High Spatiotemporal Resolution Magnetic Resonance Thermometry Based on Partially Separable Theory.

	High Spatiotemporal Resolution Magnetic Resonance Thermometry Based on Partially Separable Theory.
	Xie, Guoxi; Shi, Caiyun; Liu, Xin; Chen, MinDong, Ying; Zhang, Yongqin; Su, Shi; Zhang, Xiaoyong
刊名	JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
	2017
文献子类	期刊论文
英文摘要	It is very difficult to achieve high spatiotemporal resolution MR thermometry (MRT) due to the slow sampling speed of magnetic resonance (MR). To address this issue, we presented a novel method to improve the spatial and temporal resolutions of MRT by exploiting data redundancy based on partially separable (PS) theory. After high spatioternporal resolution images with accurate phase information were reconstructed by the PS theory, high spatiotemporal resolution MRT achieved using a standard proton resonance frequency (PRF) shift technique. The simulation, phantom and in vivo experiment results showed that the proposed method could accurately estimate dynamic temperature change with high spatiotemporal resolution. In the in vivo experiment, the temporal resolution can reach to 250 ms in the case of spatial resolution with 1.2 x 1.2 mm(2). These results demonstrated the feasibility of the proposed method for high spatiotemporal resolution MRT.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12055]
专题	深圳先进技术研究院_医工所
作者单位	JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
推荐引用方式 GB/T 7714	Xie, Guoxi,Shi, Caiyun,Liu, Xin,et al. High Spatiotemporal Resolution Magnetic Resonance Thermometry Based on Partially Separable Theory.[J]. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS,2017.
APA	Xie, Guoxi.,Shi, Caiyun.,Liu, Xin.,Chen, MinDong, Ying.,Zhang, Yongqin.,...&Zhang, Xiaoyong.(2017).High Spatiotemporal Resolution Magnetic Resonance Thermometry Based on Partially Separable Theory..JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS.
MLA	Xie, Guoxi,et al."High Spatiotemporal Resolution Magnetic Resonance Thermometry Based on Partially Separable Theory.".JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS (2017).