Twofold minimum variance beamforming for enhanced ultrasound imaging

Purpose

To calculate the optimal weights of a minimum variance (MV) beamformer, the covariance matrix of the received data should be estimated. In ultrasound imaging, it is done through spatial smoothing. However, this technique reduces the effective aperture and consequently limits the attainable resolution. To mitigate this effect, we propose a new configuration for applying an adaptive beamforming method.

Methods

The method is based on applying MV in a twofold configuration such that the outputs of the subarrays are combined through an adaptive MV-like beamformer, instead of simply summing them. In this way, a fully adaptive beamformer is obtained.

Results

Applying the method on a phantom containing point targets has shown that off-axis signals are attenuated more in comparison to MV. This results in a lowered mainlobe width and decreased sidelobe levels. Moreover, simulation results of a cyst phantom confirm the superiority of the method over the MV in terms of contrast.

Conclusion

The method yields significant improvement in the resolving capability and the contrast compared with the conventional MV. At the presence of the steering vector errors, these superiorities were achieved at a cost of slightly more errors in estimating the reflectivity coefficients.

     

Mean and variance quality control for multiple correlated levels of replicated control samples.

Mean and variance rules for quality control are more powerful than rules based on individual values. An algorithm for applying such rules is described that controls type I errors (false alarms), while allowing for multiple levels of quality control samples, correlation between levels, small numbers of preliminary values, replication of samples and autocorrelation arising from random effects. Based on ANOVA and empirical approximations for small samples, the algorithm maintains a low per-batch probability of type I errors. Three statistics are computed, z(m), z(b) and z(w), which are shown by simulations to be primarily sensitive to a concordant shift in the quality control values, a discordant shift in the values, and an increase in random variability, respectively. Simulations also show that for a Gaussian distribution of analytical errors, the per-batch probability of a type I error is likely to be within the range 0.0045-0.0071 for two to four levels where there are 20-100 preliminary batches and the inter-level correlations are between zero and 0.8. This partial separation of out-of-control alarms into three components provides more assistance with trouble-shooting than do multivariate quality control schemes based on Hotelling's T2, while retaining comparable power.     

肝移植术后管腔重建相关并发症的介入治疗

目的：探讨介入技术治疗肝移植术后血管和胆管管腔重建相关性并发症的可行性。方法：肝移植术后共有16例相关并发症患者接受介入治疗,其中肝动脉狭窄4例,肝动脉血栓形成2例,门静脉狭窄并血栓形成1例,胆管吻合口狭窄9例。肝动脉狭窄行球囊扩张（PTA）或内支架治疗,肝动脉血栓形成行导管接触性溶栓治疗,门静脉狭窄并血栓形成行溶栓、支架置入及分流道栓塞治疗,胆管吻合口狭窄行PTA或支架置入治疗。结果：16例患者均获技术成功,治疗均有效,有效率为100%。4例肝动脉狭窄1例单纯PTA有效,3例行支架置入术后有效,血流恢复。2例肝动脉血栓形成术后血栓消失,血流恢复通畅。1例门静脉并发症治疗后血流恢复,灌注增加。9例胆管吻合口狭窄2例行PTA有效,7例置入支架后有效。随访0.5～17个月无复发,5例死于原发病进展或系统并发症,与该并发症或介入治疗无关。结论：介入技术成功率高、并发症少,是治疗肝移植管腔重建相关并发症的有效方法。     

Beamformer reconstruction of correlated sources using a modified source model

This paper introduces a lead field formulation for use in beamformer analysis of MEG data. This 'dual source beamformer' is a technique to image two temporally correlated sources using beamformer methodology. We show that while the standard, single source beamformer suppresses the reconstructed power of two spatially separate but temporally correlated sources, the dual source beamformer allows for their accurate reconstruction. The technique is proven to be accurate using simulations. We also show that it can be used to image accurately the auditory steady state response, which is correlated between the left and right auditory cortices. We suggest that this technique represents a useful way of locating correlated sources, particularly if a seed location can be defined a priori for one of the two sources. Such a priori information could be based on previous studies using similar paradigms, or from other functional neuroimaging techniques.     

