Anisotropic edge-preserving network for resolution enhancement in unidirectional Cartesian magnetic particle imaging

doi:10.1088/1361-6560/acb584

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

	Anisotropic edge-preserving network for resolution enhancement in unidirectional Cartesian magnetic particle imaging
	Shang,Yaxin 6; Liu,Jie 6; Liu,Yanjun 5; Zhang,Bo 5; Wu,Xiangjun 5; Zhang,Liwen 3,4; Tong,Wei 2; Hui,Hui 3,4; Tian,Jie 1,4
刊名	Physics in Medicine & Biology
	2023-02-10
卷号	68 期号:4
关键词	deep learning magnetic particle imaging point spread function superparamagnetic iron oxide nanoparticles unidirectional Cartesian
DOI	10.1088/1361-6560/acb584
通讯作者	Zhang,Liwen() ; Tian,Jie()
英文摘要	Abstract 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.
语种	英语
出版者	IOP Publishing
WOS记录号	IOP:PMB_68_4_045014
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/51821]
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	Zhang,Liwen; Tian,Jie
作者单位	1.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, 100191, People’s Republic of China 2.Senior Department of Cardiology, the Sixth Medical Center of PLA General Hospital, Beijing, 100036, People’s Republic of China 3.The University of Chinese Academy of Sciences, Beijing, 100080, People’s Republic of China 4.CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, People’s Republic of China 5.School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, People’s Republic of China 6.School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, People’s Republic of China
推荐引用方式 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).