Literature DB >> 27002372

A comparison of direct and iterative finite element inversion techniques in dynamic elastography.

M Honarvar1, R Rohling, S E Salcudean.   

Abstract

As part of tissue elasticity imaging or elastography, an inverse problem needs to be solved to find the elasticity distribution from the measured displacements. The finite element method (FEM) is a common method for solving the inverse problem in dynamic elastography. This problem has been solved with both direct and iterative FEM schemes. Each of these methods has its own advantages and disadvantages which are examined in this paper. Choosing the data resolution and the excitation frequency are critical for achieving the best estimation of the tissue elasticity in FEM methods. In this paper we investigate the performance of both direct and iterative FEMs for different ranges of excitation frequency. A new form of iterative method is suggested here which requires a lower mesh density compared to the original form. Also two forms of the direct method are compared in this paper: one using the exact fit for derivatives calculation and the other using the least squares fit. We also perform a study on the spatial resolution of these methods using simulations. The comparison is also validated using a phantom experiment. The results suggest that the direct method with least squares fit is more robust to noise compared to other methods but has slightly lower resolution results. For example, for the homogenous region with 20 dB noise added to the data, the RMS error for the direct method with least squares fit is approximately half of the iterative method. It was observed that the ratio of voxel size to the wavelength should be within a specific range for the results to be reliable. For example for the direct method with least squares fit, for the case of 20 dB noise level, this ratio should be between 0.1 to 0.2. On balance, considering the much higher computational cost of the iterative method, the dependency of the iterative method on the initial guess, and the greater robustness of the direct method to noise, we suggest using the direct method with least squares fit for linear elasticity cases.

Mesh:

Year:  2016        PMID: 27002372     DOI: 10.1088/0031-9155/61/8/3026

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

1.  FEM-based elasticity reconstruction using ultrasound for imaging tissue ablation.

Authors:  Corin F Otesteanu; Valery Vishnevsky; Orcun Goksel
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-04-17       Impact factor: 2.924

2.  Numerical simulation of wave propagation through interfaces using the extended finite element method for magnetic resonance elastography.

Authors:  Quanshangze Du; Aline Bel-Brunon; Simon Auguste Lambert; Nahiène Hamila
Journal:  J Acoust Soc Am       Date:  2022-05       Impact factor: 2.482

3.  Nonlinear Inversion MR Elastography With Low-Frequency Actuation.

Authors:  Wei Zeng; Scott W Gordon-Wylie; Likun Tan; Ligin Solamen; Matthew D J McGarry; John B Weaver; Keith D Paulsen
Journal:  IEEE Trans Med Imaging       Date:  2019-12-06       Impact factor: 10.048

4.  Waveguide effects and implications for cardiac magnetic resonance elastography: A finite element study.

Authors:  A Manduca; T L Rossman; D S Lake; K J Glaser; A Arani; S P Arunachalam; P J Rossman; J D Trzasko; R L Ehman; D Dragomir-Daescu; P A Araoz
Journal:  NMR Biomed       Date:  2018-08-13       Impact factor: 4.044

5.  Fast acquisition of propagating waves in humans with low-field MRI: Toward accessible MR elastography.

Authors:  Maksym Yushchenko; Mathieu Sarracanie; Najat Salameh
Journal:  Sci Adv       Date:  2022-09-09       Impact factor: 14.957

Review 6.  Stiffness reconstruction methods for MR elastography.

Authors:  Daniel Fovargue; David Nordsletten; Ralph Sinkus
Journal:  NMR Biomed       Date:  2018-05-18       Impact factor: 4.044

7.  Analysis and improvement of motion encoding in magnetic resonance elastography.

Authors:  Christian Guenthner; Jurgen Henk Runge; Ralph Sinkus; Sebastian Kozerke
Journal:  NMR Biomed       Date:  2018-03-30       Impact factor: 4.044

  7 in total

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