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Proceedings Paper

Power strain imaging based on vibro-elastography techniques
Author(s): Xu Wen; S. E. Salcudean
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Paper Abstract

This paper describes a new ultrasound elastography technique, power strain imaging, based on vibro-elastography (VE) techniques. With this method, tissue is compressed by a vibrating actuator driven by low-pass or band-pass filtered white noise, typically in the 0-20 Hz range. Tissue displacements at different spatial locations are estimated by correlation-based approaches on the raw ultrasound radio frequency signals and recorded in time sequences. The power spectra of these time sequences are computed by Fourier spectral analysis techniques. As the average of the power spectrum is proportional to the squared amplitude of the tissue motion, the square root of the average power over the range of excitation frequencies is used as a measure of the tissue displacement. Then tissue strain is determined by the least squares estimation of the gradient of the displacement field. The computation of the power spectra of the time sequences can be implemented efficiently by using Welch's periodogram method with moving windows or with accumulative windows with a forgetting factor. Compared to the transfer function estimation originally used in VE, the computation of cross spectral densities is not needed, which saves both the memory and computational times. Phantom experiments demonstrate that the proposed method produces stable and operator-independent strain images with high signal-to-noise ratio in real time. This approach has been also tested on a few patient data of the prostate region, and the results are encouraging.

Paper Details

Date Published: 12 March 2007
PDF: 7 pages
Proc. SPIE 6513, Medical Imaging 2007: Ultrasonic Imaging and Signal Processing, 65130I (12 March 2007); doi: 10.1117/12.710214
Show Author Affiliations
Xu Wen, Univ. of British Columbia (Canada)
S. E. Salcudean, Univ. of British Columbia (Canada)


Published in SPIE Proceedings Vol. 6513:
Medical Imaging 2007: Ultrasonic Imaging and Signal Processing
Stanislav Y. Emelianov; Stephen A. McAleavey, Editor(s)

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