TY - JOUR
T1 - Fourier Synchrosqueezed Transform for Shear Wave Speed Estimation in Crawling Wave Sonoelastography Approach
AU - Sanchez, Joaquin
AU - Merino, Sebastian
AU - Orihuela, Cristina
AU - Castaneda, Benjamin
AU - Romero, Stefano E.
PY - 2025/7/1
Y1 - 2025/7/1
N2 - Crawling Wave Sonoelastography (CWS) is a quantitative elastography technique that employs two mechanical actuators to generate an interference pattern within the tissue. Ultrasound imaging is then used to capture the resulting wave fields, and the shear wave speed (SWS) is computed to produce an elastography image. In previous studies, different time-frequency techniques have been employed to estimate the SWS, but some limitations, such as lateral artifacts and blurred SWS maps, were reported. In this paper, a novel approach based on the Fourier Synchrosqueezed Transform (FSST) is presented. To assert the veracity of the results, previous datasets in homogeneous and heterogeneous phantoms with vibration frequencies between 200 and 360 Hz have been used. The proposed metrics for comparison were SWS mean value and standard variation, coefficient of variation (CV), Bias, R2080, and, contrast-to-noise ratio (CNR). The new estimator demonstrates marginally superior performance in SWS mean value (at 340 Hz, inclusion: 5.13±0.01 m/s, background: 3.42±0.02 m/s) CV (at 320 Hz, inclusion: 0.11%, background: 0%) and CNR (at 320 Hz, 104.7 dB), and better performance in Bias (at 320 Hz, inclusion: 0.6%, background: 0.84%) and R2080 (at 320 Hz, 0.5 mm) in comparison with previous time-frequency approaches.Clinical relevance- This investigation presents a new Shear Wave Speed estimator for Crawling Waves Sonoelastography approach, which is able to quantify stiffness tissue with great accuracy showing the potential of real-time time application to allow the characterization of tissue elasticity.
AB - Crawling Wave Sonoelastography (CWS) is a quantitative elastography technique that employs two mechanical actuators to generate an interference pattern within the tissue. Ultrasound imaging is then used to capture the resulting wave fields, and the shear wave speed (SWS) is computed to produce an elastography image. In previous studies, different time-frequency techniques have been employed to estimate the SWS, but some limitations, such as lateral artifacts and blurred SWS maps, were reported. In this paper, a novel approach based on the Fourier Synchrosqueezed Transform (FSST) is presented. To assert the veracity of the results, previous datasets in homogeneous and heterogeneous phantoms with vibration frequencies between 200 and 360 Hz have been used. The proposed metrics for comparison were SWS mean value and standard variation, coefficient of variation (CV), Bias, R2080, and, contrast-to-noise ratio (CNR). The new estimator demonstrates marginally superior performance in SWS mean value (at 340 Hz, inclusion: 5.13±0.01 m/s, background: 3.42±0.02 m/s) CV (at 320 Hz, inclusion: 0.11%, background: 0%) and CNR (at 320 Hz, 104.7 dB), and better performance in Bias (at 320 Hz, inclusion: 0.6%, background: 0.84%) and R2080 (at 320 Hz, 0.5 mm) in comparison with previous time-frequency approaches.Clinical relevance- This investigation presents a new Shear Wave Speed estimator for Crawling Waves Sonoelastography approach, which is able to quantify stiffness tissue with great accuracy showing the potential of real-time time application to allow the characterization of tissue elasticity.
UR - https://www.scopus.com/pages/publications/105023716149
U2 - 10.1109/EMBC58623.2025.11252944
DO - 10.1109/EMBC58623.2025.11252944
M3 - Article
C2 - 41336023
AN - SCOPUS:105023716149
SN - 2694-0604
VL - 2025
SP - 1
EP - 6
JO - Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
JF - Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
ER -