Polyp Segmentation Using Stair-structured U-Net

SHI Yonggang; LI Yi; ZHOU Zhiguo; ZHANG Yue; XIA Zhuoyan

doi:10.11999/JEIT210916

Volume 44 Issue 1

Jan. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(1): 39-47

SHI Yonggang, LI Yi, ZHOU Zhiguo, ZHANG Yue, XIA Zhuoyan. Polyp Segmentation Using Stair-structured U-Net[J]. Journal of Electronics & Information Technology, 2022, 44(1): 39-47. doi: 10.11999/JEIT210916

Citation:

SHI Yonggang, LI Yi, ZHOU Zhiguo, ZHANG Yue, XIA Zhuoyan. Polyp Segmentation Using Stair-structured U-Net[J]. Journal of Electronics & Information Technology, 2022, 44(1): 39-47. doi: 10.11999/JEIT210916

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Polyp Segmentation Using Stair-structured U-Net

doi: 10.11999/JEIT210916

School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

Funds: The National Natural Science Foundation of China (60971133, 61271112)

Received Date: 2021-09-01
Accepted Date: 2021-12-21
Rev Recd Date: 2021-12-21

Available Online: 2021-12-27

Publish Date: 2022-01-10

Abstract

Abstract

The precise segmentation of colon polyps plays a significant role in the diagnosis and treatment of colorectal cancer. The existing segmentation methods have generally artifacts and low segmentation accuracy. In this paper, Stair-structured U-Net (SU-Net) is proposed to segment polyp, using U-shaped structure. The Kronecker product is used to extend the standard atrous convolution kernel to keep more detail structrural features that are easily ignored. Stair-structured fusion module is applied to encompass effectively multi-scale features. The decoder introduces a convolutional reshaped upsampling module to generate pixel-level predictions. Experiments are performed on the Kvasir-SEG dataset and the CVC-EndoSceneStill dataset. The results show that the method proposed in this paper outperforms other polyp segmentation methods in Dice and Intersection-over-Union(IoU).
- Image segmentation,
- Colorectal polyp image,
- Atrous convolution,
- U-Net

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References(22)

References

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