DocumentCode :
3380292
Title :
A Deformable Statistical Shape Model Applied to Three-Dimensional Lumbar Vertebra Images
Author :
Ling, Jian ; Bartels, Keith ; Nicolella, Daniel
Author_Institution :
Southwest Res. Inst., San Antonio, TX
fYear :
2008
fDate :
24-26 March 2008
Firstpage :
133
Lastpage :
136
Abstract :
A surface morphing technique utilizing the generalized gradient vector flow (GGVF) method was implemented and tested. The surface morphing results in a homeomorphic deformation of a reference surface onto individual members of a data set. Internal and external forces that drive the surface morphing result in correspondences between the parameterized surfaces. Principal component analysis was used to form a statistical shape model from the resulting surfaces. Three dimensional LI-lumbar vertebral images were used to demonstrate the algorithm. Volume image preprocessing and segmentation is described as well.
Keywords :
bone; image morphing; image segmentation; medical image processing; orthopaedics; principal component analysis; deformable statistical shape model; generalized gradient vector flow method; homeomorphic deformation; principal component analysis; surface morphing technique; three-dimensional lumbar vertebra images; volume image preprocessing; volume image segmentation; Computed tomography; Deformable models; Humans; Image segmentation; Isosurfaces; Mathematical model; Shape; Spine; Surface morphology; X-ray imaging; 3D Medical Imaging; Lumbar Vertebra; Statistical Shape Model; Surface Morphing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on
Conference_Location :
Santa Fe, NM
Print_ISBN :
978-1-4244-2296-8
Electronic_ISBN :
978-1-4244-2297-5
Type :
conf
DOI :
10.1109/SSIAI.2008.4512303
Filename :
4512303
Link To Document :
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