"2607.00409","title":"MedCAGD: Context-Aware Gated Decoder for Efficient Medical Image Segmentation","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2607.13323","title":"SARFA: Segment Anything with Radiomic Feature Alignment","created":"2026-07-14","cited_by_count":0,"area":null},{"id":"2609.18037","title":"SetPlanner: A Lightweight Plug-in Point-Set Planner for Frozen SAM","created":"2026-09-16","cited_by_count":0,"area":null}],"next_cursor":null}