Title :
STATISTICAL SHAPE ANALYSIS OF BRAIN STRUCTURES USING SPHERICAL WAVELETS
Author :
Nain, D. ; Styner, M. ; Niethammer, M. ; Levitt, J.J. ; Shenton, M.E. ; Gerig, G. ; Bobick, A. ; Tannenbaum, A.
Author_Institution :
Coll. of Comput., Georgia Tech., Atlanta, GA
Abstract :
We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions
Keywords :
biomedical MRI; brain; image segmentation; medical image processing; neurophysiology; statistical analysis; wavelet transforms; FDR correction; MRI images; binary segmentation; brain structures; caudate nucleus; hippocampus; nonparametric permutation tests; sampled point representation; shape analysis; spherical wavelet shape representation; spherical wavelets; statistical shape analysis; statistical surface-based morphometry; Biomedical computing; Biomedical imaging; Brain; Hippocampus; Psychiatry; Shape; Surface morphology; Surface waves; Testing; Wavelet analysis;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
1-4244-0672-2
Electronic_ISBN :
1-4244-0672-2
DOI :
10.1109/ISBI.2007.356825
