TY - JOUR
T1 - Deformable registration of brain tumor images via a statistical model of tumor-induced deformation
AU - Mohamed, Ashraf
AU - Zacharaki, Evangelia I.
AU - Shen, Dinggang
AU - Davatzikos, Christos
N1 - Funding Information:
The authors thank Dr. Nick Fox at the University College London, UK, for providing the tumor patient’s images. We also thank Xiaoying Wu at the Section of Biomedical Image Analysis at the University of Pennsylvania for her help in processing the used data. This work was supported in part by the National Science Foundation under Engineering Research Center Grant EEC9731478, and by the National Institutes of Health Grant R01NS42645.
PY - 2006/10
Y1 - 2006/10
N2 - An approach to the deformable registration of three-dimensional brain tumor images to a normal brain atlas is presented. The approach involves the integration of three components: a biomechanical model of tumor mass-effect, a statistical approach to estimate the model's parameters, and a deformable image registration method. Statistical properties of the sought deformation map from the atlas to the image of a tumor patient are first obtained through tumor mass-effect simulations on normal brain images. This map is decomposed into the sum of two components in orthogonal subspaces, one representing inter-individual differences in brain shape, and the other representing tumor-induced deformation. For a new tumor case, a partial observation of the sought deformation map is obtained via deformable image registration and is decomposed into the aforementioned spaces in order to estimate the mass-effect model parameters. Using this estimate, a simulation of tumor mass-effect is performed on the atlas image in order to generate an image that is similar to tumor patient's image, thereby facilitating the atlas registration process. Results for a real tumor case and a number of simulated tumor cases indicate significant reduction in the registration error due to the presented approach as compared to the direct use of deformable image registration.
AB - An approach to the deformable registration of three-dimensional brain tumor images to a normal brain atlas is presented. The approach involves the integration of three components: a biomechanical model of tumor mass-effect, a statistical approach to estimate the model's parameters, and a deformable image registration method. Statistical properties of the sought deformation map from the atlas to the image of a tumor patient are first obtained through tumor mass-effect simulations on normal brain images. This map is decomposed into the sum of two components in orthogonal subspaces, one representing inter-individual differences in brain shape, and the other representing tumor-induced deformation. For a new tumor case, a partial observation of the sought deformation map is obtained via deformable image registration and is decomposed into the aforementioned spaces in order to estimate the mass-effect model parameters. Using this estimate, a simulation of tumor mass-effect is performed on the atlas image in order to generate an image that is similar to tumor patient's image, thereby facilitating the atlas registration process. Results for a real tumor case and a number of simulated tumor cases indicate significant reduction in the registration error due to the presented approach as compared to the direct use of deformable image registration.
KW - Atlas registration
KW - Brain image registration
KW - Brain tumor
KW - Finite element model
KW - Neurosurgical planning
KW - Statistical deformation model
UR - http://www.scopus.com/inward/record.url?scp=33748632924&partnerID=8YFLogxK
U2 - 10.1016/j.media.2006.06.005
DO - 10.1016/j.media.2006.06.005
M3 - Article
C2 - 16860588
AN - SCOPUS:33748632924
VL - 10
SP - 752
EP - 763
JO - Medical Image Analysis
JF - Medical Image Analysis
SN - 1361-8415
IS - 5
ER -