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Updated: Jun 15, 2025

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth
Published on: February 9, 2012
Frame composite imaging method based on time-sharing latency excitation for ultrasound shear wave elastography
Jiayue Dai1, Qian Lv1, Yu Li1
1Shaanxi Normal University, the Key Laboratory of Ultrasound of Shaanxi Province, School of Physics and Information Technology, Xi'an 710062, China.
Abstract:
Ultrasound shear wave elastography is an imaging modality that noninvasively assesses mechanical properties of tissues. The results of elastic imaging are obtained by accurately estimating the propagation velocity of shear wave fronts. However, the acquisition rate of the shear wave acquisition device is limited by the hardware of the system. Therefore, increasing the collection rate of shear waves can directly improve the quality of shear wave velocity images. In addition, the problem of velocity reconstruction with relatively small elastic inclusions has always been a challenge in elastic imaging and a very important and urgent issue in early disease diagnosis. For the problem of elastography detection of the shape and boundary of inclusions in tissues, Time-sharing latency excitation frame composite imaging (TS-FCI) method is proposed for tissue elasticity measurement. The method fuses the shear wave motion data generated by time sharing and latency excitation to obtain a set of composite shear wave motion data. Based on the shear wave motion data, the local shear wave velocity image is reconstructed in the frequency domain to obtain the elastic information of the tissue. The experimental results show that the TS-FCI method has a velocity estimation error of 11 % and a contrast to noise ratio (CNR) of 3.81 when estimating inclusions with smaller dimensions (2.53 mm). Furthermore, when dealing with inclusions with small elastic changes (10 kPa), the velocity estimation error is 3 % and the CNR is 3.21. Compared to conventional time-domain and frequency-domain analysis methods, the proposed method has advantages. Results and analysis have shown that this method has potential promotional value in the quantitative evaluation of organizational elasticity.
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