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MRI梯度预加重模块的分时复用设计 被引量:4

A Time-Division Multiplexing Design for Gradient Preemphasis Module in Magnetic Resonance Imaging Scanner
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摘要 为获得更优的成像质量和更快的成像速度,磁共振成像(MRI)系统的梯度预加重模块需要具有更多的补偿通道和调节参数,常规预加重模块的设计方案使现场可编程门阵列(FPGA)面临巨大的资源消耗.为解决高性能梯度预加重模块的资源消耗大的问题,本文提出了一种基于分时复用技术的梯度预加重实现方案,以常规方案1/44的资源实现了11通道×4组参数的梯度预加重模块.将该模块用于0.35 T MRI系统,测试了补偿前后的涡流曲线和磁共振图像,结果表明该模块有效降低了系统的涡流,减小了磁共振图像中的涡流伪影. In magnetic resonance imaging(MRI),a gradient preemphasis module with more compensation channels and adjustable parameters is often desired for better imaging quality and faster imaging speed.With the conventional design,however,a high performance preemphasis module often requires high resource consumption such that the field programmable gate array(FPGA)may encounter huge resource overhead.In this study,a new gradient preemphasis implementation scheme based on time-division multiplexing was proposed.With the new design,an 11 channels×4 sets of parameters implementation could be achieved with only 1/44 of the resources required by the conventional scheme.To test the performance of the new implementation,eddy current curves and magnetic resonance images before and after preemphasis compensation were measured on a 0.35 T scanner and compared.The results demonstrated that the module could effectively reduce eddy currents and related artifacts on the images.
作者 黄朝晖 张志 陈黎 陈俊飞 张震 陈方 刘朝阳 HUANG Zhao-hui;ZHANG Zhi;CHEN Li;CHEN Jun-fei;ZHANG Zhen;CHEN Fang;LIU Chao-yang(State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics,National Center for Magnetic Resonance in Wuhan,CAS Key Laboratory of Bio-Magnetic Resonance Analysis(Wuhan Institute of Physics and Mathematics,Chinese Academy of Sciences),Wuhan 430071,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处 《波谱学杂志》 CAS CSCD 北大核心 2018年第4期465-474,共10页 Chinese Journal of Magnetic Resonance
基金 国家重大科研装备研制项目(ZDYZ2010-2) 国家重大科研仪器研制项目(81627901) 国家自然科学基金青年科学基金资助项目(11705274) 中国科学院科研装备研制项目(YZ201677,YZ201551).
关键词 磁共振成像(MRI) 现场可编程门阵列(FPGA) 梯度预加重 分时复用 magnetic resonance imaging(MRI) field programmable gate array(FPGA) gradient preemphasis time-division multiplexing
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