Improving reconstruction of sound speed profiles using a self-organizing map method with multi-source observations

ABSTRACT

The sound speed profile (SSP) is a key dynamic factor affecting underwater acoustic propagation, and it is crucial to obtain SSP accurately in real time. A new scheme to improve the reconstruction performance of sound speed profile with multi-source observations using self-organizing map (SOM) method was proposed in this study. Given that the inverted echo sounder (IES) data and mix layer depth (MLD) could respectively provide information on the integrated properties of the water column and SSP structure, we included the two parameters as the priori information to improve the SSP reconstruction performance of the SOM method. With the advantage of merging multi-source information, the SOM method showed significant improvement when including IES data and MLD as the priori information to reconstruct SSPs in the dynamic Kuroshio Extension region.     

Regression-based neural network for improving image reconstruction in diffuse optical tomography

Diffuse optical tomography (DOT) is a non-invasive imaging technique utilizing multi-scattered light at visible and infrared wavelengths to detect anomalies in tissues. However, the DOT image reconstruction is based on solving the inverse problem, which requires massive calculations and time. In this article, for the first time, to the best of our knowledge, a simple, regression-based cascaded feed-forward deep learning neural network is derived to solve the inverse problem of DOT in compressed breast geometry. The predicted data is subsequently utilized to visualize the breast tissues and their anomalies. The dataset in this study is created using a Monte-Carlo algorithm, which simulates the light propagation in the compressed breast placed inside a parallel plate source-detector geometry (forward process). The simulated DL-DOT system''s performance is evaluated using the Pearson correlation coefficient (R) and the Mean squared error (MSE) metrics. Although a comparatively smaller dataset (50 nos.) is used, our simulation results show that the developed feed-forward network algorithm to solve the inverse problem delivers an increment of ∼30% over the analytical solution approach, in terms of R. Furthermore, the proposed network''s MSE outperforms that of the analytical solution''s MSE by a large margin revealing the robustness of the network and the adaptability of the system for potential applications in medical settings.     

神经网络重建仪治疗改善脑卒中偏瘫患者肢体运动功能和日常生活活动能力

目的:观察康复训练并神经网络重建仪(AM800)治疗脑卒中偏瘫患者的疗效。方法:选择2001-07/2004-07在郧阳医学院附属东风总医院神经内科收治的脑卒中后有偏瘫的患者100例,随机分为两组。实验组接受传统物理康复疗法加神经网络重建仪进行治疗,对照组只进行传统物理康复治疗。观察两组治疗对肢体运动功能(Fugl-Meyer评分)及日常生活活动(ADL)能力(Barthel指数)的改善情况。结果:治疗8周后,实验组的Fugl-Meyer评分(70.3±11.6)和对照组的Fugl-Meyer评分(48.4±10.2)比较差异有非常显著性意义(t=5.98,P<0.01)。实验组的Barthel指数评分(74.9±15.7)和对照组的Barthel指数评分(52.2±16.3)比较差异也有非常显著性意义(t=7.17,P<0.01)。结论:神经网络重建仪治疗对提高脑卒中患者的肢体运动功能及ADL能力有重要意义。     

Spatio-temporal dynamics of reach-related neural activity for visual and somatosensory targets

