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). |
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