DocumentCode :
1741131
Title :
High-speed high degree-of-freedom spatial normalization for human brain imaging
Author :
Kochunov, Pv ; Lancaster, Jl ; Fox, Pt
Author_Institution :
Health Sci. Center, Texas Univ., San Antonio, TX, USA
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
1642
Abstract :
Regional spatial normalization is an important preliminary step in the analysis of 3-D brain images. The goal is to remove anatomical differences by warping each brain image to match corresponding features in a standard brain atlas. We are developing a very efficient regional spatial normalization algorithm based on octree volume decomposition. The original Octree Spatial Normalization (OSN) algorithm was shown to perform regional spatial normalization in binary brain phantoms in less then 8 minutes with accuracy similar to previously published methods. Several modifications were made in OSN algorithm to optimize it for use with human brain images including automated brain tissue segmentation for tissue classification and feature matching methods with fast cross-correlation. Even with these modifications spatial normalization can still be done in less then 15 minutes for 256 arrays
Keywords :
biological tissues; biomedical imaging; brain; correlation methods; feature extraction; image classification; image matching; image segmentation; medical image processing; octrees; 256 arrays; 3-D brain images; CT; OSN algorithm; Octree Spatial Normalization; PET; SPECT; anatomical differences; automated brain tissue segmentation; binary brain phantoms; fMRI; fast cross-correlation; feature matching methods; high-speed high degree-of-freedom spatial normalization; human brain imaging; octree volume decomposition; regional spatial normalization; tissue classification; Brain; Feature extraction; Gray-scale; Humans; Image analysis; Image segmentation; Imaging phantoms; Optimization methods; Volume measurement; Workstations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1094-687X
Print_ISBN :
0-7803-6465-1
Type :
conf
DOI :
10.1109/IEMBS.2000.900391
Filename :
900391
Link To Document :
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