Contrast Optimization by Metaheuristic for Inclusion Detection in Nonlinear Ultrasound Imaging

Jean-Marc Girault (1) , Sébastien Ménigot (1)

1 iBraiN - Imaging, Brain & Neuropsychiatry

In ultrasound imaging, improvements have been made possible by taking into account the harmonic frequencies. However, the transmitted signal often consists of providing empirically pre-set transmit frequencies, even if the medium to be explored should be taken into account during the optimization process. To resolve this waveform optimization, transmission of stochastic sequences were proposed combined with a genetic algorithm. A medium with an inclusion was compared in term of contrast to a reference medium without defect. Two media were distinguished thanks an Euclidean distance. In simulation, the optimal distance could be multiplied by 4 in comparison with an usual excitation.

Mots clés: ultrasound; Optimal command; Metaheuristic; Inclusion detection

Domaines: Traitement du signal et de l'image [eess.SP]; Acoustique [physics.class-ph]; Imagerie

Jean-Marc Girault, Sébastien Ménigot. Contrast Optimization by Metaheuristic for Inclusion Detection in Nonlinear Ultrasound Imaging. Physics Procedia, 2015, 70, pp.614-617. ⟨10.1016/j.phpro.2015.08.037⟩. ⟨hal-01279952⟩