Lee Joohwi, Kim Sun Hyung, Oguz Ipek, Styner Martin
University of North Carolina at Chapel Hill, Department of Computer Science, United States.
University of North Carolina at Chapel Hill, Department of Psychiatry, United States.
Proc SPIE Int Soc Opt Eng. 2016 Feb 27;9784. doi: 10.1117/12.2216420. Epub 2016 Mar 21.
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, 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.
哺乳动物大脑的皮质厚度是一个重要的形态学特征,可用于研究和观察大脑可能因乙醇或可卡因等生物毒性物质而发生的发育变化。尽管已经提出了各种适用于人类大脑的皮质厚度分析方法,并已发展成为经过充分验证的开源软件包,但用于啮齿动物大脑的皮质厚度分析方法尚未像针对人类大脑设计的方法那样强大和准确。基于先前提出的用于啮齿动物大脑分析的皮质厚度测量流程,我们在准确性和解剖一致性方面提出了一种增强的皮质厚度流程。首先,我们在厚度测量步骤中提出一种基于拉格朗日的计算方法,以便使用四阶龙格 - 库塔方法最小化局部截断误差。其次,通过为厚度测量的每条流线构建一个线对象,我们可以可视化厚度测量的方式,并通过执行几何后处理实现亚体素精度。最后,强调解剖学上一致的偏微分方程(PDE)边界图的重要性,我们提出了一种特定于啮齿动物大脑解剖结构的自动PDE边界图生成算法,该算法不需要手动标记。结果表明,所提出的皮质厚度流程可以产生在前一个皮质厚度分析流程中未观察到的具有统计学意义的区域。