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首页> 外文期刊>American journal of applied sciences >A Model for Resolving Flow Parameters for MRI-Neuroimaging Application
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A Model for Resolving Flow Parameters for MRI-Neuroimaging Application

机译:MRI神经成像应用的流量参数解析模型

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The functionality of recent neuroimaging using the MRI machine has generated errors which are peculiar to all kinds of MRI processes. Though hardwares are used to complement the MRI process, the problems are not completely solved due to its fundamental errors. The fundamental error is in the exclusion of molecular interaction in the ab-initio Bloch NMR. A new mathematical concept was applied to resolve the functionality problems. The Bloch NMR features and the molecular interactions were fused via a Hamiltonian process. The simulation obtained reveals the tendencies of signals to diverge. This concept was summarized via a concept known as the signal loss factor 'E'. The signal loss factor 'E' exists when spin velocity fluctuates due to compartmental boundaries in the macromolecular sites. We propose that the fundamental error-signal loss factor 'E', is a vital factor required for clinical diagnosis of cognitive impairment.
机译:最近使用MRI机器进行神经成像的功能已产生各种MRI过程特有的错误。尽管使用硬件来补充MRI过程,但由于其基本错误,这些问题并未完全解决。基本错误是从头计算布洛赫NMR中排除了分子相互作用。应用了新的数学概念来解决功能性问题。 Bloch NMR特征和分子相互作用是通过汉密尔顿过程融合的。获得的仿真揭示了信号发散的趋势。通过称为信号损耗因子“ E”的概念概括了这一概念。当自旋速度由于大分子位点中的区室边界而波动时,存在信号损耗因子“ E”。我们建议,基本错误信号丢失因子“ E”是认知障碍临床诊断所需的重要因素。

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