CASIA OpenIR  > 中国科学院分子影像重点实验室
BSS-TFNet: Attention-Enhanced Background Signal Suppression Network for Time-Frequency Spectrum in Magnetic Particle Imaging
Wei, Zechen1,2; Liu, Yanjun3,4,5; Zhu, Tao1,2; Yang, Xin1,2; Tian, Jie4,5,6; Hui, Hui1,2
Source PublicationIEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
ISSN2471-285X
2023-12-12
Pages15
Abstract

Magnetic particle imaging (MPI) is a rapidly developing medical imaging modality, which uses the nonlinear response of superparamagnetic iron oxide nanoparticles to the applied magnetic field to image their spatial distribution. Background signal is the main source of artifacts in MPI, which mainly includes harmonic interference and Gaussian noise. For different sources of noise, the existing methods directly process the time domain signal to achieve signal enhancement or construct system function by frequency domain signal to obtain high-quality reconstructed images. However, due to the randomness and variety of the background signal, the existing methods fail to eliminate all kinds of noise at the same time, especially when the noise is nonlinear. In this work, we proposed a deep learning method adopting self-attention mechanism, which can effectively suppress different levels of harmonic interference and Gaussian noise simultaneously. Our method deals with the two-dimensional time-frequency spectrum acquired by short-time Fourier transform from the temporal signal, learning global features and local features between time and frequency domain through the network, to achieve the purpose of reducing background noise. The performance of our method is analyzed via simulation experiments and imaging experiments performed with an in-house MPI scanner, which shows that our method can effectively suppress background signals and obtain high-quality MPI images.

KeywordMagnetic particle imaging deep learning self-attention mechanism time-frequency spectrum background signal
DOI10.1109/TETCI.2023.3337342
WOS KeywordRECONSTRUCTION ; SENSITIVITY ; RESOLUTION ; TRACER
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China
Funding OrganizationNational Key Research and Development Program of China
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:001134429900001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Sub direction classificationAI芯片与智能计算
planning direction of the national heavy laboratory态势鲁棒认知
Paper associated data
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/54869
Collection中国科学院分子影像重点实验室
Corresponding AuthorYang, Xin; Hui, Hui
Affiliation1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.Beihang Univ, Key Lab Big Data Based Precis Med, Minist Ind & Informat Technol Peoples Republ China, Beijing 100190, Peoples R China
4.Beihang Univ, Sch Engn Med, Beijing 100190, Peoples R China
5.Beihang Univ, Sch Biol Sci & Med Engn, Beijing 100190, Peoples R China
6.Beihang Univ, Inst Automat, Minist Ind & Informat Technol Peoples Republ China, Key Lab Big Data Based Precis Med,CAS Key Lab Mol, Beijing 100190, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wei, Zechen,Liu, Yanjun,Zhu, Tao,et al. BSS-TFNet: Attention-Enhanced Background Signal Suppression Network for Time-Frequency Spectrum in Magnetic Particle Imaging[J]. IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE,2023:15.
APA Wei, Zechen,Liu, Yanjun,Zhu, Tao,Yang, Xin,Tian, Jie,&Hui, Hui.(2023).BSS-TFNet: Attention-Enhanced Background Signal Suppression Network for Time-Frequency Spectrum in Magnetic Particle Imaging.IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE,15.
MLA Wei, Zechen,et al."BSS-TFNet: Attention-Enhanced Background Signal Suppression Network for Time-Frequency Spectrum in Magnetic Particle Imaging".IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE (2023):15.
Files in This Item: Download All
File Name/Size DocType Version Access License
BSS-TFNet_Attention-(6094KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wei, Zechen]'s Articles
[Liu, Yanjun]'s Articles
[Zhu, Tao]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wei, Zechen]'s Articles
[Liu, Yanjun]'s Articles
[Zhu, Tao]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wei, Zechen]'s Articles
[Liu, Yanjun]'s Articles
[Zhu, Tao]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: BSS-TFNet_Attention-Enhanced_Background_Signal_Suppression_Network_for_Time-Frequency_Spectrum_in_Magnetic_Particle_Imaging.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.