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MEGANet-W: A Wavelet-Driven Edge-Guided Attention Framework for Weak Boundary Polyp Detection

arXiv 2507.02668 ↗First posted 3 Jul 2025eess.IV cs.CVcited by 0

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Abstract (arXiv)

Colorectal polyp segmentation is critical for early detection of colorectal cancer, yet weak and low contrast boundaries significantly limit automated accuracy. Existing deep models either blur fine edge details or rely on handcrafted filters that perform poorly under variable imaging conditions. We propose MEGANet-W, a Wavelet Driven Edge Guided Attention Network that injects directional, parameter free Haar wavelet edge maps into each decoder stage to recalibrate semantic features. The key novelties of MEGANet-W include a two-level Haar wavelet head for multi-orientation edge extraction; and Wavelet Edge Guided Attention (W-EGA) modules that fuse wavelet cues with boundary and input branches. On five public polyp datasets, MEGANet-W consistently outperforms existing methods, improving mIoU by up to 2.3% and mDice by 1.2%, while introducing no additional learnable parameters. This approach improves reliability in difficult cases and offers a robust solution for medical image segmentation tasks requiring precise boundary detection.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 20 of its 42 references that are in the map. First posted on arXiv 3 Jul 2025.

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20 of 42 references.

References · 20

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2017Squeeze-and-Excitation Networkscited by 4,763
  3. 2018CBAM: Convolutional Block Attention Modulecited by 2,463
  4. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
  5. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 588
  6. 2020PraNet: Parallel Reverse Attention Network for Polyp Segmentationcited by 460
  7. 2021TransFuse: Fusing Transformers and CNNs for Medical Image Segmentationcited by 258
  8. 2016A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Imagescited by 220
  9. 2016A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstructioncited by 87
  10. 2021Automatic Polyp Segmentation via Multi-scale Subtraction Networkcited by 77
  11. 2023Lesion-aware Dynamic Kernel for Polyp Segmentationcited by 39
  12. 2018Wavelet Convolutional Neural Networkscited by 29
8 more
  1. 2023MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentationcited by 28
  2. 2023A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trendscited by 12
  3. 2020WaveSNet: Wavelet Integrated Deep Networks for Image Segmentationcited by 10
  4. 2023Polyper: Boundary Sensitive Polyp Segmentationcited by 8
  5. 2024Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Surveycited by 5
  6. 2023SegT: A Novel Separated Edge-guidance Transformer Network for Polyp Segmentationcited by 3
  7. 2024Multi-scale Information Sharing and Selection Network with Boundary Attention for Polyp Segmentationcited by 3
  8. 2024EPPS: Advanced Polyp Segmentation via Edge Information Injection and Selective Feature Decouplingcited by 1

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