Recent advances in the quantitative analysis of anatomical variation, called geometric morphometric methods, have the potential to provide more powerful and complete descriptions of morphological diversity in a target population than the traditional anthropometric measurements upon which current respirator standards are based.
Geometric morphometric methods have been found to be more powerful in detecting slight differences between shapes, as would be expected within species [55], [58], [59].
In addition, while it may be of interest to look at divergence on specific axes in some studies, morphometric methods have existed for several years that allow for tests of differences in means and variance in a wholly unconstrained shape space [3], [13], [14].
The combination of an original resource based on interspecific introgression and morphometric geometrics methods has provided novel insights into the genetic architecture of mandible shape variation and morphological modularity.
Modern MRI image processing methods have yielded quantitative, morphometric, functional, and structural assessments of the human brain.
So far, there is no general method for the morphometric analysis of all these types of symmetry, although some methods have been proposed for specific types [ 37, 38] and an application of the present methodology to one type of symmetry has been published [ 39].
Results obtained with ethnobotanical and ecological methods have implication for domestication studies within the Attalea phalerata complex (sensu Henderson et al. 1995), using morphometric and genetic methods to compare wild and managed populations.
Brain images can be analyzed in more sophisticated ways than traditional morphometric methods; shape analysis, for example, has long been used to characterize features of brain structure, including cortical complexity, curvature, fractal dimension, spectral content, and other indices.
As well as these imaging methods that enable us to investigate the function of the brain during headache attacks, structural and morphometric methods, such as voxel-based morphometry, have also become available.
Whereas morphological analyses are widely implemented to study neurons and astrocytes (Matyash & Kettenmann, 2010; Saijo & Glass, 2011), only a few studies have utilized these morphometric methods to characterize microglial morphology and how it changes after various inflammatory triggers (Damani et al., 2011; Fontainhas et al., 2011).
A few different morphometric methods for the analysis of complex symmetries have been suggested in recent years [ 37, 38].
