共查询到19条相似文献,搜索用时 78 毫秒
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针对小波变换不能涉及过多尺度的问题,分析了边缘类型对小波多尺度边缘提取的影响,并结合医学图像的特点,提出基于Canny算子的梯度相位法。梯度相位法认为边缘不只是在灰度发生突变的地方存在,如果某个区域,灰度沿某个方向缓慢变化。这个区域也存在边缘,只不过可以认为边缘比较粗。通过对人脑后颅骨的CT医学图像边缘提取的实验及结果定量和定性分析,证明此方法在医学罔像边缘检测中是切实可行的。 相似文献
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目的 稀疏角度CT具有加速数据采集和减少辐射剂量的优点。然而,由于采集信息的减少,使用传统滤波反投影算法(FBP)进行重建得到的图像中伴有严重的条形伪影和噪声。针对这一问题,本文提出基于多尺度小波残差网络(MWResNet)对稀疏角度CT图像进行恢复。方法 本网络中将小波网络与残差块相结合,用以增强网络对图像特征的提取能力和加快网络训练效率。实验中使用真实的螺旋几何CT图像数据“Low-dose CT Grand Challenge”数据集训练网络。通过观察图像表征和计算定量参数的方法对结果进行评估,并与其他现有网络进行比较,包括图像恢复迭代残差卷积网络(IRLNet),残差编码解码卷积神经网络(REDCNN)和FBP卷积神经网络(FBPConvNet)。结果 实验结果表明,本文提出的多尺度小波残差网络优于其余对比方法。结论 本文提出的MWResNet网络能够在保持稀疏角度CT图像边缘细节信息的同时有效抑制噪声和伪影。 相似文献
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粗糙集理论是一种处理模糊和不确定性问题的工具,是一种非线性处理方法.本文基于边缘检测对图像进行小波阈值去噪,在此基础之上引入粗糙集理论划分子图并分别进行增强处理,再进行对比度增强.该算法把边缘检测去噪与粗糙集理论结合起来增强图像,实践证明具有良好的图像增强效果. 相似文献
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传统的边缘检测方法大都是基于灰度图像的,这就不能充分利用彩色图像的全部信息。文章提出了一种基于色差的彩色图像的边缘检测方法,它能快速准确地检测到图像的边缘,具有低的错判率和较高的效率,优于传统基于灰度的边缘检测方法。 相似文献
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Yüksel Özbay 《Journal of medical systems》2009,33(6):435-445
This paper presents the new automated detection method for electrocardiogram (ECG) arrhythmias. The detection system is implemented
with integration of complex valued feature extraction and classification parts. In feature extraction phase of proposed method,
the feature values for each arrhythmia are extracted using complex discrete wavelet transform (CWT). The aim of using CWT
is to compress data and to reduce training time of network without decreasing accuracy rate. Obtained complex valued features
are used as input to the complex valued artificial neural network (CVANN) for classification of ECG arrhythmias. Ten types
of the ECG arrhythmias used in this study were selected from MIT-BIH ECG Arrhythmias Database. Two different classification
tasks were performed by the proposed method. In first classification task (CT-1), whether CWT-CVANN can distinguish ECG arrhythmia
from normal sinus rhythm was examined one by one. For this purpose, nine classifiers were improved and executed in CT-1. Second
classification task (CT-2) was to recognize ten different ECG arrhythmias by one complex valued classifier with ten outputs.
