MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation
University of Arkansas at Fayetteville · Vietnam National University Ho Chi Minh City
Abstract
Efficient polyp segmentation in healthcare plays a critical role in enabling early diagnosis of colorectal cancer. However, the segmentation of polyps presents numerous challenges, including the intricate distribution of backgrounds, variations in polyp sizes and shapes, and indistinct boundaries. Defining the boundary between the foreground (i.e. polyp itself) and the background (surrounding tissue) is difficult. To mitigate these challenges, we propose Multi-Scale Edge-Guided Attention Network (MEGANet) tailored specifically for polyp segmentation within colonoscopy images. This network draws inspiration from the fusion of a classical edge detection technique with an attention mechanism. By combining these…
Citation impact
- FWCI
- 41.74
- Percentile
- 100%
- References
- 40
Authors
5Topics & keywords
- Computer science
- Scale (ratio)
- Enhanced Data Rates for GSM Evolution
- Boundary (topology)
- Segmentation
- Image segmentation
- Artificial intelligence
- Computer vision