The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Christos Davatzikos - One of the best experts on this subject based on the ideXlab platform.
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deformable registration of brain tumor images via a statistical model of tumor Induced Deformation
Medical Image Analysis, 2006Co-Authors: Ashraf Mohamed, Evangelia I Zacharaki, Dinggang Shen, Christos DavatzikosAbstract: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.
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A statistical approach for estimating brain tumor Induced Deformation
Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001), 2001Co-Authors: Ashraf Mohamed, S.k. Kyriacou, Christos DavatzikosAbstract:A general statistical approach for predicting anatomical Deformations is presented. Emphasis in this paper is on estimating Deformations Induced in the brain anatomy due to tumor growth. The presented approach utilizes the principal modes of co-variation between deformed (after tumor growth) and undeformed (before tumor growth) anatomy to estimate one given the other. In particular, with a statistical model constructed from a number of training samples, a patient's brain anatomy prior to tumor growth is estimated based on the patient's tumor-bearing images. This approach is suitable for use in registering a patient's tumor-bearing images to an anatomical atlas for purposes of surgical, or radio-surgical planning. The proposed approach is tested on a data set of 40 axial 2D brain images of normal human subjects. A biomechanical model was used to simulate tumor growth in each image of the data set. Pairs of deformed and undeformed anatomy were generated by tracking locations of 94 landmark points. The quality of the estimates of the undeformed anatomy are evaluated using the leave-one-out method. Results indicate good estimation accuracy considering the relatively small sample size.
Jinsong Leng - One of the best experts on this subject based on the ideXlab platform.
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Voltage-Induced Deformation in dielectric
Journal of Applied Physics, 2012Co-Authors: Jinsong LengAbstract:When subjected to a high electric field, dielectrics deform. For a hard dielectric, voltage-Induced Deformation is usually small, and the potential for Deformation is determined by its breakdown voltage. If a dielectric is soft, the voltage-Induced Deformation is significantly large. The potential for Deformation is determined by the breakdown voltage together with electromechanical instability and snap-through instability. Based on the theoretical researches conducted by Zhao and Suo [Phys. Rev. Lett. 104, 178302 (2010)] and Li et al. [Int. J. Smart Nano Mater. 2(2), 59-67 (2011)], taking the dielectric elastomer soft material as research object, we introduce three kinds of material limits: strain-stiffening, polarization saturation, and breakdown voltage. The effect of material limits on voltage-Induced Deformation is analyzed. Also investigated is the influence of pre-stretch and material parameters on the Deformation. For a specific soft dielectric material under certain pre-stretch, the theoretical m...
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Electric field Induced Deformation in soft dielectric elastomer electroactive polymer
Proceedings of SPIE, 2012Co-Authors: Jinsong LengAbstract:Subjected to a high electric field, the dielectric deforms. If the dielectric is soft, the voltage Induced Deformation is large. The Deformation is determined by the breakdown voltage together with electromechanical instability and snap-through instability. Based on the theoretical research proposed by Suo and Li, taking the dielectric elastomer soft material research object, we introduce two kinds of material limits: strain-stiffening, polarization saturation, analyze the effect of material limits on voltage Induced Deformation. For a specific soft dielectric material under certain pre-stretch, the theoretical maximum electrical actuation Deformation can be determined.
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Voltage-Induced Deformation in dielectric Multi-functional dielectric elastomer artificial muscles for soft and smart machines Voltage-Induced Deformation in dielectric
Journal of Applied Physics, 2012Co-Authors: Liwu Liu, Yanju Liu, Jinsong LengAbstract:When subjected to a high electric field, dielectrics deform. For a hard dielectric, voltage-Induced Deformation is usually small, and the potential for Deformation is determined by its breakdown voltage. If a dielectric is soft, the voltage-Induced Deformation is significantly large. The potential for Deformation is determined by the breakdown voltage together with electromechanical instability and snap-through instability. Based on the theoretical researches conducted by Zhao and Suo [Phys. Rev. Lett. 104, 178302 (2010)] and Li et al. [Int. J. Smart Nano Mater. 2(2), 59-67 (2011)], taking the dielectric elastomer soft material as research object, we introduce three kinds of material limits: strain-stiffening, polarization saturation, and breakdown voltage. The effect of material limits on voltage-Induced Deformation is analyzed. Also investigated is the influence of pre-stretch and material parameters on the Deformation. For a specific soft dielectric material under certain pre-stretch, the theoretical maximum electrical actuation Deformation can be determined.
Dinggang Shen - One of the best experts on this subject based on the ideXlab platform.
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deformable registration of brain tumor images via a statistical model of tumor Induced Deformation
Medical Image Analysis, 2006Co-Authors: Ashraf Mohamed, Evangelia I Zacharaki, Dinggang Shen, Christos DavatzikosAbstract: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.
Ashraf Mohamed - One of the best experts on this subject based on the ideXlab platform.
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deformable registration of brain tumor images via a statistical model of tumor Induced Deformation
Medical Image Analysis, 2006Co-Authors: Ashraf Mohamed, Evangelia I Zacharaki, Dinggang Shen, Christos DavatzikosAbstract: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.
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A statistical approach for estimating brain tumor Induced Deformation
Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001), 2001Co-Authors: Ashraf Mohamed, S.k. Kyriacou, Christos DavatzikosAbstract:A general statistical approach for predicting anatomical Deformations is presented. Emphasis in this paper is on estimating Deformations Induced in the brain anatomy due to tumor growth. The presented approach utilizes the principal modes of co-variation between deformed (after tumor growth) and undeformed (before tumor growth) anatomy to estimate one given the other. In particular, with a statistical model constructed from a number of training samples, a patient's brain anatomy prior to tumor growth is estimated based on the patient's tumor-bearing images. This approach is suitable for use in registering a patient's tumor-bearing images to an anatomical atlas for purposes of surgical, or radio-surgical planning. The proposed approach is tested on a data set of 40 axial 2D brain images of normal human subjects. A biomechanical model was used to simulate tumor growth in each image of the data set. Pairs of deformed and undeformed anatomy were generated by tracking locations of 94 landmark points. The quality of the estimates of the undeformed anatomy are evaluated using the leave-one-out method. Results indicate good estimation accuracy considering the relatively small sample size.
Zhigang Suo - One of the best experts on this subject based on the ideXlab platform.
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Dielectric elastomer actuators under equal-biaxial forces, uniaxial forces, and uniaxial constraint of stiff fibers
Soft Matter, 2012Co-Authors: Tongqing Lu, Jiangshui Huang, Christa Jordi, David R Clarke, Gabor Kovacs, Rui Huang, Zhigang SuoAbstract:A membrane of a dielectric elastomer deforms when a voltage is applied through its thickness. The achievable voltage-Induced Deformation is strongly affected by how mechanical loads are applied. Large voltage-Induced Deformation has been demonstrated for a membrane under equal-biaxial forces, but only small voltage-Induced Deformation has been observed for a membrane under a uniaxial force. This difference is interpreted here theoretically. The theory also predicts that, when the Deformation of a membrane is constrained in one direction, a voltage applied through the thickness of the membrane can cause it to deform substantially in the other direction. Experiments are performed on membranes under equal-biaxial forces and uniaxial forces, as well as on fiber-constrained membranes of two types: a dielectric elastomer membrane with carbon fibers on both faces, and two dielectric elastomer membranes sandwiching nylon fibers. The experimental observations are compared with the theory. ? 2012 The Royal Society of Chemistry.