440 research outputs found

    Towards dynamic contrast specific ultrasound tomography

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    We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.</p

    Fetal movement quantification by fetal vectrocardiography: a preliminary study.

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    Fetal movement is a valuable source of information to monitor the neurological development of the fetus and assess fetal health. Currently, fetal movement can be assessed by the mother or detected by analysis of ultrasound images. Long-term monitoring of movement is complicated with both these methods as maternal self-assessment has a relatively poor sensitivity and specificity and automatic analysis of ultrasound images is not available. Moreover, ultrasound transducers transmit energy into the body, potentially endangering fetal health. In this paper, an alternative method for fetal movement monitoring is presented. This method operates by estimating and analyzing the fetal vectorcardiogram (VCG) from non-invasive recordings on the maternal abdomen. The determined fetal movement is compared with that assessed from a simultaneously performed ultrasound recording; the results of the presented method are consistent with the ultrasound images. In addition, the presented method enables quantification of the rotation angles by means of analysis of the rotation matrix between consecutive fetal VCGs, providing a tool for long-term monitoring of fetal movement with increased specificity

    Electrohysterographic volume conductor modeling

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    Electrohysterographic conduction velocity estimation

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    Monitoring and analysis of the fetal-heart and the uterine-muscle activity, referred to as electrohysterogram (EHG), is essential to permit timely treatment during pregnancy. While remarkable progress is reported for monitoring of the fetal cardiac activity, the EHG measurement and interpretation remains challenging, and limited knowledge is available on the underlying physiological processes. In particular, little attention has been paid to the analysis of the EHG propagation, whose characteristics might indicate the presence of coordinated uterine contractions leading to intrauterine pressure increase. Therefore, this study focuses for the first time on the noninvasive estimation of the conduction velocity of EHG action potentials by means of multichannel EHG recording and surface high-density electrodes. A maximum likelihood algorithm, initially proposed for skeletal-muscle electromyography, is modified for the required EHG analysis. The use of clustering and weighting is introduced to deal with poor signal similarity between different channels. The presented methods were evaluated by specific simulations, proving the combination of weighting and clustering to be the most accurate method. A preliminary EHG measurement during labor confirmed the feasibility of the method. An extensive clinical validation will however be necessary to optimize the method and assess the relevance of the EHG conduction velocity for pregnancy monitoring

    Noninvasive Estimation of the Electrohysterographic Action-Potential Conduction Velocity

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    OPEN ACCESS: AN OVERVIEW

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    Contains fulltext : 217438.pdf (Publisher’s version ) (Closed access
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