Title :
Substructural segmentation based on regional shape differences
Author :
Machado, Alexei M C ; Gee, James C. ; Campos, Mario F M
Author_Institution :
Dept. of Comput. Sci., Pontifical Catholic Univ. of Minas Gerais, Belo Horizonte, Brazil
Abstract :
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.
Keywords :
eigenvalues and eigenfunctions; image registration; image segmentation; exploratory factor analysis; high-dimensional shape-related variables; regional shape differences; substructural segmentation; Anatomy; Computer science; Data mining; Image analysis; Image registration; Image segmentation; Information analysis; Magnetic resonance imaging; Principal component analysis; Shape;
Conference_Titel :
Computer Graphics and Image Processing, 2002. Proceedings. XV Brazilian Symposium on
Print_ISBN :
0-7695-1846-X
DOI :
10.1109/SIBGRA.2002.1167117
