Start Date

2016 12:00 AM

Description

Multichannel ultrasonic axial-transmission data are multimodal by nature. Multichannel analysis of dispersive ultrasonic energies requires a reliable mapping of the data from the time– distance (t-x) domain to the frequency–wavenumber (f-k) or frequency–phase velocity (f-c) domain. The mapping is usually performed with the classical 2-D Fourier transform (FT) from t- x plane to f-k plane or to f-c plane with a subsequent substitution and interpolation via c=ω/k. The extracted dispersion trajectories of the guided modes lack the resolution in the transformed domain to discriminate wave modes. The resolving power associated with the FT is closely linked to the aperture of the recorded data. In this presentation, we present a linear high- resolution Radon transform (RT) algorithm [1 & 2] to filter and reconstruct wavefields, and to image the dispersive energies of the recorded wavefields through long bones. The RT is posed as an inverse problem, which allows implementation of the regularization strategy to enhance the focusing power. The simulated, ex-vivo, and in-vivo data will be used to illustrate the advantages and robustness of the high-resolution RT algorithm. The method accommodates unevenly spaced records, effectively attenuates noise, enhances the signal-to-noise ratio, improves the coherency of the guided wave modes, and reconstructs the missing records. The dispersive energies are well focused and the trajectories are much better resolved. The proposed transform presents a powerful signal enhancement and imaging tool to process ultrasonic wavefields and extract dispersive guided wave energies under limited aperture.

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

Application of Radon Transform to Wavefield Filtering, Reconstruction, and Imaging of Dispersive Energies in Quantitative Bone Ultrasound

Multichannel ultrasonic axial-transmission data are multimodal by nature. Multichannel analysis of dispersive ultrasonic energies requires a reliable mapping of the data from the time– distance (t-x) domain to the frequency–wavenumber (f-k) or frequency–phase velocity (f-c) domain. The mapping is usually performed with the classical 2-D Fourier transform (FT) from t- x plane to f-k plane or to f-c plane with a subsequent substitution and interpolation via c=ω/k. The extracted dispersion trajectories of the guided modes lack the resolution in the transformed domain to discriminate wave modes. The resolving power associated with the FT is closely linked to the aperture of the recorded data. In this presentation, we present a linear high- resolution Radon transform (RT) algorithm [1 & 2] to filter and reconstruct wavefields, and to image the dispersive energies of the recorded wavefields through long bones. The RT is posed as an inverse problem, which allows implementation of the regularization strategy to enhance the focusing power. The simulated, ex-vivo, and in-vivo data will be used to illustrate the advantages and robustness of the high-resolution RT algorithm. The method accommodates unevenly spaced records, effectively attenuates noise, enhances the signal-to-noise ratio, improves the coherency of the guided wave modes, and reconstructs the missing records. The dispersive energies are well focused and the trajectories are much better resolved. The proposed transform presents a powerful signal enhancement and imaging tool to process ultrasonic wavefields and extract dispersive guided wave energies under limited aperture.