Practical Morphometrics Analysis (2D Model)

A step-by-step approach to morphometrics based on two-dimensional images

What you’ll learn
Introduction to morphometrics covering definitions, traditional morphometrics and geometric morphometrics
Landmarks and acqusition tools covering landmark types (anatomical or biological, mathematical, pseudo-landmarks), landmark homology, landmark acquisition tools and how to use, and error assessment with Procrustes ANOVA
Landmarks Visualization covering General Procrustes Analysis (GPA), visualization tools, scatter plots of landmark coordinates, Principal Component Analysis (PCA),Thin-Plate Spline (TPS) deformation grids, arrows, lollipops and other visualizations based on landmark displacements
Statistical methods and Analysis covering ANOVA, MANOVA, ANOSIM/PERMANOVA, regression & allometry, discriminant analysis and canonical variates analysis
Requirements
Introductory college-level science, engineering or social science
Basic knowledge of statistics
Knowledge of shape or image analysis will be an added advantage
Description
Morphometrics has experienced a major revolution through the invention of coordinate-based methods, the discovery of the statistical theory of shape, and the computational realization of deformation grids. The ubiquitous application of fast personal computers and modern analytical tools have ushered in a new era of data analysis, permitting the exploration and visualization of large high-dimensional data sets along with exact statistical tests based on resampling procedures. This new morphometric approach has been termed geometric morphometrics as it preserves the geometry of the landmark configurations throughout the analysis and thus permits to represent statistical results as actual shapes or forms. Therefore, these lectures aim at teaching practically, the concept of statistical shape analysis from 2D images. To encourage learning by exploration; images, annotations and data reports from the hand study are made available for download.