Comput Math Methods Med - Optimization of contrast-to-tissue ratio by adaptation of transmitted ternary signal in ultrasound pulse inversion imaging.

Tópicos

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Resumo

Ultrasound contrast imaging has provided more accurate medical diagnoses thanks to the development of innovating modalities like the pulse inversion imaging. However, this latter modality that improves the contrast-to-tissue ratio (CTR) is not optimal, since the frequency is manually chosen jointly with the probe. However, an optimal choice of this command is possible, but it requires precise information about the transducer and the medium which can be experimentally difficult to obtain, even inaccessible. It turns out that the optimization can become more complex by taking into account the kind of generators, since the generators of electrical signals in a conventional ultrasound scanner can be unipolar, bipolar, or tripolar. Our aim was to seek the ternary command which maximized the CTR. By combining a genetic algorithm and a closed loop, the system automatically proposed the optimal ternary command. In simulation, the gain compared with the usual ternary signal could reach about 3.9 dB. Another interesting finding was that, in contrast to what is generally accepted, the optimal command was not a fixed-frequency signal but had harmonic components.

Resumo Limpo

ultrasound contrast imag provid accur medic diagnos thank develop innov modal like puls invers imag howev latter modal improv contrasttotissu ratio ctr optim sinc frequenc manual chosen joint probe howev optim choic command possibl requir precis inform transduc medium can experiment difficult obtain even inaccess turn optim can becom complex take account kind generat sinc generat electr signal convent ultrasound scanner can unipolar bipolar tripolar aim seek ternari command maxim ctr combin genet algorithm close loop system automat propos optim ternari command simul gain compar usual ternari signal reach db anoth interest find contrast general accept optim command fixedfrequ signal harmon compon

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