Case Center for Imaging Research, Department of Radiology and Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106 USA.
IEEE Trans Med Imaging. 2010 Feb;29(2):339-49. doi: 10.1109/TMI.2009.2029854. Epub 2009 Aug 25.
It is a well-known property in Fourier transform magnetic resonance imaging (MRI) that rigid body translational motion in image space results in linear phase accumulation in k -space. This work describes Multiple Overlapping k-space Junctions for Investigating Translating Objects (MOJITO), a correction scheme based on phase differences at trajectory intersections caused by 2-D alterations in the position of an object during MR imaging. The algorithm allows both detection and correction of motion artifacts caused by 2-D rigid body translational motion. Although similar in concept to navigator echoes, MOJITO does not require a repeating path through k-space, uses k-space data from a broader region of k -space, and uses the repeated data in image reconstruction; this provides the potential for a highly efficient self-navigating motion correction method. Here, the concept and theoretical basis of MOJITO is demonstrated using the continuous sampling BOWTIE trajectory in simulation and MR experiments. This particular trajectory is selected since it is well suited for such an algorithm due to numerous trajectory intersections. Specifically, the validity of the technique in the presence of noise and off-resonance effects is demonstrated through simulation.
在傅里叶变换磁共振成像(MRI)中,众所周知的是,图像空间中的刚体平移运动会导致 k 空间中的线性相位累积。这项工作描述了用于研究平移物体的多个重叠 k 空间交点(MOJITO),这是一种基于物体在磁共振成像过程中位置的二维变化引起的轨迹交点处相位差的校正方案。该算法允许检测和校正由于二维刚体平移运动引起的运动伪影。尽管在概念上与导航回波相似,但 MOJITO 不需要通过 k 空间重复路径,而是使用 k 空间中更广泛区域的 k 空间数据,并在图像重建中使用重复数据;这为高效的自导航运动校正方法提供了潜力。在这里,使用模拟和 MR 实验中的连续采样 BOWTIE 轨迹演示了 MOJITO 的概念和理论基础。选择这种特殊的轨迹是因为由于存在许多轨迹交点,因此非常适合这种算法。具体来说,通过模拟证明了该技术在存在噪声和失谐效应时的有效性。