[1]LIU Guoqi,CHEN Zongyu,LIU Dong,et al.A small polyp objects network integrating boundary attention features[J].CAAI Transactions on Intelligent Systems,2024,19(5):1092-1101.[doi:10.11992/tis.202306025]
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A small polyp objects network integrating boundary attention features

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 19 Number of periods: 2024 5 Page number: 1092-1101 Column: 学术论文—机器学习 Public date: 2024-09-05
Title:
A small polyp objects network integrating boundary attention features
Author(s):
LIU Guoqi1; 2;  CHEN Zongyu1; 2;  LIU Dong1; 2;  CHANG Baofang1;  WANG Jiajia1; 2
1. College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China;
2. Henan Key Laboratory of Educational Artificial Intelligence and Personalized Learning, Henan Normal University, Xinxiang 453007, China
Keywords:
small polyp objects segmentation; Transformer; convolutional neural network; feature mining; attention mechanism; boundary attention; semantic information; global feature
CLC:
TP391
DOI:
10.11992/tis.202306025
Abstract:
Segmentation of small target lesion areas, such as polyps in colon images, is essential for the prevention and diagnosis of colorectal cancer. However, existing methods face two main limitations: either the global context information cannot be captured robustly or the fine-grained detail information cannot be fully mined. To address these issues, this study proposes TFB-Net, a feature mining network for small target polyps that integrates boundary attention. The network consists of three core modules: First, a Transformer is used to establish long-term dependencies and supplement global information. Second, the feature mining module is designed to further optimize and enhance the learned features. Finally, the boundary inversion attention module strengthens attention to the boundary semantic space, which consequently improves regional discrimination. Extensive experiments were conducted on five small polyp target datasets, and the results show that TFB-Net achieves superior segmentation performance.
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Last Update: 2024-09-05

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