Contrast imaging has significantly improved clinical diagnosis by increasing the contrast-to-tissue ratio after microbubble injection. Pulse inversion imaging is the most commonly used contrast imaging technique because it greatly increases the contrast-to-tissue ratio by extracting microbubble nonlinearities. The main purpose of our study was to propose an automatic technique providing the best contrast- to-tissue ratio throughout the experiment. For reasons of simplicity, we proposed maximizing the contrast-to-tissue ratio with an appropriate choice of the transmit frequency. The contrast-to-tissue ratio was maximized by a closed-loop system including the pulse inversion technique. An algorithm based on gradient descent provided iterative determination of the optimal transmit frequency. The optimization method converged quickly after six iterations. This optimal control method is easy to implement and it optimizes the contrast-to-tissue ratio by adaptively selecting the transmit frequency.
Characterizing fetal wellbeing with a Doppler ultrasound device requires computation of a score based on fetal parameters. In order to analyze the parameters derived from the fetal heart rate correctly, an accuracy of 0.25 beats per minute is needed. Simultaneously with the lowest false negative rate and the highest sensitivity, we investigated whether various Doppler techniques ensure this accuracy. We found that the accuracy was ensured if directional Doppler signals and autocorrelation estimation were used. Our best estimator provided sensitivity of 95.5%, corresponding to an improvement of 14% compared to the standard estimator.
Ultrasound contrast imaging has been introduced in order to increase the contrast of echographic images by injecting micro-bubbles in the vascular system. They are gaz filled microbubbles with nonlinear behavior. One of the most used modality of ultrasound contrast imaging is the second harmonic imaging. This imaging technique, based on the reception of the second harmonic, is devoted to image only the nonlinearity of the microbubble. However, in such ultrasound images the contrast is limited by the nonlinear components of non-perfused tissue. Sub and ultra harmonic imaging appeared to be an interesting alternative to overcome this limitation since, unlike tissue, microbubbles generate sub and ultra harmonics. In order to extract optimally these sub and ultra harmonic components, we proposed a modified Hammerstein model able to model and extract sub and ultra harmonics. Results showed i) that microbubble signal is accurately represented both in time and frequency domains and ii) that sub-and ultra-harmonics were well extracted and separated from harmonic component. Note that the gain achieved by comparing the filtering signals by the modified Hammerstein and the standard Hammerstein was 4.6 dB.
Sub- and ultraharmonic (SUH) ultrasound contrast imaging is an alternative modality to the second harmonic imaging, since, in specific conditions it could produce high quality echographic images. This modality enables the contrast enhancement of echographic images by using SUH present in the contrast agent response but absent from the nonperfused tissue. For a better access to the components generated by the ultrasound contrast agents, nonlinear techniques based on Hammerstein model are preferred. As the major limitation of Hammerstein model is its capacity of modeling harmonic components only, in this work we propose two methods allowing to model SUH. These new methods use several Hammerstein models to identify contrast agent signals having SUH components and to separate these components from harmonic components. The application of the proposed methods for modeling simulated contrast agent signals shows their efficiency in modeling these signals and in separating SUH components. The achieved gain with respect to the standard Hammerstein model was 26.8 dB and 22.8 dB for the two proposed methods, respectively.
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