This article presents a method for the segmentation of substructures based on exploratory factor analysis. In this approach, a set of high-dimensional shape-related variables is examined with the purpose of finding clusters with strong correlation. This clustering can potentially identify regions that have anatomic significance and thus lend insight to morphometric investigations.
['Alexei Manso Correa Machado', 'James C. Gee', 'Mario Fernando Montenegro Campos']
Substructural segmentation based on regional shape differences