Literature DB >> 28534769

A Systematic Investigation of Lateral Estimation Using Various Interpolation Approaches in Conventional Ultrasound Imaging.

Zhi Liu, Chengwu Huang, Jianwen Luo.   

Abstract

Accurate lateral displacement and strain estimation is critical for some applications of elasticity imaging. Typically, motion estimation in the lateral direction is challenging because of low sampling frequency and lack of phase information in conventional ultrasound imaging. Several approaches have been proposed to improve the performance of lateral estimation, such as lateral interpolation on the radio frequency (RF) signals (Interp_RF), lateral interpolation on the cross-correlation function (Interp_CCF), and lateral interpolation on both the RF signals and cross-correlation function (Interp_Both). In this paper, the estimation performances of the above-mentioned three approaches are compared systematically in simulations and phantom experiments. In the simulations, the root-mean-square error (RMSE) of axial/lateral displacement and strain is utilized to assess the accuracy of motion estimation. In the phantom experiments, the displacement quality metric (DQM), defined as the normalized cross-correlation between the motion-compensated reference frame and the comparison frame, and the contrast-to-noise ratio (CNR) of axial/lateral strain are used as the evaluation criteria. The results show that the three approaches have similar performance in axial estimation. For lateral estimation, if the line density of ultrasound imaging is relatively high (i.e., >4.2 lines/mm), Interp_CCF is comparable to Interp_Both, and Interp_RF performs the worst. However, if the line density is relatively low (i.e., <2.8 lines/mm), Interp_Both performs the best as indicated by the lowest RMSEs or highest DQMs and CNRs in lateral estimation. The trend is consistent at different window sizes, applied strains, and sonographic signal-to-noise ratios (>20 dB). Besides, Interp_Both with a small interpolation factor (e.g., 3-5) is found to obtain the best tradeoff between the estimation accuracy and the computational cost, and thus is suggested for lateral motion estimation in the case of a low line density (i.e., <2.8 lines/mm).

Year:  2017        PMID: 28534769     DOI: 10.1109/TUFFC.2017.2705186

Source DB:  PubMed          Journal:  IEEE Trans Ultrason Ferroelectr Freq Control        ISSN: 0885-3010            Impact factor:   2.725


  3 in total

1.  Locally optimized correlation-guided Bayesian adaptive regularization for ultrasound strain imaging.

Authors:  Rashid Al Mukaddim; Nirvedh H Meshram; Tomy Varghese
Journal:  Phys Med Biol       Date:  2020-03-19       Impact factor: 3.609

2.  Improving Ultrasound Lateral Strain Estimation Accuracy using Log Compression of Regularized Correlation Function.

Authors:  Rashid Al Mukaddim; Tomy Varghese
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2020-07

3.  Comparison of Displacement Tracking Algorithms for in Vivo Electrode Displacement Elastography.

Authors:  Robert M Pohlman; Tomy Varghese; Jingfeng Jiang; Timothy J Ziemlewicz; Marci L Alexander; Kelly L Wergin; James L Hinshaw; Meghan G Lubner; Shane A Wells; Fred T Lee
Journal:  Ultrasound Med Biol       Date:  2018-10-11       Impact factor: 2.998

  3 in total

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