Training and test sets were formed by mixing the arrhythmias in a certain order. Accuracy rates were obtained as 99.8% (averaged)
and 99.2% for the first and second classification tasks, respectively. All arrhythmias in training and test phases were classified
correctly for both of the classification tasks. 相似文献
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基于Canny算子的医用X光图像边缘检测算法研究 总被引:1,自引:0,他引:1
为了进一步加强数字图像处理技术在医学图像领域的应用,提供一种基 Canny算子的医用X先图像边缘检测方法.首先介绍边缘检测算法的理论基础,然后结合Canny算子的实现过程,说明边缘检测的所遵循的基本原则,最后对该算法进行了实验验证.从实验的结果可以看出,这种方法对医用X光图像非常有效,对利用计算机进行图像处理有着重要的现实意义. 相似文献
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Rohit Thanki Surekha Borra Vedvyas Dwivedi Komal Borisagar 《Journal of medical systems》2017,41(9):143
Nowadays medical data in terms of image files are often exchanged between different hospitals for use in telemedicine and diagnosis. Visible watermarking being extensively used for Intellectual Property identification of such medical images, leads to serious issues if failed to identify proper regions for watermark insertion. In this paper, the Region of Non-Interest (RONI) based visible watermarking for medical image authentication is proposed. In this technique, to RONI of the cover medical image is first identified using Human Visual System (HVS) model. Later, watermark logo is visibly inserted into RONI of the cover medical image to get watermarked medical image. Finally, the watermarked medical image is compared with the original medical image for measurement of imperceptibility and authenticity of proposed scheme. The experimental results showed that this proposed scheme reduces the computational complexity and improves the PSNR when compared to many existing schemes. 相似文献
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Recently, numerous concealed information test (CIT) studies have been done with event related potential (ERP) for its sufficient validity in applied use. In this study, a new approach based on wavelet coefficients (WCs) and kernel learning algorithm is proposed to identify concealed information. Totally 16 subjects went through the designed CIT paradigm and the multichannel electroencephalogram (EEG) signals were recorded. Then, the high-dimensional WCs of ERP in delta, theta, alpha and beta rhythms were extracted. For the analysis of the data, kernel principle component analysis (KPCA) and a support vector machines (SVM) classifier are implemented. The results show that WCs features are significant differences between concealed information and irrelevant information (P?<?0.05). The KPCA is able to effectively reduce feature dimensionalities and increase generalization performance of SVM. A high accuracy (93.6%) in recognizing concealed information and irrelevant information is achieved, which indicates the combination KPCA and SVM may provide a useful tool for detecting the concealed information. 相似文献
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目的探索多尺度熵结合支持向量机的方法是否可以有效检测人体脑疲劳状态,进而比较不同脑皮层位置的电极检测脑疲劳的效果。方法通过持续认知负荷任务建立脑疲劳模型,采用一款便携式脑电设备采集12名实验对象清醒和疲劳状态的脑电信号,以多尺度熵为特征,结合支持向量机算法对两种状态的脑电进行分类。结果在进行持续认知负荷任务后,实验对象的疲劳程度明显上升,NASA-TLX和KSS量表结果均具有显著的统计学差异(P<0.01);在额叶Fpz、顶叶Pz和枕叶Oz三个电极,实验对象清醒和疲劳状态脑电信号的平均分类准确率分别为92.16%、81.63%和90.54%,其中Fpz和Oz电极之间没有统计学差异(P>0.05),二者和Pz电极之间有显著的统计学差异(P<0.05)。结论多尺度熵结合支持向量机可以有效地对人体清醒和脑疲劳状态进行检测,Fpz和Oz电极比Pz电极的检测效果更好。 相似文献
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Zeyu Li Yimin Chen Yan Zhao Lifeng Zhu Shengqing Lv Jiahui Lu 《Journal of medical systems》2016,40(8):184
The interpolation technique of computed tomography angiography (CTA) image provides the ability for 3D reconstruction, as well as reduces the detect cost and the amount of radiation. However, most of the image interpolation algorithms cannot take the automation and accuracy into account. This study provides a new edge matching interpolation algorithm based on wavelet decomposition of CTA. It includes mark, scale and calculation (MSC). Combining the real clinical image data, this study mainly introduces how to search for proportional factor and use the root mean square operator to find a mean value. Furthermore, we re- synthesize the high frequency and low frequency parts of the processed image by wavelet inverse operation, and get the final interpolation image. MSC can make up for the shortage of the conventional Computed Tomography (CT) and Magnetic Resonance Imaging(MRI) examination. The radiation absorption and the time to check through the proposed synthesized image were significantly reduced. In clinical application, it can help doctor to find hidden lesions in time. Simultaneously, the patients get less economic burden as well as less radiation exposure absorbed. 相似文献
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QT间期测量的小波分析方法 总被引:1,自引:0,他引:1
目的 准确获取人体心电信号 (ECG)中的 QT间期值。方法 利用小波变换多尺度多分辨的特点 ,将心电信号进行多尺度分解 ,把不同频带的信号显现在小波分解各个尺度上。特征尺度上准确定位 QRS波及T波的起始点 ,从而获得 QT间期的精确值。结果 1在 2 m V的心电信号上引入峰峰值为 1m V的误差信号 ,利用二进小波进行分解和重构得到相对精确的心电波形 ,测得 QRS波、P波、T波的宽度最大误差分别为 5 .75 % ,5 .2 % ,3.8%。 2用小波分析方法对 MIT/ BIH数据库中的 ECG信号进行处理后 ,测量得到各间期的平均值及标准偏差 ,可以反映出 QT间期及相应各间期的稳定性。结论 人体心电信号随着检测状态及时间的变化具有明显的非平稳性及包含许多干扰的特点。利用小波变换将心电信号进行处理能够获得 QT间期的精确值 ,为临床诊断提供了更加准确的依据 相似文献