2013
DOI: 10.1109/tmi.2012.2228664
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Mesh Adaptation for Improving Elasticity Reconstruction Using the FEM Inverse Problem

Abstract: The finite element method is commonly used to model tissue deformation in order to solve for unknown parameters in the inverse problem of viscoelasticity. Typically, a (regular-grid) structured mesh is used since the internal geometry of the domain to be identified is not known a priori. In this work, the generation of problem-specific meshes is studied and such meshes are shown to significantly improve inverse-problem elastic parameter reconstruction. Improved meshes are generated from axial strain images, wh… Show more

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Cited by 24 publications
(14 citation statements)
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“…Preoperative 3D CT/MRI data of an organ may be used to create a patient-speci c mesh model [15]. Moreover, mechanical characters obtained from the literature or MR/ultrasound elastography may be applied to the mesh model [16][17][18]. In order to simulate physical properties of real organs or large deformation, non-linear elastic body model should be considered.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Preoperative 3D CT/MRI data of an organ may be used to create a patient-speci c mesh model [15]. Moreover, mechanical characters obtained from the literature or MR/ultrasound elastography may be applied to the mesh model [16][17][18]. In order to simulate physical properties of real organs or large deformation, non-linear elastic body model should be considered.…”
Section: Discussionmentioning
confidence: 99%
“…The basic problem for compressed sensing is to reduce M (< N); that is, the number of observed values under the condition where x is sparse. In general, this x is solved by L1-norm minimization [12][13][14][15][16][17]. The optimization problem; that is, minimization of ||x|| 1 under the linear constraint y = Ax, is called L1-norm minimization; it is described below.…”
Section: Estimation Methods Of External Forces Applying L1-norm Minimimentioning
confidence: 99%
“…Hence, the result of the reconstructed Young’s modulus becomes worse when the inclusion gets smaller (Figure 7). To overcome these limitations, the mesh adaptation algorithm has been proposed to improve the accuracy of Young’s modulus reconstruction [46]. Nevertheless, the adaptive mesh generation requires image segmentation using the internal tissue geometry or axial strain information.…”
Section: Discussionmentioning
confidence: 99%
“…Eskandari et al solved the time‐harmonic equations in a similar fashion using Levenburg–Marquardt. This implementation was later used in a study on bandpass sampling and was extended to employ mesh adaptation . Honarvar et al solved the mixed displacement‐pressure and time‐harmonic form using Gauss–Newton and Levenburg–Marquardt.…”
Section: Methodsmentioning
confidence: 99%
“…This implementation was later used in a study on bandpass sampling 66 and was extended to employ mesh adaptation. 67 Honarvar et al 68 solved the mixed displacement-pressure and time-harmonic form using Gauss-Newton and Levenburg-Marquardt. This implementation was also used for comparison with heterogeneous direct methods.…”
Section: Gauss-newton Methodsmentioning
confidence: 99%