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.

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

ALESSANDRINI, MARTINO;MAGGIO, SIMONA;DE MARCHI, LUCA;SPECIALE, NICOLO'ATTILIO;
2011

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.
Proc. of SPIE -Medical Imaging 2011: Ultrasonic Imaging, Tomography, and Therapy
79680E-1
79680E-6
M. Alessandrini; S. Maggio; J. Poree; L. De Marchi; N. Speciale; E. Franceschini; O. Bernardc; O. Basset
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/114155
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact