中文版 | English
Title

Fourier Channel Attention Powered Lightweight Network for Image Segmentation

Author
Publication Years
2023
DOI
Source Title
ISSN
2168-2372
EISSN
2168-2372
Volume11Pages:252-260
Abstract
The accuracy of image segmentation is critical for quantitative analysis. We report a lightweight network FRUNet based on the U-Net, which combines the advantages of Fourier channel attention (FCA Block) and Residual unit to improve the accuracy. FCA Block automatically assigns the weight of the learned frequency information to the spatial domain, paying more attention to the precise high-frequency information of diverse biomedical images. While FCA is widely used in image super-resolution with residual network backbones, its role in semantic segmentation is less explored. Here we study the combination of FCA and U-Net, the skip connection of which can fuse the encoder information with the decoder. Extensive experimental results of FRUNet on three public datasets show that the method outperforms other advanced medical image segmentation methods in terms of using fewer network parameters and improved accuracy. It excels in pathological section segmentation of nuclei and glands.
Keywords
URL[Source Record]
Language
English
SUSTech Authorship
First
Scopus EID
2-s2.0-85151537522
Data Source
Scopus
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10086528
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/524264
DepartmentDepartment of Biomedical Engineering
Affiliation
Department of Biomedical Engineering, UTS-SUStech Joint Research Centre for Biomedical Materials and Devices, Southern University of Science and Technology, Shenzhen, Guangdong, China
First Author AffilicationDepartment of Biomedical Engineering
First Author's First AffilicationDepartment of Biomedical Engineering
Recommended Citation
GB/T 7714
Zou,Fu,Liu,Yuanhua,Chen,Zelyu,et al. Fourier Channel Attention Powered Lightweight Network for Image Segmentation[J]. IEEE Journal of Translational Engineering in Health and Medicine,2023,11:252-260.
APA
Zou,Fu,Liu,Yuanhua,Chen,Zelyu,Zhanghao,Karl,&Jin,Dayong.(2023).Fourier Channel Attention Powered Lightweight Network for Image Segmentation.IEEE Journal of Translational Engineering in Health and Medicine,11,252-260.
MLA
Zou,Fu,et al."Fourier Channel Attention Powered Lightweight Network for Image Segmentation".IEEE Journal of Translational Engineering in Health and Medicine 11(2023):252-260.
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