Lacadie Cheryl M, Fulbright Robert K, Rajeevan Nallakkandi, Constable R Todd, Papademetris Xenophon
Department of Diagnostic Radiology, Yale School of Medicine, New Haven, CT, USA.
Neuroimage. 2008 Aug 15;42(2):717-25. doi: 10.1016/j.neuroimage.2008.04.240. Epub 2008 Apr 30.
While the Talairach atlas remains the most commonly used system for reporting coordinates in neuroimaging studies, the absence of an actual 3-D image of the original brain used in its construction has severely limited the ability of researchers to automatically map locations from 3-D anatomical MRI images to the atlas. Previous work in this area attempted to circumvent this problem by constructing approximate linear and piecewise-linear mappings between standard brain templates (e.g. the MNI template) and Talairach space. These methods are limited in that they can only account for differences in overall brain size and orientation but cannot correct for the actual shape differences between the MNI template and the Talairach brain. In this paper we describe our work to digitize the Talairach atlas and generate a non-linear mapping between the Talairach atlas and the MNI template that attempts to compensate for the actual differences in shape between the two, resulting in more accurate coordinate transformations. We present examples in this paper and note that the method is available freely online as a Java applet.
虽然Talairach图谱仍然是神经影像学研究中报告坐标时最常用的系统,但其构建所依据的原始大脑缺乏实际的三维图像,这严重限制了研究人员将三维解剖MRI图像中的位置自动映射到该图谱的能力。该领域之前的工作试图通过构建标准脑模板(如MNI模板)与Talairach空间之间的近似线性和分段线性映射来规避这个问题。这些方法的局限性在于,它们只能考虑整体脑大小和方向的差异,而无法校正MNI模板与Talairach脑之间实际的形状差异。在本文中,我们描述了将Talairach图谱数字化并在Talairach图谱与MNI模板之间生成非线性映射的工作,该映射试图补偿两者之间实际的形状差异,从而实现更精确的坐标转换。我们在本文中给出了示例,并指出该方法可作为Java小程序在网上免费获取。