可穿戴电容耦合式电极在载人航天心电检测中的应用

目的研究可穿戴的小尺寸电容耦合式电极在载人航天中的应用问题。方法针对电极尺寸减小对信号幅值和噪声带来的影响,在系统设计中采用动态驱动屏蔽的电极结构、噪声性能优良的阻抗转换放大器等措施提高信噪比,并采用小波阈值滤波算法去噪。结果相比直径4 cm电极,直径2 cm电容耦合式电极采集的信号幅值减小,但心电信号P波、QRS波、T波均得到完整检测,并在降低界面噪声方面具有一定的优势。小波阈值滤波有效消除噪声。结论本文所设计的使用小尺寸电容耦合式电极的心电检测系统实现了隔着衣服对心电信号的非接触式检测,信号波形清晰完整,可以满足航天医学监护要求。     

基于正交合成的两导联心电信号的分析与处理

目的 进一步挖掘出两导联心电信号中潜在的信息，探讨一种分析与处理两导联心电信号的新方法，即心电正交合成图法。方法 从MlT心电数据库中的实际病例中截取几段有代表意义的心拍，绘制出相应的心电正交合成图，并进行定性和定量分析。结果 所研究的病例中各类心拍的心电正交合成图形态差别明显，提取的QRS环最大向量的幅度、角度等指标能有效地区分各类心拍，从而进一步掌握逐个心拍心脏电活动的变化特征。结论 本文提出的心电正交合成图这一方法简单、可行，适应于载人航天的特殊需要，充分利用了目前的航天导联系统。     

心电基线漂移去除方法的比较研究

基线漂移可严重影响心电信号的分析与处理.滤波法和拟合基漂法是去除心电基线漂移的两类主要算法.本文讨论了形态滤波、中值滤波、线性相位FIR滤波、小波变换、形态和小波相结合、中值滤波和小波相结合等去除基漂的滤波方法,并与导数法与坐标法这两类基漂拟合方法进行了对比.实验结果表明,滤波法实现简单,但精度较低;分段拟合法去除基漂的效果更好,有自适应的特性而且失真较小.无论是实时性还是准确性,基漂拟合法都比滤波法更有优势;但某些场合下,基漂拟合点的提取十分困难,此时只能使用滤波法.本文比较了基漂去除的常用方法,从而为基漂去除方法的选择提供参考.     

一种基于MBE和HHT的心电信号自动分类方法

目的研究一种基于多尺度化基本尺度熵(multiscale base-scale entropy,MBE)和希尔伯特-黄变换(Hilbert-Huang transform,HHT)的心电信号自动分类方法。方法首先利用离散小波变换对心电信号进行去噪预处理;其次利用多尺度化基本尺度熵进行分析,提取多个尺度下的基本尺度熵值;然后利用希尔伯特-黄变换得到希尔伯特边际谱,并求取边际谱的信息熵;最后将这两部分特征参数输入到支持向量机中,实现心电信号的自动分类。结果健康人、心律不齐患者、呼吸暂停患者和房颤患者的心电信号分类准确率分别为87.5%、93.75%、90.63%和90.63%。结论本文提出的基于多尺度化基本尺度熵和希尔伯特-黄变换的分类方法,可以有效实现心电信号的自动分类。     

基于小波变换模板的QRS检测方法

目的 有效提高QRS复合波的检测率。方法 ECG信号经过小波变换后，其不同频率成份会映射到变换结果的不同尺度上，而在这些尺度之间存在相互的联系。本文正是利用小波变换后尺度之间的相互关系，提出了一种基于墨西哥草帽小波变换不同尺度之间关系的ECG信号QRS复合波检测方法。该方法根据变换结果的特征点提取小波变换模板，并将这个模板用于ECG信号的QRS检测，可以在滤除噪声的同时，有效提高检测率。结果 经MIT／BIH标准心电数据库检测验证，QRS波正确检测率达到99．9％。结论 综合利用小波变换不同尺度进行非线性变换所得到的模板可以显著提高QRS复合波的检测率。     

二项式小波检测心电特征点

目的 使用二项式小波检测心电信号的特征点,为心电信号的分析提供新的检测手段。方法 设计对称形式的二项式小波,应用它对实际心电信号进行小波变换,并进行特征点的检测,观察检测效果。结果 使用二项式小波检测心电特征点方法实现简单,对试验心电信号的特征点定位准确,快速。结论 对称形式的二项式小波检测较其他小波检测方法简单,无须预处理,有良好的临床应用价值,在心电信号的实时分析中也有很好的应用前景。     

心电信号形态相关性分析

目的 扩展深化载人航天条件下心电信息的分析方法.方法 针对心电信号波形形态间的相似性信息,提出心电相关序列(electrocardio-correlation sequence,ECCS)的分析方法,并对试验数据、MITBIH数据库中的数据构建出心电相关序列,进行分析.结果 心电相关序列较好地展现了心电信号波形形态相似程度的变化趋势.结论 心电相关序列可以在载人航天条件下从一个新的途径研究心肌电活动情况.     