The parieto-frontal network plays a crucial role in the transformations that convert visual information into motor commands for hand reaching movements. Here we use electroencephalography to determine whether the planning of reaching movements to visual and somatosensory targets involves a similar spatio-temporal pattern of neural activity. Subjects performed reaching movements toward spatial locations defined either by visual (light-emitting diode) or somatosensory (vibration of a fingertip of the contralateral hand) stimuli. To identify the activations associated with sensorimotor transformations, we subtracted the event-related potentials recorded in a “static” task (the stimuli were presented but no movement was initiated) from those recorded in a “reach” task (a reach had to be initiated toward the spatial location of the stimuli). In the visual condition, reach-related activities were observed over parietal, premotor and sensorimotor areas contralateral to the reaching hand. Activation was first observed over parietal areas 140 ms after stimulus onset and progressed to frontal areas. The proprioceptive condition recruited a similar set of structures as for visual targets. However, the temporal pattern of activity within these cortical areas differed greatly. Activity was sustained over premotor and sensorimotor areas throughout the reaction time interval, occurring simultaneously with the parietal activation. These results suggest that a common cortical network serves to transform visual and somatosensory signals into motor commands, but that the interactions between the structures of this network differ. This raises the possibility that different coordinate frames are used to encode the motor error for the two target modalities.     

神经干细胞的应用

神经于细胞存在于人类神经系统中，具有自我更新、活跃的增殖和分化能力、向脑内病变部位迁移以及分化成神经元、星形胶质细胞和少突胶质细胞的能力。近年来神经干细胞疗法已成为治疗多种疾病的新策略，其目的是替代、修复或加强受损的细胞或器官的生物学功能，是基因疗法的一种理想的靶细胞。应用主要集中以下几方面：①直接细胞移植进行替代治疗，神经干细胞作为细胞移植的来源，可以通过神经干细胞的体外移植或体内神经干细胞的激活，分化为神经元和胶质细胞，与已经存在的细胞结构整合到一起。②作为基因载体，携带治疗作用的报告基因进行移植，从而达到细胞替代和基因治疗的双重作用。③通过对牛长因子和细胞因子的研究，诱导自身的神经千细胞分化进行神经自我修复。可广泛应用于脑外伤、脑血管病后脑功能损伤、脑瘤及其他疾病的治疗。     

Reconstruction of correlated brain activity with adaptive spatial filters in MEG

Adaptive spatial filters (beamformers) have gained popularity as an effective method for the localization of brain activity from magnetoencephalography (MEG) data. Among the attractive features of some beamforming methods are high spatial resolution and no localization bias even in the presence of random noise. A drawback common to all beamforming methods, however, is significant degradation in performance in the presence of sources with high temporal correlations. Using numerical simulations and examples of auditory and visual evoked field responses, we demonstrate that, at typical signal-to-noise levels, the complete attenuation of fully correlated brain activity is less likely to occur, although significant localization and amplitude biases may occur. We compared various methods for correcting these biases and found the coherent source suppression model (CSSM) (Dalal et al., 2006) to be the most effective, with small biases for widely separated sources (e.g., bilateral auditory areas), however, amplitude biases increased systematically as distance between the sources was decreased. We assessed the performance and systematic biases that may result from the use of this model, and confirmed our findings with real examples of correlated brain activity in bilateral occipital and inferior temporal areas evoked by visually presented faces in a group of 21 adults. We demonstrated the ability to localize source activity in both regions, including correlated sources that are in close proximity (～ 3 cm) in bilateral primary visual cortex when using a priori information regarding source location. We conclude that CSSM, when carefully applied, can significantly improve localization accuracy, although amplitude biases may remain.     

Localization of correlated network activity at the cortical level with MEG

In both hemodynamic and neurophysiological imaging methods, analysis of functionally interconnected networks has typically focused on brain areas that show strong activation in specific tasks. Alternatively, connectivity measures may be used directly to localize network nodes, independent of their level of activation. This approach requires initial cortical reference areas which may be identified based on their high level of activation, their coherence with an external reference signal, or their strong connectivity with other brain areas. Irrespective of how the nodes have been localized the mathematical complexity of the analysis methods precludes verification of the accuracy and completeness of the network structure by direct comparison with the measured data. Therefore, it is critical to understand how the choices of parameters and procedures used in the analysis affect the network identification. Here, using simulated and measured magnetoencephalography (MEG) data, and Dynamic Imaging of Coherent Sources (DICS) for connectivity analysis, we quantify the veracity of network detection at the individual and group level as a function of relevant parameter choices. Using simulations, we demonstrate that coupling measures enable accurate identification of the network structure even without external reference signals, and illustrate the applicability of this approach to real data. We show that a valid estimate of interindividual variability is critical for reliable group-level analysis. Although this study focuses on application of DICS to MEG data, many issues considered here, especially those regarding individual vs. group-level analysis, are likely to be relevant for other neuroimaging methods and analysis approaches as well.     

