ABSTRACT
Super-harmonics (SH) only come from contrast agents (CA), and the clutter-free SH imaging (SHI) has higher quality in ultrasound CA imaging. How to better separate the SH from echo signals is a key issue to improve the SHI of the CA. The existing three algorithms all have some limitations, the arrival artifact of pulse inversion (PI) method, the inflexible parameters of high pass filter (HPF) method and the noise residue of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method. In this study, the improved complete ensemble empirical mode decomposition with adaptive noise adaptive decomposition of adaptive noise (ICEEMDAN) method is proposed to improve the quality of the SHI. The CA echo signals from computer simulations and rabbit kidney experiments are decomposed by the ICEEMDAN to obtain a set of intrinsic mode functions (IMF), and then the SH are obtained by adaptive decomposition according to the IMF spectra. The results show that the SHI based on the ICEEMDAN has clearer contours, less interference, and higher image contrast. For the rabbit kidney experiments, the contrasts, contrast-to-noise ratios (CNR), and tissue-to-clutter ratios (TCR) of the ICEEMDAN-based SHI are averagely increased by 43.03%, 27.40% and 33.13%, compared with those based on the PI, HPF and CEEMDAN methods. Therefore, the ICEEMDAN method proposed in this paper has a better effect on separating the SH and can improve the performance of the SHI.
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Index Terms
- Improved Super-harmonic Imaging of Ultrasound Contrast Agents Based on ICEEMDAN
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