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基于模糊核聚类的MR图像分割新算法   总被引:1,自引:0,他引:1  
在传统的模糊聚类算法中引入了核函数,同时引入了控制邻域作用的约束项,提出了改进的基于模糊核聚类的MR图像分割新算法.通过对模拟图和仿真的脑部MR图像的分割实验,证明本算法可以有效地分割含有噪声的图像.  相似文献
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Breast cancer is the second leading cause of death in women. It occurs when cells in the breast begin to grow out of control and invade nearby tissues or spread throughout the body. The limitations of mammography as a screening modality, especially in young women with denser breasts, necessitated the development of novel and more effective screening strategies with acceptable sensitivity and specificity. The aim of this study was to develop a feasible interpretive software system which was able to detect and classify breast cancer patients by employing techniques of different analytical software. The protocol described uses 6,000 pieces of thermal data collected from 16-sensors, eight placed on the surface of each breast. Data was collected every 5 min for the duration of the test period. Placement of sensors was accomplished with the use of a template design from information provided by the national tumor registry to insure that the information was collected in areas of the breast where most breast cancers develop. Data in this study was collected from 90 individuals exhibiting four different breast conditions, namely: normal, benign, cancer and suspected-cancer. The temperature data collected from these 16 sensors placed on the surface of each breast were fed as inputs to the classifiers. Comparisons were made on five different kinds of classifiers: back-propagation algorithm, probabilistic neural network, fuzzy (Sugeno-type), Gaussian mixture model and support vector machine. These classifiers were able to attain approximately 80% accuracy in classifying the four different diagnoses (normal, benign, cancer and suspected-cancer). Gaussian mixture model was the most sensitive classifier, achieving the highest sensitivity of 94.8%. Support vector machine was considered the best classifier as it was able to produce the most specific and accurate results. Based on these evaluations, this current effort shows the feasibility of applying analytical software techniques together with the real-time functional thermal analysis to develop a potential tool for the detection and classification of breast cancer.  相似文献
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基于聚类算法对数据对象多个属性综合聚类的特点,研究网络流量的GMM模型及其在数据流尺度上的Lognormal分布。用EM算法研究了具有交互特征的网络流量的分类;通过与K-means算法比较,讨论了EM算法在流量聚类中的适用性;通过平衡和不平衡流量的聚类分析,研究了不同类型流量GMM建模的有效性。研究流量的幂律关系及其在不同尺度间的传递性,用户行为和应用程序特征通过传输层控制协议分解传递到IP层后,在数据包尺度上表现出分形和自相似性,在数据流尺度上表现出Log- normal分布。  相似文献
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Diabetes is a disorder of metabolism—the way our bodies use digested food for growth and energy. The most common form of diabetes is Type 2 diabetes. Abnormal plantar pressures are considered to play a major role in the pathologies of neuropathic ulcers in the diabetic foot. The purpose of this study was to examine the plantar pressure distribution in normal, diabetic Type 2 with and without neuropathy subjects. Foot scans were obtained using the F-scan (Tekscan USA) pressure measurement system. Various discrete wavelet coefficients were evaluated from the foot images. These extracted parameters were extracted using the discrete wavelet transform (DWT) and presented to the Gaussian mixture model (GMM) and a four-layer feed forward neural network for classification. We demonstrated a sensitivity of 100% and a specificity of more than 85% for the classifiers.  相似文献
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提出一种基于子图像邻域梯度信息度量的边界提取算法,通过构造邻域信息映射矩阵并利用矩阵梯度信息度量值提取图像目标的有效边界,详细阐述了应用本文算法实现劣质液滴图像的边界检测及接触角测量的方法与步骤。实验结果表明:本文算法能有效地提取劣质液滴图像的目标边界,完成液滴接触角的自动计算,接触角计算结果与人工计算结果基本一致。  相似文献
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水平集方法(LSM)图像分割的本质是求解一个随时间变化的偏微分方程,而使用变分法求解此水平集方程(LSE)往往要耗费过多的计算时间。为了减少算法的运行时间,提出了一种快速水平集图像分割算法。该算法在模糊聚类水平集方法(FCM-LSM)的基础上使用高斯混合模型(GMM)改造其隶属度损失函数,并利用离散网格Boltzmann方法(LBM)求解水平集方程。实验结果表明:本文提出的算法无论是在执行效率上还是在分割效果上都优于传统方法,证明了算法的可行性。  相似文献
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