Development of a functional magnetic resonance imaging simulator for modeling realistic rigid-body motion artifacts
Development of a functional magnetic resonance imaging simulator for modeling realistic rigid-body motion artifacts
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DOI：
10.1002/mrm.20939
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发表时间：
2006-08-01
影响因子：
3.3
通讯作者：
Jenkinson, Mark
中科院分区：
文献类型：
--
作者：
Drobnjak, Ivana;Gavaghan, David;Jenkinson, Mark
功能性磁共振成像（functional magnetic resonance imaging，FMRI）是一种非侵入性的活体脑功能成像方法。然而，在功能磁共振成像实验中产生的图像是不完美的，并包含一些污染数据的伪影。这些伪影包括刚体运动效应、均匀性中的B-0场、化学位移和涡流。为了研究这些伪影，最终目标是最大限度地减少或完全消除它们，我们建立了FMR图像采集过程的计算模型，可以模拟所有上述伪影。本文综述了功能磁共振成像模拟器的发展。模拟器使用Bloch方程以及对象（大脑）的几何定义和BOLD激活的变化T-2（*）模型。此外，它模拟刚体运动的对象通过求解布洛赫方程的给定的运动参数，定义为一个对象在时间上连续移动，包括在读出周期，这是一种新的方法在该地区的MRI计算机模拟。通过这种方法，可以以受控和精确的方式模拟FMRI数据中各种刚体运动伪影的全部影响（例如自旋历史效应，B-0-运动相互作用和扫描内运动模糊），从而制定和测试用于减少它们的算法。
Functional magnetic resonance imaging (FMRI) is a noninvasive method of imaging brain function in vivo. However, images produced in FMRI experiments are imperfect and contain several artifacts that contaminate the data. These artifacts include rigid-body motion effects, B-0-field in homogeneities, chemical shift, and eddy currents. To investigate these artifacts, with the eventual aim of minimizing or removing them completely, a computational model of the FMR image acquisition process was built that can simulate all of the above-mentioned artifacts. This paper gives an overview of the development of the FMRI simulator. The simulator uses the Bloch equations together with a geometric definition of the object (brain) and a varying T-2(*) model for the BOLD activations. Furthermore, it simulates rigid-body motion of the object by solving Bloch equations for given motion parameters that are defined for an object moving continuously in time, including during the read-out period, which is a novel approach in the area of MRI computer simulations. With this approach it is possible, in a controlled and precise way, to simulate the full effects of various rigid-body motion artifacts in FMRI data (e.g. spin-history effects, B-0-motion interaction, and within-scan motion blurring) and therefore formulate and test algorithms for their reduction.