mlsanityData to 7 Oct 2026

Polyp Segmentation in Colonoscopy Images Using Fully Convolutional Network

arXiv 1802.00368 ↗First posted 1 Feb 2018eess.IVcited by 33

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Abstract (arXiv)

Colorectal cancer is a one of the highest causes of cancer-related death, especially in men. Polyps are one of the main causes of colorectal cancer and early diagnosis of polyps by colonoscopy could result in successful treatment. Diagnosis of polyps in colonoscopy videos is a challenging task due to variations in the size and shape of polyps. In this paper we proposed a polyp segmentation method based on convolutional neural network. Performance of the method is enhanced by two strategies. First, we perform a novel image patch selection method in the training phase of the network. Second, in the test phase, we perform an effective post processing on the probability map that is produced by the network. Evaluation of the proposed method using the CVC-ColonDB database shows that our proposed method achieves more accurate results in comparison with previous colonoscopy video-segmentation methods.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Feb 2018.

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Citing papers per year: 2021: 12; 2022: 6; 2023: 6; 2024: 7; 2025: 2.

33 papers.

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  1. 2021Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformerscited by 159
  2. 2021Shallow Attention Network for Polyp Segmentationcited by 107
  3. 2022Video Polyp Segmentation: A Deep Learning Perspectivecited by 81
  4. 2021Automatic Polyp Segmentation via Multi-scale Subtraction Networkcited by 77
  5. 2021Progressively Normalized Self-Attention Network for Video Polyp Segmentationcited by 75
  6. 2021HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPScited by 71
  7. 2023Adaptive Context Selection for Polyp Segmentationcited by 47
  8. 2021A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentationcited by 41
  9. 2023Lesion-aware Dynamic Kernel for Polyp Segmentationcited by 39
  10. 2021Enhanced U-Net: A Feature Enhancement Network for Polyp Segmentationcited by 33
  11. 2022Camouflaged Object Detection via Context-aware Cross-level Fusioncited by 32
  12. 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challengecited by 27
21 more
  1. 2023TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testingcited by 26
  2. 2021Duplex Contextual Relation Network for Polyp Segmentationcited by 22
  3. 2021Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopycited by 20
  4. 2023A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trendscited by 12
  5. 2022BoxPolyp:Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotationscited by 10
  6. 2021Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentationcited by 7
  7. 2024Segmenting Medical Images: From UNet to Res-UNet and nnUNetcited by 6
  8. 2024Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Surveycited by 5
  9. 2022BoxShrink: From Bounding Boxes to Segmentation Maskscited by 4
  10. 2024Multi-scale Information Sharing and Selection Network with Boundary Attention for Polyp Segmentationcited by 3
  11. 2023Cooperation Learning Enhanced Colonic Polyp Segmentation Based on Transformer-CNN Fusioncited by 2
  12. 2023Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesionscited by 2
  13. 2024Multi-Layer Dense Attention Decoder for Polyp Segmentationcited by 2
  14. 2025PolypFlow: Reinforcing Polyp Segmentation with Flow-Driven Dynamicscited by 2
  15. 2021Supervised Segmentation with Domain Adaptation for Small Sampled Orbital CT Imagescited by 1
  16. 2021Colorectal Polyp Detection in Real-world Scenario: Design and Experiment Studycited by 0
  17. 2022Rethinking the transfer learning for FCN based polyp segmentation in colonoscopycited by 0
  18. 2024BetterNet: An Efficient CNN Architecture with Residual Learning and Attention for Precision Polyp Segmentationcited by 0
  19. 2024ODC-SA Net: Orthogonal Direction Enhancement and Scale Aware Network for Polyp Segmentationcited by 0
  20. 2024CRIS: Collaborative Refinement Integrated with Segmentation for Polyp Segmentationcited by 0
  21. 2025PVTAdpNet: Polyp Segmentation using Pyramid vision transformer with a novel Adapter blockcited by 0