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Proceedings Paper

An expectation maximization framework for an improved ultrasound-based tissue characterization
Author(s): Martino Alessandrini; Simona Maggio; Jonathan Porée; Luca De Marchi; Nicolò Speciale; Emilie Franceschini; Olivier Bernard; Olivier Basset
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Paper Abstract

Ultrasonic tissue characterization has been gaining increasing attention. This procedure is generally based on the analysis of the echo signal. As the ultrasound echo is degraded by the system Point Spread Function, deconvolution could be employed to provide a tissue response estimate, exploitable for a better characterization. In this context, we present a deconvolution framework expressively designed to improve tissue characterization. Thanks to a new model for tissue reflectivity the proposed framework overcomes limitations associated with standard ones. The performance was evaluated from several tissue-mimicking phantoms. Obtained results show relevant improvements in classification accuracy. From a comparison with standard schemes the superiority of the proposed algorithm was attested.

Paper Details

Date Published: 25 March 2011
PDF: 6 pages
Proc. SPIE 7968, Medical Imaging 2011: Ultrasonic Imaging, Tomography, and Therapy, 79680E (25 March 2011);
Show Author Affiliations
Martino Alessandrini, ARCES, Univ. di Bologna (Italy)
Simona Maggio, DEIS, Univ. di Bologna (Italy)
Jonathan Porée, CREATIS, CNRS, INSERM U630, Univ. de Lyon 1 (France)
Luca De Marchi, DEIS, Univ. di Bologna (Italy)
Nicolò Speciale, ARCES, Univ. di Bologna (Italy)
DEIS, Univ. di Bologna (Italy)
Emilie Franceschini, Lab. de Mécanique et d'Acoustique, CNRS (France)
Olivier Bernard, CREATIS, CNRS, INSERM U630, Univ. de Lyon 1 (France)
Olivier Basset, CREATIS, CNRS, INSERM U630, Univ. de Lyon 1 (France)

Published in SPIE Proceedings Vol. 7968:
Medical Imaging 2011: Ultrasonic Imaging, Tomography, and Therapy
Jan D'hooge; Marvin M. Doyley, Editor(s)

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