CASIA OpenIR  > 中国科学院分子影像重点实验室
Anisotropic edge-preserving network for resolution enhancement in unidirectional Cartesian magnetic particle imaging
Shang,Yaxin1; Liu,Jie1; Liu,Yanjun2; Zhang,Bo2; Wu,Xiangjun2; Zhang,Liwen3,4; Tong,Wei5; Hui,Hui3,4; Tian,Jie3,6
Source PublicationPhysics in Medicine & Biology
2023-02-10
Volume68Issue:4
Corresponding AuthorZhang,Liwen() ; Tian,Jie()
AbstractAbstract Objective. Magnetic particle imaging (MPI) is a novel imaging modality. It is crucial to acquire accurate localization of the superparamagnetic iron oxide nanoparticles distributions in MPI. However, the spatial resolution of unidirectional Cartesian trajectory MPI exhibits anisotropy, which blurs the boundaries of MPI images and makes precise localization difficult. In this paper, we propose an anisotropic edge-preserving network (AEP-net) to alleviate the anisotropic resolution of MPI. Methods. AEP-net resolve the resolution anisotropy by constructing an asymmertic convolution. To recover the edge information, we design the uncertainty region module. In addition, we evaluated the performance of the proposed AEP-net model by using simulations and experimental data. Results. The results show that the AEP-net model alleviates the anisotropy of the unidirectional Cartesian trajectory and preserves edge details in the MPI image. By comparing the visualization results and the metrics, we demonstrate that our method is superior to other methods. Significance. The proposed method produces accurate visualization in unidirectional Cartesian devices and promotes accurate quantization, which promote the biomedical applications using MPI.
Keyworddeep learning magnetic particle imaging point spread function superparamagnetic iron oxide nanoparticles unidirectional Cartesian
DOI10.1088/1361-6560/acb584
Language英语
WOS IDIOP:pmb_68_4_045014
PublisherIOP Publishing
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/51822
Collection中国科学院分子影像重点实验室
Corresponding AuthorZhang,Liwen; Tian,Jie
Affiliation1.School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, People’s Republic of China
2.School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, People’s Republic of China
3.CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, People’s Republic of China
4.The University of Chinese Academy of Sciences, Beijing, 100080, People’s Republic of China
5.Senior Department of Cardiology, the Sixth Medical Center of PLA General Hospital, Beijing, 100036, People’s Republic of China
6.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, 100191, People’s Republic of China
Recommended Citation
GB/T 7714
Shang,Yaxin,Liu,Jie,Liu,Yanjun,et al. Anisotropic edge-preserving network for resolution enhancement in unidirectional Cartesian magnetic particle imaging[J]. Physics in Medicine & Biology,2023,68(4).
APA Shang,Yaxin.,Liu,Jie.,Liu,Yanjun.,Zhang,Bo.,Wu,Xiangjun.,...&Tian,Jie.(2023).Anisotropic edge-preserving network for resolution enhancement in unidirectional Cartesian magnetic particle imaging.Physics in Medicine & Biology,68(4).
MLA Shang,Yaxin,et al."Anisotropic edge-preserving network for resolution enhancement in unidirectional Cartesian magnetic particle imaging".Physics in Medicine & Biology 68.4(2023).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Shang,Yaxin]'s Articles
[Liu,Jie]'s Articles
[Liu,Yanjun]'s Articles
Baidu academic
Similar articles in Baidu academic
[Shang,Yaxin]'s Articles
[Liu,Jie]'s Articles
[Liu,Yanjun]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Shang,Yaxin]'s Articles
[Liu,Jie]'s Articles
[Liu,Yanjun]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

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