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Enhanced Cortical Thickness Measurements for Rodent Brains via Lagrangian-based RK4 Streamline Computation

机译:通过基于拉格朗日的RK4流线计算增强了啮齿动物大脑的皮质厚度测量

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The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the the previous cortical thickness analysis pipeline.
机译:哺乳动物大脑皮层的厚度是一个重要的形态特征,可用于研究和观察大脑的发育变化,这些变化可能是由生物毒性物质(例如乙醇或可卡因)引起的。尽管已经提出了各种适用于人脑的皮质厚度分析方法,并且已经发展成为经过充分验证的开源软件包,但是用于啮齿类动物脑的皮质厚度分析方法尚未像针对人脑设计的那样健壮和准确。基于先前提出的用于啮齿动物脑部分析的皮质厚度测量管道,1我们在准确性和解剖学一致性方面提出了一种增强的皮质厚度管道。首先,我们在厚度测量步骤中提出了一种基于拉格朗日的计算方法,以便使用四阶Runge-Kutta方法将局部截断误差降至最低。其次,通过为厚度测量的每个流水线构造一个线对象,我们可以可视化测量厚度的方式并通过执行几何后处理来实现亚体素精度。最后,着重强调解剖上一致的偏微分方程(PDE)边界图的重要性,我们提出了一种自动PDE边界图生成算法,该算法特定于啮齿动物的大脑解剖结构,不需要手动标记。结果表明,所提出的皮质厚度管道可以产生统计上显着的区域,而先前的皮质厚度分析管道中未观察到这些区域。

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