Strain estimation by a Fourier Series-based extrema tracking algorithm for elastography

Wang, Wenxia; Hu, Dongming; Wang, Jiajun; Zou, Wei

doi:10.1016/j.ultras.2015.05.028

Cited by 5 publications

(4 citation statements)

References 31 publications

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“…Hence, the displacements can be calculated from the distance between the matched extremum pairs and subsequently, the strains in the tissue are determined. Experimental results in our previous paper 21 showed that this method outperforms other methods. 9,18…”

Section: Methodsmentioning

confidence: 74%

“…Here, our previously developed key-point tracking type method 21 is employed. In this method, in order to avoid explicit implementation of the interpolation operation in cases when the RF ultrasound signals are sampled in low sampling rate, we proposed a new extrema tracking strategy based on the Fourier-series expansion of the windowed RF segments.…”

Section: Methodsmentioning

confidence: 99%

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Adaptive mesh refinement for elastic modulus reconstruction in elastography

Wang

Zou

et al. 2018

Proc Inst Mech Eng H

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Meshes play a crucial role in determining the accuracy of the elastic modulus reconstruction in the elastography when the finite element method is employed. In this article, we propose an adaptive mesh refinement strategy which can ensure the coincidence of the meshes with the shape of the inclusions in the observed tissue. This strategy is based on the intensity distribution of the strain image where the variance of the strain distribution in each element of the meshes is used to measure the homogeneity of the element, that is, the larger the strain variance is the more inhomogeneous the element will be and hence more detailed information will be included in this element. For more accurate reconstruction of such detailed information, mesh refinement procedure is implemented in such elements. Besides, two refinement steps are employed for the reconstruction to improve the fitness of the reconstructed image and the observed tissue. Simulation results show that the two-stage adaptive mesh refinement algorithm performs well without needing any prior information about the internal geometric shape in tissue. Not only Young's moduli of models but also shapes of the inclusions can be reconstructed perfectly and quickly with our proposed method.

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Section: Methodsmentioning

confidence: 74%

Section: Methodsmentioning

confidence: 99%

Adaptive mesh refinement for elastic modulus reconstruction in elastography

Wang

Zou

et al. 2018

Proc Inst Mech Eng H

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show abstract

“…The definition of this parameter is

C N R_{e} = \frac{2 {(e_{1} - e_{2})}^{2}}{σ_{1}^{2} + σ_{2}^{2},}

where

e_{1}

and

e_{2}

denote the average strain in the inclusion and background area, respectively, and

σ_{1}

and

σ_{2}

are the standard deviations of the strain in those two regions. Figure A shows the CNR e curves for the case in which the inclusion and background regions were both selected as 2 × 2 mm 2 rectangles, whereas those in Figure B were selected as 8 × 8 mm 2 rectangles. The trend of the curves in Figure coincides with the results shown in Figure .…”

Section: Resultsmentioning

confidence: 99%

A Fast Peak‐Searching Algorithm for Ultrasonic Elastography

Chen

Wang

Zhang

et al. 2017

J of Ultrasound Medicine

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Tissue axial strain estimation with ultrasound elastography has become a hot field in recent years. However, for keypoints tracking-based elastography algorithms, locating extrema in multimodal ultrasonic radiofrequency signals is still a challenging problem. In this paper, a new method is proposed to locate the local maxima and minima of the RF signals directly without derivation operation. This algorithm can accurately locate extrema even if disturbed peaks resulting from different noise exist. Furthermore, the new algorithm can speed up approximately 79% of the implementation process as compared with the standard cross-correlation method on the same computing platform. In addition, the elastographic signal-to-noise ratio and the contrast-to-noise ratio are also significantly improved with this new method.

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“…The correlation between tissue mechanical property changes and diseases has led to the development of elastography methods, focusing on tissue elasticity [ 5 , 6 ]. Recent studies exploring nonlinear models to mimic tissue behavior acknowledge limitations, including a lack of very high accuracy, relative elastic coefficients (especially for breast tissues), and high calibration costs [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the effect of tissue stimulation at different frequencies on breast lesion classification based on nonlinear features using a novel radio frequency time series approach

Norouzi Ghehi,

Fallah,

Rashidi

et al. 2024

Heliyon

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Strain estimation by a Fourier Series-based extrema tracking algorithm for elastography

Cited by 5 publications

References 31 publications

Adaptive mesh refinement for elastic modulus reconstruction in elastography

Adaptive mesh refinement for elastic modulus reconstruction in elastography

A Fast Peak‐Searching Algorithm for Ultrasonic Elastography

Evaluating the effect of tissue stimulation at different frequencies on breast lesion classification based on nonlinear features using a novel radio frequency time series approach

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