Magnetic-resonance image segmentation based on improved variable weight multi-resolution Markov random field in undecimated complex wavelet domain

To solve the problem that the magnetic resonance (MR) image has weak boundaries, large amount of information, and low signal-to-noise ratio, we propose an image segmentation method based on the multi-resolution Markov random field (MRMRF) model. The algorithm uses undecimated dual-tree complex wavelet transformation to transform the image into multiple scales. The transformed low-frequency scale histogram is used to improve the initial clustering center of the K-means algorithm, and then other cluster centers are selected according to the maximum distance rule to obtain the coarse-scale segmentation. The results are then segmented by the improved MRMRF model. In order to solve the problem of fuzzy edge segmentation caused by the gray level inhomogeneity of MR image segmentation under the MRMRF model, it is proposed to introduce variable weight parameters in the segmentation process of each scale. Furthermore, the final segmentation results are optimized. We name this algorithm the variable-weight multi-resolution Markov random field (VWMRMRF). The simulation and clinical MR image segmentation verification show that the VWMRMRF algorithm has high segmentation accuracy and robustness, and can accurately and stably achieve low signal-to-noise ratio, weak boundary MR image segmentation.     

能耗均衡的无线传感器网络的入侵检测机制

针对无线传感器网络中能量有限和安全问题,本文提出了一种基于能耗均衡的无线传感器的入侵检测机制.首先在无线传感器现有的分簇模型上划分若干Sector,然后在某些节点上部署IDS,提出入侵检测的算法,利用仿真验证了本文所提出的模型与算法,结果表明可使网络节点的能耗得到有效的降低,同时提高了检测错误数据和异常节点的准确率.     

基于遗传算法的亚100nm SOI MOSFET模型参数提取

为了简化亚100nm SOI MOSFET BSIMSOI4的模型参数提取过程,实现全局优化,使用了遗传算法技术,并提出了保留多个最优的自适应遗传算法.该算法通过保留最优个体的多个拷贝,对适应度高和适应度低的个体分别进行诱导变异和动态变异,在进化起始阶段和终止阶段分别执行随机交叉和诱导交叉,既具有全局优化特性,又加速了局部搜索过程,提高了最终解的质量.不同种群数和进化代数条件下的参数提取实例表明,该算法提取精度高、速度快,全局优化稳定性好;适当增加种群数,有利于加速算法的全局收敛过程.