TY - JOUR
T1 - Adaptive FEM-based nonrigid image registration using truncated hierarchical B-splines
AU - Pawar, Aishwarya
AU - Zhang, Yongjie
AU - Jia, Yue
AU - Wei, Xiaodong
AU - Rabczuk, Timon
AU - Chan, Chiu Ling
AU - Anitescu, Cosmin
N1 - Funding Information:
The medical images were provided from ( http://overcode.yak.net/15 ). The research at Carnegie Mellon University was supported in part by NSF CAREER Award OCI-1149591 . The research at Bauhaus University Weimar was supported in part by the ITN-INSIST and ERC-COMBAT funded by the EU-FP7 ( PITN-GA-2011-289361 ).
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2016/10/1
Y1 - 2016/10/1
N2 - We present an efficient approach of Finite Element Method (FEM)-based nonrigid image registration, in which the spatial transformation is constructed using truncated hierarchical B-splines (THB-splines). The image registration framework minimizes an energy functional using an FEM-based method and thus involves solving a large system of linear equations. This framework is carried out on a set of successively refined grids. However, due to the increased number of control points during subdivision, large linear systems are generated which are generally demanding to solve. Instead of using uniform subdivision, an adaptive local refinement scheme is carried out, only refining the areas of large change in deformation of the image. By incorporating the key advantages of THB-spline basis functions such as linear independence, partition of unity and reduced overlap into the FEM-based framework, we improve the matrix sparsity and computational efficiency. The performance of the proposed method is demonstrated on 2D synthetic and medical images.
AB - We present an efficient approach of Finite Element Method (FEM)-based nonrigid image registration, in which the spatial transformation is constructed using truncated hierarchical B-splines (THB-splines). The image registration framework minimizes an energy functional using an FEM-based method and thus involves solving a large system of linear equations. This framework is carried out on a set of successively refined grids. However, due to the increased number of control points during subdivision, large linear systems are generated which are generally demanding to solve. Instead of using uniform subdivision, an adaptive local refinement scheme is carried out, only refining the areas of large change in deformation of the image. By incorporating the key advantages of THB-spline basis functions such as linear independence, partition of unity and reduced overlap into the FEM-based framework, we improve the matrix sparsity and computational efficiency. The performance of the proposed method is demonstrated on 2D synthetic and medical images.
KW - Adaptive local refinement
KW - Finite Element Method
KW - Nonrigid image registration
KW - Truncated hierarchical B-splines
UR - http://www.scopus.com/inward/record.url?scp=84992521453&partnerID=8YFLogxK
U2 - 10.1016/j.camwa.2016.05.020
DO - 10.1016/j.camwa.2016.05.020
M3 - Article
AN - SCOPUS:84992521453
SN - 0898-1221
VL - 72
SP - 2028
EP - 2040
JO - Computers and Mathematics with Applications
JF - Computers and Mathematics with Applications
IS - 8
ER -