Paper
20 March 2014 Medical ultrasound image reconstruction using compressive sampling and lρ-norm minimization
Adrian Basarab, Alin Achim, Denis Kouamé
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Abstract
In the last four years, a few research groups worked on the feasibility of compressive sampling (CS) in ultrasound medical imaging and several attempts of applying the CS theory may be found in the recent literature. In particular, it was shown that using iotap-norm minimization with p different from 1 provides interesting RF signal reconstruction results. In this paper, we propose to further improve this technique by processing the reconstruction in the Fourier domain. In addition, alpha -stable distributions are used to model the Fourier transforms of the RF lines. The parameter p used in the optimization process is related to the parameter alpha obtained by modelling the data (in the Fourier domain) as an alpha -stable distribution. The results obtained on experimental US images show significant reconstruction improvement compared to the previously published approach where the reconstruction was performed in the spatial domain.
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Adrian Basarab, Alin Achim, and Denis Kouamé "Medical ultrasound image reconstruction using compressive sampling and lρ-norm minimization", Proc. SPIE 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography, 90401H (20 March 2014); https://doi.org/10.1117/12.2042991
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Cited by 6 scholarly publications.
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KEYWORDS
Fourier transforms

Ultrasonography

Medical imaging

Image compression

Modeling

Image restoration

Error analysis

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