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Test Suite for Image-Based Motion Estimation of the Brain and Tongue

机译:基于图像的大脑和舌头运动估计的测试套件

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Noninvasive analysis of motion has important uses as qualitative markers for organ function and to validate biomechanical computer simulations relative to experimental observations. Tagged MRI is considered the gold standard for noninvasive tissue motion estimation in the heart, and this has inspired multiple studies focusing on other organs, including the brain under mild acceleration and the tongue during speech. As with other motion estimation approaches, using tagged MRI to measure 3D motion includes several preprocessing steps that affect the quality and accuracy of estimation. Benchmarks, or test suites, are datasets of known geometries and displacements that act as tools to tune tracking parameters or to compare different motion estimation approaches. Because motion estimation was originally developed to study the heart, existing test suites focus on cardiac motion. However, many fundamental differences exist between the heart and other organs, such that parameter tuning (or other optimization) with respect to a cardiac database may not be appropriate. Therefore, the objective of this research was to design and construct motion benchmarks by adopting an 'image synthesis' test suite to study brain deformation due to mild rotational accelerations, and a benchmark to model motion of the tongue during speech. To obtain a realistic representation of mechanical behavior, kinematics were obtained from finite-element (FE) models. These results were combined with an approximation of the acquisition process of tagged MRI (including tag generation, slice thickness, and inconsistent motion repetition). To demonstrate an application of the presented methodology, the effect of motion inconsistency on synthetic measurements of head-brain rotation and deformation was evaluated. The results indicated that acquisition inconsistency is roughly proportional to head rotation estimation error. Furthermore, when evaluating non-rigid deformation, the results suggest that inconsistent motion can yield 'ghost' shear strains, which are a function of slice acquisition viability as opposed to a true physical deformation.
机译:运动的非侵入性分析具有重要的用途,可以作为器官功能的定性标记,并可以验证相对于实验观察结果的生物力学计算机模拟。标记MRI被认为是心脏无创组织运动估计的金标准,这激发了针对其他器官的多项研究,这些器官包括轻度加速下的大脑和言语中的舌头。与其他运动估计方法一样,使用标记的MRI来测量3D运动包括一些影响估计质量和准确性的预处理步骤。基准或测试套件是已知几何形状和位移的数据集,可用作调整跟踪参数或比较不同运动估计方法的工具。由于运动估计最初是为研究心脏而开发的,因此现有的测试套件将重点放在心脏运动上。但是,心脏和其他器官之间存在许多基本差异,因此相对于心脏数据库的参数调整(或其他优化)可能不合适。因此,本研究的目的是通过采用“图像合成”测试套件来设计和构建运动基准,以研究由于轻微的旋转加速度而导致的大脑变形,以及在语音过程中模拟舌头运动的基准。为了获得机械行为的真实表示,从有限元(FE)模型获得了运动学。这些结果与标记MRI的采集过程(包括标记生成,切片厚度和运动重复不一致)的近似值结合在一起。为了证明所提出的方法的应用,评估了运动不一致对头脑旋转和变形的综合测量的影响。结果表明,采集不一致性大致与磁头旋转估计误差成正比。此外,在评估非刚性变形时,结果表明,不一致的运动会产生“重影”剪切应变,这是切片获取能力的函数,而不是真实的物理变形。

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