Title
Snake-based approach for segmenting pedicles in radiographs and its application in three-dimensional vertebrae reconstruction
Abstract
A gradient vector flow (GVF) snake based method was proposed for pedicle segmentation in vertebral radiographs. Since pedicles were oval-shaped, the elliptical shape prior was used to constrain the evolution of the GVF snake. From segmented pedicles, some landmarks were automatically identified for 3D stereoradiographic reconstruction of vertebrae to reduce the observer variability. Ten radiographs including 260 pedicles were used to evaluate the segmentations. Results demonstrated that the distance between contours manually delineated by the user and those segmented by the proposed algorithm was far less than the distance resulted from the traditional GVF snake. The 3D reconstruction variance was reduced by using the landmarks obtained from the segmented pedicles. These results indicated that utilizing the elliptical shape prior improved the GVF snake for segmenting pedicles in radiographs, and the proposed method might be a useful preprocessing tool for 3D stereoradiographic reconstruction.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652596
ICIP
Keywords
Field
DocType
vertebral radiographs,gradient vector flow (gvf) snake,pedicle segmentation,elliptical shape prior,3d stereoradiographic reconstruction,elliptical shape,image segmentation,pedicle segmention,computer graphics,gradient vector flow,snake-based approach,three-dimensional (3d) reconstruction,image reconstruction,radiograph,snake based method,radiography,three-dimensional vertebrae reconstruction,computational modeling,3d reconstruction,shape,force,three dimensional
Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Segmentation,Image segmentation,Preprocessor,Vector flow,Artificial intelligence,Radiography,3D reconstruction
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
0
PageRank 
References 
Authors
0.34
7
5
Name
Order
Citations
PageRank
Junhua Zhang1376.68
xinling shi27415.34
Yuanyuan Wang349882.58
Liang Lv4323.42
Jun Wu500.34