基于能量变换与小波分解的QRS波群检测算法

目的 使用能量变换与小波分解的联合算法检测心电信号QRS波群的特征点,为心电信号的自动分析提供新的手段.方法 能量变换是基于信号的局部特征的,可以有效地突出信号的峰点或谷点;小波分解对信号做多分辨率分解,可以突出信号的特征信息;两种方法的结合更利于QRS波群的检测.结果 使用30例样本检测算法性能,证明联合算法能够提高信噪比,对特征点的定位准确可靠.经MIT/BIH心电数据库的检测验证,其R波定位的正确率高达99.79%.使用心率趋势图分析计算结果,不仅可以完全纠正误检和漏检,而且能够定位异常的心搏.结论 本算法能够准确、实时地识别被噪声严重干扰的心电信号的QRS波群,因而在心电信号的自动分析中有很好的应用前景.     

一种抑制心电信号50 Hz工频干扰的改进Levkov方法

目的 探讨一种用于抑制心电信号中５０Ｈｚ工频干扰的新方法。方法 在Ｌｅｖｋｏｖ滤波法的基础上,加入ＱＲＳ开关函数,并用此法与几种常用的滤波方法进行比较。结果 该方法算法简单,处理速度快,对强、弱噪声滤波效果都较好。结论 该方法对于抑制心电信号中５０Ｈｚ工频干扰有很好的应用前景。     

基于各向异性扩散的超声医学图像滤波方法

目的将各向异性扩散方法应用于超声医学图像的去噪处理。方法采用基于各向异性扩散的偏微分方程，其初始值为输入图像，转化为差分格式迭代求解滤波结果，并通过修改方程中的噪声比例函数使方程更加适用于超声医学图像的滤波。结果通过与其他3种传统滤波方法比较，修正系数后的各向异性扩散滤波方法能够较好地平滑图像的噪声，并且图像的边缘和细节部分依然清晰可见。结论各向异性扩散方法是一种去除超声图像Speckle噪声的有效方法，为超声医学图像的滤波开辟了一条新途径。     

一种基于二代小波变换与盲信号分离的脑电信号处理方法

目的研究对混杂有眼电和心电干扰脑电信号的处理方法。方法首先用二代小波硬/软阈值、折衷阈值、μ律阈值方法对脑电信号消噪,然后运用FastICA算法对消噪后仍含眼电和心电的脑电信号进行盲信号分离。结果二代小波μ律阈值方法对脑电信号有较好的消噪效果,FastICA算法能成功分离出脑电中眼电和心电的干扰。结论运用二代小波μ律阈值法对脑电消噪后再用FastICA算法对独立源产生的干扰进行分离是一种有效的预处理方法。     

Breast volume denoising and noise characterization by 3D wavelet transform.

Breast imaging through cone-beam computed tomography provides a digital breast volume, with which the three-dimensional (3D) breast tissues can be analyzed. Data denoising, as a preprocessing step for subsequent volumetric breast segmentation is always needed. In this paper, we report a volumetric denoising technique by a separable 3D wavelet transform (WT), i.e. a '2D WT plus 1D WT' scheme. Specifically, the scheme performs two-dimensional (2D) wavelet denoising on a stack of slice images of the breast volume, followed by one-dimensional (1D) wavelet denoising along the stacking direction. The denoising is achieved by wavelet decomposition, high-pass subband attenuation, and wavelet synthesis. A one-level 3D WT produces eight subbands occupying the octants of the 3D wavelet space. Multilevel WT also provides a multiresolution representation of breast volume, i.e. a sequence of low-pass subbands. In general, most noise and irregularity features are imparted into the high-pass subbands, which are removed or reduced for denoising purpose. Meanwhile, the information in a subband can be characterized in terms of energy, variance, and entropy. Through 3D visualization, the spatial structure in a subband can also be visually perceived. Experimental demonstration with the breast volume reconstructed from a specimen is provided.     

航天活动各阶段心电图和心动时相的变化及其机理分析

心电图（ＥＣＧ）仍是国外载人航天活动各阶段中连续医学监测的唯一技术。我国载人航天计划中ＥＣＧ也作为重要的医监项目。采用ＥＣＧ,可动态观察人体４大生命体征之一的脉搏（或心率）和心功能,与ＥＣＧ有关的心动进相是反映心功能的一项重要指标,系统了解国外载人航天活动中ＥＣＧ和心动时相的变化及其机理对我国载人航天紧急措施的制定具有重要的参考价值。本文对此作了较系统的回顾与分析。     

基于双向小波变换的心电图压缩算法

目的：在合理的计算复杂度下，尽量保持原始心电图（ECG）信号有用信息的同时获得尽可能大的数据压缩比，方法：将L帧经过预处理的一维ECG信号组成一幅二维图像，通过双向小波变换，尽量解除ECG信号的帧间相关性和帧内相关性，并采用适合的编码达到压缩数据的目的。结果：更好地消除了两种数据的相关性，得到了更高的压缩比。结论：本算法和一维小波变换域压缩法相比，得到的压缩比更高。     

