Effects of different segmentation methods on geometric morphometric data collection from primate skulls
Effects of different segmentation methods on geometric morphometric data collection from primate skulls
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DOI：
10.1111/2041-210x.13274
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发表时间：
2019-11-01
影响因子：
6.6
通讯作者：
Ito, Tsuyoshi
中科院分区：
文献类型：
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作者：
Ito, Tsuyoshi
越来越多的研究正在使用几何形态测量与断层扫描数据分析物体的形状，这些数据通常在测量之前被分割并转换为三维（3D）表面模型。本研究的目的是评估不同的图像分割方法对几何形态测量数据收集使用计算机断层扫描数据收集从非人灵长类动物头骨的影响。比较了基于视觉选择阈值、半最大高度协议和梯度分水岭算法的三种分割方法。对于每种方法，表面重建的效率，标志放置的准确性和形状和大小的变化水平与不同水平的生物变异进行了评价。基于视觉的方法在高密度解剖区域中膨胀表面，而半最大高度协议导致大量的人工孔和侵蚀。然而，基于梯度的方法缓解了这些问题，并生成了最有效的表面模型。所使用的分割方法对形状和大小变化的影响比种间和个体间差异小得多。然而，与个体内（波动不对称）变异相比，这种影响具有统计学显著性，不可忽略。虽然基于梯度的方法在几何形态学分析中没有得到广泛的应用，但它可能是重建3D表面的有前途的选择之一。在评估小的变化时，如波动的不对称性，应注意组合使用不同分割方法获得的3D数据。
An increasing number of studies are analysing the shapes of objects using geometric morphometrics with tomographic data, which are often segmented and transformed to three-dimensional (3D) surface models before measurement. This study aimed to evaluate the effects of different image segmentation methods on geometric morphometric data collection using computed tomography data collected from non-human primate skulls. Three segmentation methods based on a visually selected threshold, a half-maximum height protocol and a gradient and watershed algorithm were compared. For each method, the efficiency of surface reconstruction, the accuracy of landmark placement and the level of variation in shape and size compared with various levels of biological variation were evaluated. The visual-based method inflated the surface in high-density anatomical regions, whereas the half-maximum height protocol resulted in a large number of artificial holes and erosion. However, the gradient-based method mitigated these issues and generated the most efficient surface model. The segmentation method used had a much smaller effect on shape and size variation than interspecific and inter-individual differences. However, this effect was statistically significant and not negligible when compared with intra-individual (fluctuating asymmetric) variation. Although the gradient-based method is not widely used in geometric morphometric analyses, it may be one of promising options for reconstructing 3D surfaces. When evaluating small variations, such as fluctuating asymmetry, care should be taken around combining 3D data that were obtained using different segmentation methods.