Spatial normalisation of three-dimensional neuroanatomical models using shape registration, averaging, and warping

P. Andrey, E. Maschino, Y. Maurin
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引用次数: 8

Abstract

In neuroanatomical studies, the specimens are generally cut into serial sections that are processed to reveal the elements of interest. The third dimension lost during sectioning can be recovered by reconstructing three-dimensional graphical models of the studied structures. To reach statistical significance and to compare results from distinct experiments, data from different models must be combined into common representations. Due to biological and experimental variability, this requires a non-linear spatial normalisation step. In this paper, an algorithm is presented to normalise and map data into average models. The usefulness of the approach for elucidating spatial organisations in the nervous system is illustrated on rat neuroanatomical data.
使用形状配准、平均和翘曲的三维神经解剖模型的空间归一化
在神经解剖学研究中,标本通常被切成连续的部分,经过处理以揭示感兴趣的元素。通过重建所研究结构的三维图形模型,可以恢复切片过程中丢失的第三维。为了达到统计显著性和比较不同实验的结果,必须将来自不同模型的数据组合成共同的表示。由于生物和实验的可变性,这需要非线性空间归一化步骤。本文提出了一种将数据归一化并映射为平均模型的算法。该方法对阐明神经系统空间组织的有用性在大鼠神经解剖学数据上得到了说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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