Super-resolution spectral analysis for ultrasound scatter characterization

Konstantinos Diamantis, Maruf A. Dhali, Gavin Jarvis Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Parametric Bayesian spectral estimation methods have been previously utilized to improve frequency resolution. Ultrasound signals have been tested in such methods resulting in higher precision frequency detection compared to common non-parametric spectral estimation methods based on the Fourier transform. Such a technique using a reversible jump Markov Chain Monte Carlo algorithm has been developed to fully characterize signals and in addition to frequency, to provide amplitude and noise estimation. The analysis of this method is demonstrated with a real copper sphere ultrasound scatter signal. Based on typical diagnostic ultrasound data between 1.2-4.5 MHz the new spectral estimation achieves 110 kHz minimum frequency resolution. This is at least twice the resolution of Fourier based methods, resulting in revealing new frequencies. The method may be used in the entire range of ultrasound imaging modalities and may help provide improved sensitivity, reproducibility and spatial resolution.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PublisherIEEE
Pages903-907
Number of pages5
ISBN (Print)9781479999880
DOIs
Publication statusPublished - 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing 2016 - Shanghai International Convention Center, Shanghai, China
Duration: 20 Mar 201625 Mar 2016

Conference

Conference41st IEEE International Conference on Acoustics, Speech and Signal Processing 2016
Abbreviated titleICASSP 2016
CountryChina
CityShanghai
Period20/03/1625/03/16

Keywords

  • Bayesian inference

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  • Cite this

    Diamantis, K., Dhali, M. A., Gibson, G. J., Yan, Y., Hopgood, J. R., & Sboros, V. (2016). Super-resolution spectral analysis for ultrasound scatter characterization. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 903-907). IEEE. https://doi.org/10.1109/ICASSP.2016.7471806