Contrast Optimization by Metaheuristic for Inclusion Detection in Nonlinear Ultrasound Imaging
Résumé
Context: Nowadays, ultrasound imaging is become an essential tool for diagnosis in industry. This is due to the recent developments of post-processing and pre-processing in nonlinear ultrasound imaging. Problem to be solved: In flaw detection in industrial media or in inclusion detection in biological tissues, transmission of ultrasound sequences is performed with hypotheses that are mostly not justified. Why exploring media with ultrasound waves at a certain frequency, amplitude, duration, shape without taking into account the explored medium ? Is there another paradigm overpassing this drawback ? Proposed solution: The new paradigm that we proposed to take into account the medium but without any a priori information, is to introduce: 1.a feedback in the first steps of the imaging chain allowing an iterative correction of the transmitted waves; 2.a transmission of stochastic waves; 3.a maximization process of the cost function allowing the best discrimination between the reference medium and the tested medium; 4.A meta-heuristic process to accelerate the process convergence.
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