Wavelet denoising for voxel-based compartmental analysis of peripheral benzodiazepine receptors with <Superscript>18</Superscript>F-FEDAA1106

Purpose We evaluated the noise reduction capability of wavelet denoising for estimated binding potential (BP) images (k ₃/k ₄) of the peripheral benzodiazepine receptor using ¹⁸F-FEDAA1106 and nonlinear least-square fitting. Methods Wavelet denoising within a three-dimensional discrete dual-tree complex wavelet transform was applied to simulate data and clinical dynamic positron emission tomography images of ¹⁸F-FEDAA1106. To eliminate noise components in wavelet coefficients, real and imaginary coefficients for each subband were thresholded individually using NormalShrink. A simulated dynamic brain image of ¹⁸F-FEDAA1106 was generated and Gaussian noise was added to mimic PET dynamic scan. The derived BP images were compared with true images using 156 rectangular regions of interest. Wavelet denoising was also applied to data derived from seven young normal volunteers. Results In the simulations, estimated BP by denoised image showed better correlation with the true BP values (Y = 0.83X + 0.94, r = 0.80), although no correlation was observed in the estimates between noise-added and true images (Y = 1.2X + 0.78, r = 0.49). For clinical data, there were visual improvements in the signal-to-noise ratio for estimated BP images. Conclusions Wavelet denoising improved the bias and reduced the variation of pharmacokinetic parameters for BP.     

PET kinetic analysis: wavelet denoising of dynamic PET data with application to parametric imaging

Physiological functions (e.g., cerebral blood flow, glucose metabolism, and neuroreceptor binding) can be investigated as parameters estimated by kinetic modeling using dynamic positron emission tomography (PET) images. Imaging of these physiological parameters, called parametric imaging, can locate the regional distribution of functionalities. However, the most serious technical issue affecting parametric imaging is noise in dynamic PET data. This review describes wavelet denoising of dynamic PET images for improving image quality in estimated parametric images. Wavelet denoising provides significantly improved quality directly to dynamic PET images and indirectly to estimated parametric images. The application of wavelet denoising to radio-ligand and kinetic analysis is still in the development stage, but even so, it is thought that wavelet techniques will have a substantial impact on nuclear medicine in the near future.     

Lactate doublet quantification and lipid signal suppression using a new biexponential decay filter: application to simulated and 1H MRS brain tumor time-domain data.

A new postprocessing filter based on the continuous wavelet transform (CWT) method modeled as a biexponential decay function to isolate the lactate doublet from overlapping lipid resonance(s) and estimate its magnetic resonance spectroscopy (MRS) parameters (signal amplitude, resonance frequencies, and apparent relaxation time (T(*) (2))) is proposed. The new filter employs the same iterative process used in the previously single exponential decay filter. A comparison of the results obtained from application of both filters to simulated data and real (1)H MRS data collected from human blood plasma and brain tumors demonstrates that the new filter provides a better estimate of MRS parameters of lactate, with less computation time. Furthermore, the results show that the new filter is less sensitive to noise and provides a direct estimate of J-coupling value of the lactate doublet.     

Denoising and enhancing digital mammographic images for visual screening.

Dense regions in digital mammographic images are usually noisy and have low contrast, and their visual screening is difficult. This paper describes a new method for mammographic image noise suppression and enhancement, which can be effective particularly for screening image dense regions. Initially, the image is preprocessed to improve its local contrast and the discrimination of subtle details. Next, image noise suppression and edge enhancement are performed based on the wavelet transform. At each resolution, coefficients associated with noise are modelled by Gaussian random variables; coefficients associated with edges are modelled by Generalized Laplacian random variables, and a shrinkage function is assembled based on posterior probabilities. The shrinkage functions at consecutive scales are combined, and then applied to the wavelets coefficients. Given a resolution of analysis, the image denoising process is adaptive (i.e. does not require further parameter adjustments), and the selection of a gain factor provides the desired detail enhancement. The enhancement function was designed to avoid introducing artifacts in the enhancement process, which is essential in mammographic image analysis. Our preliminary results indicate that our method allows to enhance local contrast, and detect microcalcifications and other suspicious structures in situations where their detection would be difficult otherwise. Compared to other approaches, our method requires less parameter adjustments by the user.     

Image restoration and spatial resolution in 7‐tesla magnetic resonance imaging

A good spatial resolution is essential for high precision segmentations of small structures in magnetic resonance images. However, any increase in the spatial resolution results in a decrease of the signal‐to‐noise ratio (SNR). In this article, this problem is addressed by a new image restoration technique that is used to partly compensate for the loss in SNR. Specifically, a two‐stage hybrid image restoration procedure is proposed where the first stage is a Wiener wavelet filter for an initial denoising. The artifacts that will inevitably be produced by this step are subsequently reduced using a recent variant of anisotropic diffusion. The method is applied to magnetic resonance imaging data acquired on a 7‐T magnetic resonance imaging scanner and compared with averaged multiple measurements of the same subject. It was found that the effect of image restoration procedure roughly corresponds to averaging across three repeated measurements. Magn Reson Med 64:15–22, 2010. © 2010 Wiley‐Liss, Inc.