mlsanityData to 7 Oct 2026

Polyp SAM 2: Advancing Zero shot Polyp Segmentation in Colorectal Cancer Detection

arXiv 2408.05892 ↗First posted 12 Aug 2024eess.IV cs.CV cs.LGcited by 8

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Abstract (arXiv)

Polyp segmentation plays a crucial role in the early detection and diagnosis of colorectal cancer. However, obtaining accurate segmentations often requires labor-intensive annotations and specialized models. Recently, Meta AI Research released a general Segment Anything Model 2 (SAM 2), which has demonstrated promising performance in several segmentation tasks. In this manuscript, we evaluate the performance of SAM 2 in segmenting polyps under various prompted settings. We hope this report will provide insights to advance the field of polyp segmentation and promote more interesting work in the future. This project is publicly available at https://github.com/ sajjad-sh33/Polyp-SAM-2.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 41 of its 54 references that are in the map. First posted on arXiv 12 Aug 2024.

Builds on

41 of 54 references.

References · 41

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2023Segment Anythingcited by 8,158
  3. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  4. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 588
  5. 2019UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentationcited by 583
  6. 2020PraNet: Parallel Reverse Attention Network for Polyp Segmentationcited by 460
  7. 2023Segment Anything in Medical Imagescited by 226
  8. 2016A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Imagescited by 220
  9. 2019ResUNet++: An Advanced Architecture for Medical Image Segmentationcited by 211
  10. 2022UNeXt: MLP-based Rapid Medical Image Segmentation Networkcited by 185
  11. 2023Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imagingcited by 161
  12. 2021Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformerscited by 159
29 more
  1. 2024Medical SAM 2: Segment medical images as video via Segment Anything Model 2cited by 151
  2. 2023Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applicationscited by 121
  3. 2021Shallow Attention Network for Polyp Segmentationcited by 107
  4. 2023SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentationcited by 103
  5. 2023Can SAM Segment Anything? When SAM Meets Camouflaged Object Detectioncited by 99
  6. 2021Context-aware Cross-level Fusion Network for Camouflaged Object Detectioncited by 86
  7. 2021Automatic Polyp Segmentation via Multi-scale Subtraction Networkcited by 77
  8. 2021HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPScited by 71
  9. 2023Polyp-SAM: Transfer SAM for Polyp Segmentationcited by 64
  10. 2021A multi-centre polyp detection and segmentation dataset for generalisability assessmentcited by 63
  11. 2021UACANet: Uncertainty Augmented Context Attention for Polyp Segmentationcited by 61
  12. 2023SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Modelcited by 61
  13. 2023Can SAM Segment Polyps?cited by 59
  14. 2022Stepwise Feature Fusion: Local Guides Globalcited by 56
  15. 2023How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Imagescited by 53
  16. 2023Adaptive Context Selection for Polyp Segmentationcited by 47
  17. 2024Segment Anything in Medical Images and Videos: Benchmark and Deploymentcited by 42
  18. 2022Feature Aggregation and Propagation Network for Camouflaged Object Detectioncited by 40
  19. 2023Lesion-aware Dynamic Kernel for Polyp Segmentationcited by 39
  20. 2021Enhanced U-Net: A Feature Enhancement Network for Polyp Segmentationcited by 33
  21. 2024Segment anything model 2: an application to 2D and 3D medical imagescited by 27
  22. 2023TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testingcited by 26
  23. 2023SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathologycited by 26
  24. 2021Duplex Contextual Relation Network for Polyp Segmentationcited by 22
  25. 2023Polyp-SAM++: Can A Text Guided SAM Perform Better for Polyp Segmentation?cited by 22
  26. 2024Interactive 3D Medical Image Segmentation with SAM 2cited by 17
  27. 2024Biomedical SAM 2: Segment Anything in Biomedical Images and Videoscited by 14
  28. 2024ASPS: Augmented Segment Anything Model for Polyp Segmentationcited by 12
  29. 2024Polyp-DAM: Polyp segmentation via depth anything modelcited by 5

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Cited by year

Citing papers per year: 2024: 3; 2025: 5.

8 papers.

  1. 2024Unleashing the Potential of SAM2 for Biomedical Images and Videos: A Surveycited by 14
  2. 2025SAM2 for Image and Video Segmentation: A Comprehensive Surveycited by 13
  3. 2024When SAM2 Meets Video Camouflaged Object Segmentation: A Comprehensive Evaluation and Adaptationcited by 11
  4. 2025CamSAM2: Segment Anything Accurately in Camouflaged Videoscited by 7
  5. 2024Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Modelcited by 6
  6. 2025Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation Modelscited by 1
  7. 2025HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priorscited by 1
  8. 2025Towards Better Ultrasound Video Segmentation Foundation Model: An Empirical study on SAM2 Finetuning from Data Perspectivecited by 0