DocumentCode :
3050137
Title :
Learning 2D shape models
Author :
Duta, Nicolae ; Jain, Anil K. ; Dubuisson-Jolly, Marie-Pierre
Author_Institution :
Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA
Volume :
2
fYear :
1999
fDate :
1999
Abstract :
A new fully automated shape learning method is presented. It is based on clustering a set of training shapes in the original shape space (defined by the coordinates of the contour points) and performing a Procrustes analysis on each cluster to obtain cluster prototypes and information about shape variation. The main difference from previously reported methods is that the training set is first automatically clustered and those shapes considered to be outliers are discarded. The second difference is in the manner in which registered sets of points are extracted from each shape contour. As a direct application of our shape learning method, an 11-structure shape model of brain substructures was extracted from MR image data, an eigen-shape model was automatically trained, and employed to segment several MR brain images not present in the shape-training set. A quantitative analysis of our shape registration approach, within the main cluster of each structure, shows that our results compare very well to those achieved by manual registration; achieving an average rms error of about 1 pixel. Our approach can serve as a fully automated substitute to the tedious and time-consuming manual shape registration and analysis
Keywords :
biomedical MRI; eigenvalues and eigenfunctions; image registration; learning (artificial intelligence); 11-structure shape model; 2D shape models learning; MR image data; Procrustes analysis; cluster prototypes; eigen-shape model; fully automated shape learning method; quantitative analysis; shape learning method; shape registration; shape variation; Brain modeling; Computer science; Data mining; Data visualization; Image segmentation; Learning systems; Machine learning; Performance analysis; Prototypes; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
Conference_Location :
Fort Collins, CO
ISSN :
1063-6919
Print_ISBN :
0-7695-0149-4
Type :
conf
DOI :
10.1109/CVPR.1999.784601
Filename :
784601
Link To Document :
بازگشت