Statistical shape analysis is an analysis of the
geometrical properties of some given set of
shapes by
statistical methods. For instance, it could be used to quantify differences between male and female Gorilla skull shapes, normal and
pathological bone shapes, etc. Important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate mean shapes from (possibly random) samples, to estimate shape variability within samples, to perform clustering and to test for differences between shapes. One of the main methods used is
principal component analysis. Statistical shape analysis has applications in various fields, including medical imaging, computer vision, sensor measurement, and geographical profiling.