Visualization Toolkit软件在医学图像三维可视化中的应用

医学图像的可视化已成为基础医学研究和临床辅助诊断、治疗的重要手段,用计算机构建高度精密的人体各部位的三维模型已成为目前医学研究和疾病诊疗方法进一步发展的重要基础.Visualization Toolkit(VTK)作为一款流行的科学可视化软件,具有方便、高效的编程特点.采用VTK结合VC++实现医学图像三维可视化,分别采用Contour-connecting算法、Marching Cubes算法和Ray-casting算法进行了头部的三维绘制.结果证明VTK使用灵活,功能强大,具有重建步骤简单、速度快、交互能力强等优点,可以被广泛应用于医学图像的三维重建中.     

MSCT曲面重建肠管成像技术的应用

目的:探讨多层螺旋CT(MSCT)曲面重建(CPR)肠管成像技术在肠道病变诊断中的临床应用价值。方法:42例肠道病变患者,十二指肠腺癌3例,空肠脂肪瘤1例,回肠淋巴瘤1例,回肠平滑肌肉瘤1例,回肠腺癌4例,回肠及结肠Crohn病1例,结肠腺癌19例,结肠淋巴瘤1例,直肠腺癌11例。采用10mm层厚层距行全腹部MSCT容积扫描,获得原始数据,用2.5mm层厚、1.25mm间隔重叠50%重建轴面源像(ASI),传输至AW4.0诊断工作站,用reformat软件行局部肠管多平面重建(MPR),获得冠状面、矢状面及任意斜面肠管图像,再沿肠管走行划曲线进行CPR成像。结果:CPR肠管成像成功率为100%,图像清晰,均清楚地显示肠道病变。结论:CPR技术可获得良好的肠管图像,CPR肠管成像可直观地显示肠道病变,是对轴位CT图像一种很好的补充。     

The development of sustained and transient neural activity

Sustained and transient signals were compared in a group of 7-8-year-old children and a group of adults performing the same cognitive task using functional magnetic resonance imaging (fMRI) in conjunction with a mixed blocked/event-related design. Results revealed several regions, including a region in the right lateral inferior frontal gyrus, that exhibited opposing developmental trajectories in sustained and transient signals--in particular, decreased sustained signals and increased transient signals with age. Re-analysis of the data assuming "blocked" and "event-related" designs, as opposed to a mixed design, produced different results. In combination, these results may help to explain contradictory findings in the literature regarding the direction of neural development in frontal cortex. Moreover, these results underscore the value of separating sustained and transient signals in fMRI studies of development.     

Tryptase enzyme activity is correlated with severity of chronic obstructive pulmonary disease

