DocumentCode
2057082
Title
Skull Registration Using Rigid Super-Curves
Author
Liao, Iman Yi ; Zheng, Pan ; Belaton, Bahari
Author_Institution
Sch. of Comput. Sci., Univ. Sains Malaysia, Minden, Malaysia
fYear
2009
fDate
11-14 Aug. 2009
Firstpage
475
Lastpage
479
Abstract
This research presents an algorithm, Rigid Super Curves (RSC), to solve the problem of registering two sets of digitized skulls data under a rigid transformation using crest lines. The method that restitutes the rigid transformation between two sets of fully matched curves is propounded. RSC exploits the non-ambiguity of B-Spline representation of super-curves whilst overcoming the inability of super-curves to restore rigid transformations. A further contribution of this study is a two-stage algorithm based on RSC which registers two sets of partially matched curves under a rigid transformation. The algorithm improves the robustness over feature based methods by considering the structure rather than individual points of the curve. Experimental results on CT scanned skull data show that proposed algorithm is more robust and accurate at restoring the rigid transformation between two sets of crest line data compared with Iterated Closest Point and Super Curves methods.
Keywords
curve fitting; image registration; medical image processing; splines (mathematics); B-Spline representation; CT scanned skull data; crest line data sets; curve points; digitized skull data; feature based methods; iterated closest point method; rigid super-curves; rigid transformation; skull registration; Biomedical imaging; Computer graphics; Data visualization; Image registration; Image restoration; Medical diagnostic imaging; Robustness; Skull; Spline; Voting; Iterated-Closest- Point; Medical image registration; crest lines; curve matching; rigid transformation; super-curves;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Graphics, Imaging and Visualization, 2009. CGIV '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3789-4
Type
conf
DOI
10.1109/CGIV.2009.62
Filename
5298761
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