25 March 2011 An expectation maximization framework for an improved ultrasound-based tissue characterization
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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.
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Martino Alessandrini, Simona Maggio, Jonathan Porée, Luca De Marchi, Nicolò Speciale, Emilie Franceschini, Olivier Bernard, 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); doi: 10.1117/12.877632; https://doi.org/10.1117/12.877632
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