Tryptic enzymes, including tryptase, a signature enzyme in mast cells, are involved in the pathogenesis of chronic obstructive pulmonary disease (COPD), a chronic inflammatory airway disease. However, the relationship between tryptase enzyme activity and COPD remains to be investigated. We therefore measured the enzyme activity and immunoreactivity of tryptase in the sputum and plasma of COPD patients in the present study. The results showed that tryptase enzyme activity in the sputum of severe COPD patients (FEV(1)s being recorded at ≤ 30% prediction values) was 3.4 times greater than that in patients with mild COPD (FEV(1)s being recorded at ≥ 80% of predicted values), whereas tryptic activity was 2.0 times higher in the severe COPD patients than in mild COPD patients. Moreover, tryptase enzyme activity, but not tryptic enzyme activity, was significantly elevated in the plasma of severe COPD patients compared with that of mild COPD patients. The level of immunoreactive tryptase was 1.9 times higher in the sputum of the severe COPD patients at admission than that at remission stage. We also employed a rat model of cigarette smoke-induced COPD. After 36 weeks of daily challenges with cigarette smoke, a well-established risk factor of COPD, tryptic and tryptase activities in the bronchoalveolar lavage fluid were elevated 1.5 and 2.6 times, respectively. These results indicate that smoking induces tryptase enzyme activity in the airway. In conclusion, tryptase enzyme activity is markedly increased in sputum and plasma of severe COPD patients. Enhanced tryptase enzyme activity may contribute to the pathogenesis of COPD.     

VisualizationToolkit软件在医学图像三维可视化中的应用

医学图像的可视化已成为基础医学研究和I临床辅助诊断、治疗的重要手段,用计算机构建高度精密的人体各部位的三维模型已成为目前医学研究和疾病诊疗方法进一步发展的重要基础。VisualizationToolkit（VTK）作为一款流行的科学可视化软件,具有方便、高效的编程特点。采用VTK结合VC＋＋实现医学图像三维可视化,分别采用Contour-connecting算法、MarchingCubes算法和Ray—casting算法进行了头部的三维绘制。结果证明VTK使用灵活,功能强大,具有重建步骤简单、速度快、交互能力强等优点,可以被广泛应用于医学图像的三维重建中。     

查对流程再造在儿科静脉输液中的应用

查对制度是医院护理管理的核心制度之一,也是护理工作安全和质量的重要保证[1],查对不严是护士静脉输液缺陷发生的主要原因.自2007年1月我科将静脉输液查对环节进行流程再造后对护士进行培训、督导临床应用,降低了护理缺陷发生率,提高了护理质量.现将做法与体会总结如下.     

临床康复护理路径在拇指再造病人中的应用

[目的]观察临床康复护理路径在拇指再造病人康复中的应用效果。[方法]选择2008年6月-2011年6月在我科住院的拇指再造病人44例,随机分为对照组20例和干预组24例,对照组采用传统康复治疗及护理方法,实验组采用临床康复护理路径模式,测定两组病人平均住院日、平均住院费用以及满意度、功能锻炼掌握、并发症、再造拇指功能评定的效果。[结果]两组病人的平均住院天数、住院费用及满意度、术后功能锻炼掌握、并发症、再造拇指功能评定评分差异均有统计学意义(P<0.05)。[结论]按临床康复护理路径实施护理,可以提高拇指再造病人的疗效,减少住院天数,降低费用,和谐护患关系。     

Source reconstruction of brain electromagnetic fields — Source iteration of minimum norm (SIMN)

A recursive scheme aiming at obtaining sparse and focal brain electromagnetic source distribution is proposed based on the interpretation that the weighted minimum norm is the minimum norm estimates of amplitudes on grid points for the source distribution specified by the diagonal elements of the weight matrix. The source distribution is updated so that, at each grid point, the number of current dipoles equals the total source strength estimate of the pre-specified current dipoles. The source strength of a pre-specified current dipole is estimated by projecting the vector of minimum norm estimate to the space spanned by the three column vectors, corresponding to the three amplitudes of the current dipole, of the resolution matrix. The norm of the projected vector yields the source strength estimate of the current dipole. Exact inverse solutions are obtained by this source iteration of minimum norm (SIMN) algorithm for noiseless MEG signals from multi-point sources provided the sources are sufficiently sparse and there are no substantial cancellations among the signals of the sources. For noisy data, a set of “noise sources” is introduced. The diagonal matrix formed by the “noise source numbers” plays the role of regularization matrix and Tikhonov regularization is applied to initialize the “noise source numbers”. Application to the source localization of real EEG data is also presented.