Savadjiev Peter, Rathi Yogesh, Bouix Sylvain, Verma Ragini, Westin Carl-Fredrik
Laboratory for Mathematics in Imaging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Med Image Comput Comput Assist Interv. 2012;15(Pt 3):34-41. doi: 10.1007/978-3-642-33454-2_5.
The geometry of white matter tracts is of increased interest for a variety of neuroscientific investigations, as it is a feature reflective of normal neurodevelopment and disease factors that may affect it. In this paper, we introduce a novel method for computing multi-scale fibre tract shape and geometry based on the differential geometry of curve sets. By measuring the variation of a curve's tangent vector at a given point in all directions orthogonal to the curve, we obtain a 2D "dispersion distribution function" at that point. That is, we compute a function on the unit circle which describes fibre dispersion, or fanning, along each direction on the circle. Our formulation is then easily incorporated into a continuous scale-space framework. We illustrate our method on different fibre tracts and apply it to a population study on hemispheric lateralization in healthy controls. We conclude with directions for future work.
白质纤维束的几何结构在各种神经科学研究中受到越来越多的关注,因为它是反映正常神经发育以及可能影响其的疾病因素的一个特征。在本文中,我们介绍了一种基于曲线集微分几何来计算多尺度纤维束形状和几何结构的新方法。通过测量曲线在与该曲线正交的所有方向上某一给定点处的切向量变化,我们在该点获得一个二维“离散分布函数”。也就是说,我们在单位圆上计算一个函数,该函数描述了沿圆上每个方向的纤维离散或散开情况。然后,我们的公式很容易被纳入连续的尺度空间框架。我们在不同的纤维束上展示了我们的方法,并将其应用于对健康对照者半球侧化的群体研究。最后我们给出了未来工作的方向。