An expectation maximization framework for an improved ultrasound-based tissue characterization

Martino Alessandrini; Simona Maggio; Jonathan Porée; Luca De Marchi; Nicolò Speciale; Emilie Franceschini; Olivier Bernard; Olivier Basset

doi:10.1117/12.877632

25 March 2011 An expectation maximization framework for an improved ultrasound-based tissue characterization

Martino Alessandrini, Simona Maggio, Jonathan Porée, Luca De Marchi, Nicolò Speciale, Emilie Franceschini, Olivier Bernard, Olivier Basset

Author Affiliations +

Proceedings Volume 7968, Medical Imaging 2011: Ultrasonic Imaging, Tomography, and Therapy; 79680E (2011) https://doi.org/10.1117/12.877632
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

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.

Citation Download Citation

Martino Alessandrini, Simona Maggio, Jonathan Porée, Luca De Marchi, Nicolò Speciale, Emilie Franceschini, Olivier Bernard, and Olivier Basset "An expectation maximization framework for an improved ultrasound-based tissue characterization", Proc. SPIE 7968, Medical Imaging 2011: Ultrasonic Imaging, Tomography, and Therapy, 79680E (25 March 2011); https://doi.org/10.1117/12.877632

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