Overview

Polyp segmentation studies how to outline colorectal polyps in colonoscopy images and video, helping clinicians identify lesions and assess their shape and extent. Common approaches include CNN encoder-decoder models such as U-Net, attention and transformer or state-space networks, and foundation-model features; video methods also use information from nearby frames. Current work explores boundary refinement, sparse-label learning, cross-dataset generalization, and compact models that can run in real time on clinical or edge hardware. A key tension is achieving reliable boundaries across imaging devices, centers, and occlusions while keeping evaluation comparable and inference efficient.

Latest papers

CardsList

23 papers2 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

  1. Polyp-VSSD: A Pre-trained Transformer with Local-Global Joint VSSD Decoding for Polyp Segmentation

    Oct 23, 2026Xiaobo Zhu, Shiwei Wu, Yu An +4Polyp SegmentationMedical Image Segmentation

  2. Lightweight Frame Compensation for Real-Time Polyp Segmentation under Frame Skipping

    Oct 22, 2026Weihao GaoPolyp SegmentationVideo Object Segmentation

  3. woma: a real-time foundation model and its fine-tuned models for endoscopy

    Sep 14, 2026Thang Tran, Lan DangEndoscopyMedical Imaging Foundation Models

  4. Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

    Sep 9, 2026Siddharth Gupta, Jitin SinglaPolyp SegmentationSegmentation Uncertainty Estimation

  5. InstEditSeg: Instruction-Driven Image Editing for Polyp and Skin Lesion Segmentation

    Sep 2, 2026Ziquan Liu, Zhewei Zhu, Xuyang ShiText-Guided Image SegmentationPolyp Segmentation

  6. CSG-Mamba: A Convolutional Scoring Gating Vision State Space Network for Endoscopic Polyp Segmentation

    Aug 14, 2026Yuliang Wang, Jiaqi Wu, Jiaye Song +1Polyp SegmentationMedical Image Segmentation

  7. PolypVision: A Three-Stage Hierarchical Deep Learning Framework for Classification and Segmentation of Colorectal Polyps

    Aug 11, 2026Hamidreza Bolhasani, Hamidreza Rastad, Amir Mohammad Akbari +4Medical Image ClassificationPolyp Segmentation

  8. QFedPolyp: A Communication- and Inference-Efficient Federated Learning Framework for Polyp Segmentation

    Jul 23, 2026Madan Baduwal, Priyanka PaudelPolyp SegmentationMedical Image Segmentation

  9. Induce to Empower: Improving Lightweight Baselines via Foundation Model Induction for Generalized Polyp Segmentation

    Jul 19, 2026Shivanshu Agnihotri, Snehashis Majhi, Deepak Ranjan Nayak +2Medical Imaging Foundation ModelsDomain Generalization

  10. Metrics or Mirage? An Audit of Evaluation Inconsistencies in Colonoscopy Polyp Segmentation Benchmarks

    Jul 9, 2026Aisha Urooj, Zain Ul Abdien, Neelu MadanPolyp SegmentationBenchmark Reproducibility

  11. Lightweight Polyp Segmentation via a Gain-Aware Prediction-Space Recursive Controller

    Jul 3, 2026Jiachi Zhang, Zhuoyu Wu, Quanjun Wang +2Polyp SegmentationMedical Image Segmentation

  12. RIGS-Refiner: Risk-Guided Recursive Refinement in Prediction Space for Colonoscopy Polyp Segmentation

    Jul 3, 2026Jiachi Zhang, Zhuoyu Wu, Wenqi FangPolyp SegmentationMedical Image Segmentation

  13. ARTEMIS: Agent-guided Reliability-aware Temporal Mask Evolution for Imperfectly Supervised Video Polyp Segmentation

    Jun 18, 2026Tong Wang, Siwen Wang, Yaolei Qi +4Video Object SegmentationSemi-Supervised Medical Image Segmentation

  14. Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation

    May 18, 2026Diego Adame, Fabian Vazquez, Jose A. Nunez +7MambaImage Segmentation

  15. DepthPolyp: Pseudo-Depth Guided Lightweight Segmentation for Real-Time Colonoscopy

    May 15, 2026Zhuoyu Wu, Wenhui Ou, Lexi Zhang +5EndoscopyImage Segmentation

  16. Sharpening Lightweight Models for Generalized Polyp Segmentation: A Boundary Guided Distillation from Foundation Models

    Apr 20, 2026Shivanshu Agnihotri, Snehashis Majhi, Deepak Ranjan NayakImage SegmentationVision Foundation Model Adaptation

  17. ASGNet: Adaptive Spectrum Guidance Network for Automatic Polyp Segmentation

    Apr 16, 2026Yanguang Sun, Hengmin Zhang, Jianjun Qian +2Medical Image AnalysisPolyp Segmentation

  18. Seeing Through the Tool: A Controlled Benchmark for Occlusion Robustness in Foundation Segmentation Models

    Apr 13, 2026Nhan Ho, Luu Le, Thanh-Huy Nguyen +3Amodal SegmentationImage Segmentation

  19. RPG-SAM: Reliability-Weighted Prototypes and Geometric Adaptive Threshold Selection for Training-Free One-Shot Polyp Segmentation

    Mar 8, 2026Weikun Lin, Yunhao Bai, Yan WangImage SegmentationPolyp Segmentation

  20. A multi-center analysis of deep learning methods for video polyp detection and segmentation

    Mar 4, 2026Noha Ghatwary, Pedro Chavarias Solano, Mohamed Ramzy Ibrahim +24Medical Image AnalysisPolyp Segmentation

  21. Polyp Segmentation Using Wavelet-Based Cross-Band Integration for Enhanced Boundary Representation

    Mar 4, 2026Haesung Oh, Jaesung LeeImage SegmentationPolyp Segmentation

  22. CMSA-Net: Causal Multi-scale Aggregation with Adaptive Multi-source Reference for Video Polyp Segmentation

    Feb 26, 2026Tong Wang, Yaolei Qi, Siwen Wang +3Causal AttentionPolyp Segmentation

  23. BiSe-Unet: A Lightweight Dual-path U-Net with Attention-refined Context for Real-time Medical Image Segmentation

    Feb 22, 2026M Iffat Hossain, Laura BrattainLightweight Neural NetworksMedical Image Segmentation