Magnetic particle imaging deblurring with dual contrastive learning and adversarial framework

doi:10.1016/j.compbiomed.2023.107461

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Magnetic particle imaging deblurring with dual contrastive learning and adversarial framework
	Zhang, Jiaxin 1,2,10; Wei, Zechen 1,2,10; Wu, Xiangjun 7,8,9; Shang, Yaxin 6; Tian, Jie 1,2,3,4,7,8,9,10; Hui, Hui 1,2,5
刊名	COMPUTERS IN BIOLOGY AND MEDICINE
	2023-10-01
卷号	165 页码:11
关键词	Magnetic particle imaging Deblurring Unpaired data Contrastive learning Adversarial framework
ISSN号	0010-4825
DOI	10.1016/j.compbiomed.2023.107461
通讯作者	Tian, Jie(jie.tian@ia.ac.cn) ; Hui, Hui(hui.hui@ia.ac.cn)
英文摘要	Magnetic particle imaging (MPI) is an emerging medical imaging technique that has high sensitivity, contrast, and excellent depth penetration. In MPI, x-space is a reconstruction method that transforms the measured voltages into particle concentrations. The reconstructed native image can be modeled as a convolution of the magnetic particle concentration with a point-spread function (PSF). The PSF is one of the important parameters in deconvolution. However, accurately measuring or modeling the PSF in the hardware used for deconvolution is challenging due to the various environment and magnetic particle relaxation. The inaccurate PSF estimation may lead to the loss of the content structure of the MPI image, especially in low gradient fields. In this study, we developed a Dual Adversarial Network (DAN) with patch-wise contrastive constraint to deblur the MPI image. This method can overcome the limitations of unpaired data in data acquisition scenarios and remove the blur around the boundary more effectively than the common deconvolution method. We evaluated the performance of the proposed DAN model on simulated and real data. Experimental results confirmed that our model performs favorably against the deconvolution method that is mainly used for deblurring the MPI image and other GAN-based deep learning models.
资助项目	National Key Research and Development Program of China[2017YFA0700401] ; National Natural Science Foundation of China[62027901] ; National Natural Science Foundation of China[81827808] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81227901] ; Beijing Natural Science Foundation[JQ22023] ; CAS Youth Innovation Promotion Association[Y2022055]
WOS关键词	RECONSTRUCTION ; RESOLUTION
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Computer Science ; Engineering ; Mathematical & Computational Biology
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:001080561100001
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; CAS Youth Innovation Promotion Association
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53005]
专题	自动化研究所_中国科学院分子影像重点实验室
通讯作者	Tian, Jie; Hui, Hui
作者单位	1.Beijing Key Lab Mol Imaging, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 3.Beihang Univ, Sch Biol Sci & Med Engn, Beijing 100083, Peoples R China 4.Beihang Univ, Sch Engn Med, Beijing 100083, Peoples R China 5.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 6.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China 7.Beihang Univ, Sch Biol Sci & Med Engn, Beijing, Peoples R China 8.Beihang Univ, Sch Engn Med, Beijing, Peoples R China 9.Beihang Univ, Minist Ind & Informat Technol, Key Lab Big Data Based Precis Med, Beijing, Peoples R China 10.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Jiaxin,Wei, Zechen,Wu, Xiangjun,et al. Magnetic particle imaging deblurring with dual contrastive learning and adversarial framework[J]. COMPUTERS IN BIOLOGY AND MEDICINE,2023,165:11.
APA	Zhang, Jiaxin,Wei, Zechen,Wu, Xiangjun,Shang, Yaxin,Tian, Jie,&Hui, Hui.(2023).Magnetic particle imaging deblurring with dual contrastive learning and adversarial framework.COMPUTERS IN BIOLOGY AND MEDICINE,165,11.
MLA	Zhang, Jiaxin,et al."Magnetic particle imaging deblurring with dual contrastive learning and adversarial framework".COMPUTERS IN BIOLOGY AND MEDICINE 165(2023):11.