Affiliations: [a] Department of Information Engineering, School of Information Science and Technology, Qingdao University of Science and Technology, Tsingtao, Shandong, China | [b] Department of Biomedical Engineering, School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Hefei, Anhui, China | [c] Orthopedic Department of the Second Hospital, Air Force Military Medical University, Xi’an, Shaanxi, China
Correspondence:
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Corresponding author: Xiaoyan Zhao, Department of Information Engineering, School of Information Science and Technology, Qingdao University of Science and Technology, Tsingtao, Shandong, China. E-mail: [email protected].
Abstract: BACKGROUND: Pulse-inversion-based tissue harmonic imaging has been utilized for many years because it can effectively eliminate the harmonic leakage and produce low side-lobe. However, the pulse inversion method is sensitive to imaging object movements, which may result in motion artifacts. Spatial resolution and contrast were limited. OBJECTIVE: To improve ultrasound image quality by a new pulse-inversion-based tissue harmonic imaging technique. METHODS: Continuous wavelet transform is applied to investigate the correlation between mother wavelet and the received echoes from two opposite pulses. To get a better correlation, a novel mother wavelet named ‘tissue wavelet’ is designed based on the Khokhlov-Zabolotskaya- Kuznetsov (KZK) wave equation. Radio frequency data were obtained from open Ultrasonix SonixTouch imaging system. Experiments were carried on ultrasonic tissue phantom, human carotid artery and human liver. RESULTS: The average improvement of lateral spatial resolution is 49.52% compared to pulse-inversion-based tissue second-harmonic Imaging (PIHI). Contrast ratio (CR) and contrast-to-noise ratio (CNR) increased by 5.55 dB and 1.40 dB over PIHI. Tissue wavelet performs better than Mexh and Morl wavelet in lateral spatial resolution, CR, and CNR. CONCLUSION: The proposed technique effectively improves the imaging quality in lateral spatial resolution, CR, and CNR.
Keywords: Medical information science, ultrasound imaging, correlation study, wavelet transform, signal detection analysis
