{"total":22,"rows":[{"id":"2108.06932","title":"Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers","created":"2021-08-16","cited_by_count":159,"area":null},{"id":"2306.06370","title":"AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder","created":"2023-06-10","cited_by_count":70,"area":null},{"id":"2305.00293","title":"Polyp-SAM: Transfer SAM for Polyp Segmentation","created":"2023-04-29","cited_by_count":64,"area":null},{"id":"2304.07583","title":"Can SAM Segment Polyps?","created":"2023-04-15","cited_by_count":59,"area":null},{"id":"2202.12031","title":"Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge","created":"2022-02-24","cited_by_count":27,"area":null},{"id":"2308.06623","title":"Polyp-SAM++: Can A Text Guided SAM Perform Better for Polyp Segmentation?","created":"2023-08-12","cited_by_count":22,"area":null},{"id":"2311.18373","title":"A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends","created":"2023-11-30","cited_by_count":12,"area":null},{"id":"2407.00718","title":"ASPS: Augmented Segment Anything Model for Polyp Segmentation","created":"2024-06-30","cited_by_count":12,"area":null},{"id":"2408.05892","title":"Polyp SAM 2: Advancing Zero shot Polyp Segmentation in Colorectal Cancer Detection","created":"2024-08-12","cited_by_count":8,"area":null},{"id":"2206.00806","title":"XBound-Former: Toward Cross-scale Boundary Modeling in Transformers","created":"2022-06-02","cited_by_count":6,"area":null},{"id":"2401.11734","title":"Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Survey","created":"2024-01-22","cited_by_count":5,"area":null},{"id":"2402.02298","title":"Polyp-DAM: Polyp segmentation via depth anything model","created":"2024-02-03","cited_by_count":5,"area":null},{"id":"2309.10523","title":"Edge-aware Feature Aggregation Network for Polyp Segmentation","created":"2023-09-19","cited_by_count":4,"area":null},{"id":"2401.12439","title":"MAST: Video Polyp Segmentation with a Mixture-Attention Siamese Transformer","created":"2024-01-23","cited_by_count":3,"area":null},{"id":"2405.07523","title":"Adaptation of Distinct Semantics for Uncertain Areas in Polyp Segmentation","created":"2024-05-13","cited_by_count":3,"area":null},{"id":"2409.08501","title":"PSTNet: Enhanced Polyp Segmentation with Multi-scale Alignment and Frequency Domain Integration","created":"2024-09-13","cited_by_count":2,"area":null},{"id":"2309.08234","title":"Efficient Polyp Segmentation Via Integrity Learning","created":"2023-09-15","cited_by_count":1,"area":null},{"id":"2502.03829","title":"Frequency Domain Enhanced U-Net for Low-Frequency Information-Rich Image Segmentation in Surgical and Deep-Sea Exploration Robots","created":"2025-02-06","cited_by_count":1,"area":null},{"id":"2604.14755","title":"ASGNet: Adaptive Spectrum Guidance Network for Automatic Polyp Segmentation","created":"2026-04-16","cited_by_count":1,"area":null},{"id":"2309.05987","title":"FLDNet: A Foreground-Aware Network for Polyp Segmentation Leveraging Long-Distance Dependencies","created":"2023-09-12","cited_by_count":0,"area":null},{"id":"2404.00726","title":"MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with its Application for Colonic Polyp Image Segmentation","created":"2024-03-31","cited_by_count":0,"area":null},{"id":"2410.01210","title":"Polyp-SES: Automatic Polyp Segmentation with Self-Enriched Semantic Model","created":"2024-10-02","cited_by_count":0,"area":null}],"next_cursor":null}