A 2D strain estimator with numerical optimization method for soft-tissue elastography |
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Authors: | Ke Liu Pengfei Zhang Jinhua Shao Xinjian Zhu Yun Zhang Jing Bai |
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Institution: | aDepartment of Biomedical Engineering, Tsinghua University, Beijing 100084, China;bDepartment of Cardiology, Qilu Hospital of Shandong University, Jinan 250012, China |
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Abstract: | Elastography is a bioelasticity-based imaging modality which has been proved to be a potential evaluation tool to detect the tissue abnormalities. Conventional method for elastography is to estimate the displacement based on cross-correlation technique firstly, then strain profile is calculated as the gradient of the displacement. The main problem of this method arises from the fact that the cross-correlation between pre- and post-compression signals will be decreased because of the signal’s compression-to-deformation. It may constrain the estimation of the displacement. Numerical optimization, as an efficient tool to estimate the non-rigid deformation in image registration, has its potential to achieve the elastogram. This paper incorporates the idea of image registration into elastography and proposes a radio frenquency (RF) signal registration strain estimator based on the minimization of a cost function using numerical optimization method with Powell algorithm (NOMPA). To evaluate the proposed scheme, the simulation data with a hard inclusion embedded in the homogeneous background is produced for analysis. NOMPA can obtain the displacement profiles and strain profiles simultaneously. When compared with the cross-correlation based method, NOMPA presents better signal-to-noise ratio (SNR, 32.6 ± 1.5 dB vs. 23.8 ± 1.1 dB) and contrast-to-noise ratio (CNR, 28.8 ± 1.8 dB vs. 21.7 ± 0.9 dB) in axial normal strain estimation. The in vitro experiment of porcine liver with ethanol-induced lesion is also studied. The statistic results of SNR and CNR indicate that strain profiles by NOMPA performs better anti-noise and target detectability than that by cross-correlation based method. Though NOMPA carry a heavier computational burden than cross-correlation based method, it may be an useful method to obtain 2D strains in elastography. |
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Keywords: | Elastography Displacement Strain Correlation NOMPA |
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