Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Generalized sidelobe canceller beamforming method for ultrasound imaging.

A modified generalized sidelobe canceller (IGSC) algorithm is proposed to enhance the resolution and robustness against the noise of the traditional generalized sidelobe canceller (GSC) and coherence factor combined method (GSC-CF). In the GSC algorithm, weighting vector is divided into adaptive and non-adaptive parts, while the non-adaptive part does not block all the desired signal. A modified steer vector of the IGSC algorithm is generated by the projection of the non-adaptive vector on the signal space constructed by the covariance matrix of received data. The blocking matrix is generated based on the orthogonal complementary space of the modified steer vector and the weighting vector is updated subsequently. The performance of IGSC was investigated by simulations and experiments. Through simulations, IGSC outperformed GSC-CF in terms of spatial resolution by 0.1 mm regardless there is noise or not, as well as the contrast ratio respect. The proposed IGSC can be further improved by combining with CF. The experimental results also validated the effectiveness of the proposed algorithm with dataset provided by the University of Michigan.

Heart motion uncertainty compensation prediction method for robot assisted beating heart surgery - Master-slave Kalman Filters approach.

Robot Assisted Coronary Artery Bypass Graft (CABG) allows the heart keep beating in the surgery by actively eliminating the relative motion between point of interest (POI) on the heart surface and surgical tool. The inherited nonlinear and diverse nature of beating heart motion gives a huge obstacle for the robot to meet the demanding tracking control requirements. In this paper, we novelty propose a Master-slave Kalman Filter based on beating heart motion Nonlinear Adaptive Prediction (NAP) algorithm. In the study, we describe the beating heart motion as the combination of nonlinearity relating mathematics part and uncertainty relating non-mathematics part. Specifically, first, we model the nonlinearity of the heart motion via quadratic modulated sinusoids and estimate it by a Master Kalman Filter. Second, we involve the uncertainty heart motion by adaptively change the covariance of the process noise through the slave Kalman Filter. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The results indicate that the new approach reduces prediction errors by at least 30 µm. Moreover, the new approach performs well in robustness test, in which two kinds of arrhythmia datasets from MIT-BIH arrhythmia database are assessed.

Topology identification of uncertain nonlinearly coupled complex networks with delays based on anticipatory synchronization.

This paper presents an adaptive anticipatory synchronization based method for simultaneous identification of topology and parameters of uncertain nonlinearly coupled complex dynamical networks with time delays. An adaptive controller is proposed, based on Lyapunov stability theorem and Barbǎlat's Lemma, to guarantee the stability of the anticipatory synchronization manifold between drive and response networks. Meanwhile, not only the identification criteria of network topology and system parameters are obtained but also the anticipatory time is identified. Numerical simulation results illustrate the effectiveness of the proposed method.

Parameter estimation of the FitzHugh-Nagumo model using noisy measurements for membrane potential.

This paper proposes an identification method to estimate the parameters of the FitzHugh-Nagumo (FHN) model for a neuron using noisy measurements available from a voltage-clamp experiment. By eliminating an unmeasurable recovery variable from the FHN model, a parametric second order ordinary differential equation for the only measurable membrane potential variable can be obtained. In the presence of the measurement noise, a simple least squares method is employed to estimate the associated parameters involved in the FHN model. Although the available measurements for the membrane potential are contaminated with noises, the proposed identification method aided by wavelet denoising can also give the FHN model parameters with satisfactory accuracy. Finally, two simulation examples demonstrate the effectiveness of the proposed method.

The stimulative effects of endogenous opioids on endothelial cell proliferation, migration and angiogenesis in vitro.

The opioid peptides modulate extensive bioactivities, including pain, cardiovascular response, development and further responses. In the present study, the stimulative effects of endogenous opioid peptides on angiogenesis are evaluated in the proliferation, migration, adhesion and tube formation assays of the human umbilical vein endothelial cell (HUVEC) for the first time. Endomorphin-1, endomorphin-2 and deltorphin I at physiological concentrations could stimulate HUVECs proliferation, migration, adhesion and tube formation in a dose dependent manner; whereas, they exhibited the cytotoxic effects on HUVECs at the higher doses in these assays. Naloxone, the nonselective opioid receptor antagonist, did not influence angiogenesis when it was administrated on its own; but it could antagonize the stimulative effects of the opioid peptides on angiogenesis when it was administrated in combination with the opioid peptides. Taken altogether, the results suggested that endogenous opioid peptides (endomorphin-1 and -2 and deltorphin I) stimulated angiogenesis at the cellular level, and these effects were mediated by the opioid receptors. These data are significant for potential clinical implementation in future.

Endogenous opioid peptides, endomorphin-1 and -2 and deltorphin I, stimulate angiogenesis in the CAM assay.

The opioid peptides modulate extensive bioactivities, including pain, cardiovascular response, development and so on. The effects of endogenous opioid peptides on angiogenesis were evaluated in the chick embryo chorioallantoic membrane (CAM) assay for the first time in the present study. Endomorphin-1, endomorphin-2 and deltorphin I at the dosage of 1, 10, 100 nmol/embryo could stimulate angiogenesis dose-dependently, respectively. Naloxone, the nonselective opioid receptor antagonist, did not influence angiogenesis alone; but it could antagonize the stimulative effects of the opioid peptides on angiogenesis when it was administrated in combination with the opioid peptides. Taken altogether, the results suggested that endogenous opioid peptides (endomorphin-1 and -2 and deltorphin I) stimulated angiogenesis in the CAM assay, and these effects were modulated with the opioid receptors. These data are important for potential future clinical implementation.

Melatonin attenuates the development of antinociceptive tolerance to delta-, but not to mu-opioid receptor agonist in mice.

The effects of melatonin (Mel) on the development of tolerance to antinociceptive actions induced by mu- and delta-opioid receptor agonists were determined in male Kunming mice. In the mouse tail-flick tests, selective mu and delta receptor agonists were repeatedly administered to mice supraspinally (intracerebroventricularly, i.c.v.) in the absence or presence of melatonin. Administration of endomorphin-1 (EM-1, a mu-opioid receptor agonist) or deltorphin I (del I, a delta-opioid receptor agonist) twice daily for 4 days produced antinociceptive tolerance compared with vehicle controls. Co-administration with melatonin prevented the development of tolerance to deltorphin I analgesia, and this effect was dose dependent. However, melatonin did not affect the development of antinociceptive tolerance to endomorphin-1. Additionally, the attenuation of deltorphin I tolerance by melatonin was reduced by chronic treatment with luzindole (luz), a selective antagonist on the MT(2) receptor subtype. Taken together, these data suggest that melatonin interferes with the neural mechanisms involved in the development of tolerance to delta-opioid agonist analgesia via its receptor.

[Study on topological description and matching of vessel tree].

Topological description and matching are committed steps for three-dimensional reconstruction of vessel tree from two angiograms. Binary tree is proposed to describe the two-dimensional vessel tree. "Node Weight" and "Similar Node" are defined in order to get better description. Vessel segments in two images are matched by the preorder traversal of the binary trees, and the method is proved fast and accurate.