Morphometrics, 3D Imaging, and Craniofacial Development

被引:57
作者
Hallgrimsson, Benedikt [1 ,2 ]
Percival, Christopher J. [1 ,2 ]
Green, Rebecca [1 ,2 ]
Young, Nathan M. [3 ]
Mio, Washington [4 ]
Marcucio, Ralph [3 ]
机构
[1] Univ Calgary, Dept Cell Biol & Anat, Alberta Childrens Hosp Res Inst, Calgary, AB, Canada
[2] Univ Calgary, McCaig Bone & Joint Inst, Calgary, AB, Canada
[3] Univ Calif San Francisco, Dept Orthopaed Surg, San Francisco Gen Hosp, Orthopaed Trauma Inst, San Francisco, CA 94143 USA
[4] Florida State Univ, Dept Math, Tallahassee, FL 32306 USA
来源
CRANIOFACIAL DEVELOPMENT | 2015年 / 115卷
关键词
MAGNETIC-RESONANCE MICROSCOPY; DISTANCE MATRIX ANALYSIS; MORPHOLOGICAL INTEGRATION; GEOMETRIC MORPHOMETRICS; SHAPE VARIATION; MOUSE EMBRYOS; FACE SHAPE; GROWTH; HOMOLOGY; ALLOMETRY;
D O I
10.1016/bs.ctdb.2015.09.003
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Recent studies have shown how volumetric imaging and morphometrics can add significantly to our understanding of morphogenesis, the developmental basis for variation, and the etiology of structural birth defects. On the other hand, the complex questions and diverse imaging data in developmental biology present morphometrics with more complex challenges than applications in virtually any other field. Meeting these challenges is necessary in order to understand the mechanistic basis for variation in complex morphologies. This chapter reviews the methods and theory that enable the application of modern landmark-based morphometrics to developmental biology and craniofacial development, in particular. We discuss the theoretical foundations of morphometrics as applied to development and review the basic approaches to the quantification of morphology. Focusing on geometric morphometrics, we discuss the principal statistical methods for quantifying and comparing morphological variation and covariation structure within and among groups. Finally, we discuss the future directions for morphometrics in developmental biology that will be required for approaches that enable quantitative integration across the genotype-phenotype map.
引用
收藏
页码:561 / 597
页数:37
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