Iulian Voicu

New Estimators and Guidelines for Better Use of Fetal Heart Rate Estimators with Doppler Ultrasound Devices

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.

Optimization of contrast-to-tissue ratio by frequency adaptation in pulse inversion imaging

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.

Estimating Fetal Heart Rate from Multiple Ultrasound Signals

In utero, Monitoring of fetal wellbeing or suffering is today an open challenge, due to the high number of clinical parameters to be considered. An automatic monitoring of fetal activity, dedicated for quantifying fetal wellbeing, becomes necessary. For this purpose and in a view to supply an alternative for the Manning test, we used an ultrasound multitransducer multigate Doppler system. One important issue (and first step in our investigation) is the accurate estimation of fetal heart rate (FHR). An estimation of the FHR is obtained by evaluating the autocorrelation function of the Doppler signals for ills and healthiness foetus. However, this estimator is not enough robust since about 20% of FHR are not detected in comparison to a reference system. These non detections are principally due to the fact that the Doppler signal generated by the fetal moving is strongly disturbed by the presence of others several Doppler sources (mother’s moving, pseudo breathing, etc.). By modifying the existing method (autocorrelation method) and by proposing new time and frequency estimators used in the audio’ s domain, we reduce to 5% the probability of non-detection of the fetal heart rate. These results are really encouraging and they enable us to plan the use of automatic classification techniques in order to discriminate between healthy and in suffering foetus.

Support-vector-machines-based multidimensional signal classification for fetal activity characterization

Electronic fetal monitoring may be required during the whole pregnancy to closely monitor specific fetal and maternal disorders. Currently used methods suffer from many limitations and are not sufficient to evaluate fetal asphyxia. Fetal activity parameters such as movements, heart rate and associated parameters are essential indicators of the fetus well being, and no current device gives a simultaneous and sufficient estimation of all these parameters to evaluate the fetus well-being. We built for this purpose, a multi-transducer-multi-gate Doppler system and developed dedicated signal processing techniques for fetal activity parameter extraction in order to investigate fetuss asphyxia or well-being through fetal activity parameters. To reach this goal, this paper shows preliminary feasibility of separating normal and compromised fetuses using our system. To do so, data set consisting of two groups of fetal signals (normal and compromised) has been established and provided by physicians. From estimated parameters an instantaneous Manning-like score, referred to as ultrasonic score was introduced and was used together with movements, heart rate and associated parameters in a classification process using Support Vector Machines (SVM) method. The influence of the fetal activity parameters and the performance of the SVM were evaluated using the computation of sensibility, specificity, percentage of support vectors and total classification accuracy. We showed our ability to separate the data into two sets : normal fetuses and compromised fetuses and obtained an excellent matching with the clinical classification performed by physician.

Transmit Frequency Optimization for Ultrasound Constrast Agent Response

Introduction: Since the introduction of ultrasound (US) contrast imaging, the imaging systems use a fixed emitting frequency. However it is known that the insonified medium is time-varying and therefore an adapted time-varying excitation is expected. We suggest an adaptive imaging technique which selects the optimal transmit frequency that maximizes the acoustic contrast. Two algorithms have been proposed to find an US excitation for which the frequency was optimal with microbubbles.

Adaptive matched filters for contrast imaging

The ultrasound (US) contrast imaging is a promising technique. Currently the scientific community of this field seeks US excitations which should make possible the optimization of the acoustic contrast. Two matched filters (MF) techniques are used to improve the image contrast. The first technique is an adaptive MF technique and the second is a RLS technique derived from identification theory. The system proposed is a close loop system which optimizes the power backscattered by microbubbles. After having transmit a first signal, the backscattered power is optimized by transmitting the matched filtered signal at each iteration. This process is iterated until convergence. Simulations are carried out for encapsulated microbubbles of 2 microns by considering the modified Rayleigh-Plesset equation for a 2.25MHz transmitted frequency and for various pressure levels (20 kPa up to 420kPa). In vitro, experiments are carried out by using two transducers a transducers which were placed perpendicularly. The signal was transmitted through a 2.25 MHz transducer. Responses of a 1/2000 diluted solution of SonoVue™ were measured by a 3.5 MHz transducer. Each experiment has been realized with three pressure levels (127, 244 and 370 kPa). We show through simulations and through in vitro experiments that our adaptive imaging technique gives in case of simulations a gain which can reach 12 dB compared to the traditional technique and for in vitro experiments, the MF gives a gain which can reach 4.5 dB whereas the MF derived from identification theory can reach 6 dB.