Title :
Wavelet-Based Independent Component Analysis For Statistical Shape Modeling
Author :
Zewail, Rami ; Elsafi, Ahmed ; Durdle, Nelson
Author_Institution :
Alberta Univ., Edmonton
Abstract :
Over the past decade, active shape models have gained increased popularity in medical image analysis. However, despite its widespread, it is now widely accepted that classical shape models using principle component analysis (PCA) is not able to faithfully model the wide range of variations that anatomical structures can undergo. In this paper, we present a new statistical shape model using wavelet transform and independent component analysis (ICA). In an attempt to benefit from the sparsification and approximation power of wavelets, we investigate constructing an ICA-based shape model in a compressed wavelet domain. In order to assess the efficiency of the proposed shape model; experiments were conducted using contours of human vertebrae from X-ray images.
Keywords :
diagnostic radiography; independent component analysis; medical image processing; wavelet transforms; X-ray images; active shape model; compressed wavelet domain; human vertebrae; independent component analysis; medical image analysis; statistical shape modeling; wavelet transform; Active shape model; Anatomical structure; Biomedical imaging; Image analysis; Image coding; Independent component analysis; Principal component analysis; Wavelet analysis; Wavelet domain; Wavelet transforms;
Conference_Titel :
Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
1-4244-1020-7
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2007.299