Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 752-763 |
| Number of pages | 12 |
| Journal | Medical Image Analysis |
| Volume | 10 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2006 Oct 1 |
| Externally published | Yes |
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Keywords
- Atlas registration
- Brain image registration
- Brain tumor
- Finite element model
- Neurosurgical planning
- Statistical deformation model
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Medicine (miscellaneous)
- Computer Science (miscellaneous)
Cite this
Deformable registration of brain tumor images via a statistical model of tumor-induced deformation. / Mohamed, Ashraf; Zacharaki, Evangelia I.; Shen, Dinggang; Davatzikos, Christos.
In: Medical Image Analysis, Vol. 10, No. 5, 01.10.2006, p. 752-763.Research output: Contribution to journal › Article
}
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
PY - 2006/10/1
Y1 - 2006/10/1
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
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UR - http://www.scopus.com/inward/citedby.url?scp=33748632924&partnerID=8YFLogxK
U2 - 10.1016/j.media.2006.06.005
DO - 10.1016/j.media.2006.06.005
M3 - Article
VL - 10
SP - 752
EP - 763
JO - Medical Image Analysis
JF - Medical Image Analysis
SN - 1361-8415
IS - 5
ER -