Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

A virtual actuator and sensor approach for fault tolerant control of LPV systems

In this paper, a fault tolerant control (FTC) strategy using virtual actuators and sensors for linear parameter varying (LPV) systems is proposed. The main idea of this FTC method, initially developed for LTI systems, is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator/sensor is modified adding the virtual actuator/sensor block that masks the actuator/sensor fault. The suggested technique is an active FTC strategy that reconfigures the virtual actuator/sensor on-line taking into account faults and operating point changes. The stability of the reconfigured control loop is guaranteed if the faulty plant is stabilizable/detectable. The LPV virtual actuator/sensor is designed using polytopic LPV techniques and linear matrix inequalities (LMIs). A two-tank system simulator is used to assess the performance of the proposed method. In particular, it is shown that the application of the proposed technique results in an improvement, in terms of performance, with respect to the LTI counterpart.     

Development of a variable selection method for soft sensor using artificial neural network and nonnegative garrote

This paper developed a new variable selection method for soft sensor applications using the nonnegative garrote (NNG) and artificial neural network (ANN). The proposed method employs the ANN to generate a well-trained network, and then uses the NNG to conduct the accurate shrinkage of input weights of the ANN. This paper took Bayesian information criterion as the model evaluation criterion, and the optimal garrote parameter s was determined by v-fold cross-validation. The performance of the proposed algorithm was compared to existing state-of-art variable selection methods. Two artificial dataset examples and a real industrial application for air separation process were applied to demonstrate the performance of the methods. The experimental results showed that the proposed method presented better model accuracy with fewer variables selected, compared to other state-of-art methods.     

无线传感器网络连通恢复综述

针对无线传感器网络中连通恢复问题,分析和总结了近年来相关的主要方向和研究成果,同时对无线传感器网络连通恢复解决方法进行了分类和总结,并指出了其中的不足与未来的研究方向。     

带速度控制的能量高效的数据收集算法

无线传感网络中, 在保证节点能耗较低, 从而延长网络寿命的基础上, 减小数据收集时延是数据收集的核心问题。为此, 提出了一种带速度控制的能量高效的移动数据收集方法。该方法首先基于节点剩余能量进行动态分簇, 每个簇形成两个簇头来分担簇头能耗; 然后给小车装载双天线, 使得节点能够MIMO数据上传; 最后利用TSP问题找到一条最优路径, 并对移动小车的速度进行控制, 以便小车能够更快地收集数据。仿真实验结果表明, 该方法能够均衡网络流量, 延长网络寿命; 与其他算法相比, 数据收集时延较短。     

基于无线传感网的智能环境监控系统设计

针对传统环境监控系统存在的缺点,设计了一种新型无线传感器网络的环境监控系统。系统采用分布式融合结构,通过终端节点的多种传感器采集环境信息,终端对信息预处理后实时将信息传输到协调器。协调器融合各终端传感器信息,提取精确信息上传至融合中心,融合中心通过分析数据发布命令给控制中心,控制中心利用单片机驱动电机可以自动或手动控制风机和水泵对环境进行调节和控制。同时,系统还具有自动预警功能。通过验证,该系统稳定、可靠,能广泛应用于不同领域的分布式多点环境监控。     

汽车胎压监测系统的设计及其通信抗干扰研究

针对大多数直接式汽车胎压监测系统组件集成度低、体积和功耗较大等问题,提出了一种基于短距离无线通信ZigBee技术的新型胎压无线监测系统的设计。主要采用TI的CC2530芯片和英飞凌SP12集成式数字传感器,实现对汽车轮胎内部状态的实时监测。采用软硬件协同设计以降低系统功耗,并通过多点轮询通信方式和ZigBee高级加密设置保障了其无线通信的抗干扰能力。     

硅压阻式气压高度计的设计与实现

采用硅压阻式压力传感器,以ATmega88PA为控制器设计了气压高度计。内嵌全温度范围的曲面拟合算法进行温度补偿及线性化处理,解决了压力传感器的温漂和非线性问题,并用海拔高度与气压的关系计算高度。测量结果通过RS-485接口发送给上位机。测试结果表明,该气压高度计压力测量误差优于0.50‰,分辨率为0.01 h Pa,线性度为0.999 9;标准大气环境下高度测量误差为0.16 m,线性度为0.999 8。该气压高度计具有质量小、功耗低、精度高、工作可靠等优点。     

应力型微悬臂梁生化传感器响应机理研究进展

针对静态微悬臂梁表面特异性结合产生表面应力信号的响应机制问题,介绍了微悬臂梁生化传感器的工作原理,阐述了应力响应机制的简化模型,从纵向界面上和横向分子间2个方面对特异性吸附引起的悬臂梁表面应力的变化进行了剖析,讨论了界面能变化、位阻作用、静电力、氢键作用等与表面应力大小及方向之间的关系,总结了应力型微悬臂梁生化传感器的响应机理的研究。     

基于FPGA的多路矿用气体传感器智能调校系统

矿用气体传感器因煤矿安全被大量使用,国家规定必须定期进行调校,目前的传感器调校系统可同时对5-8台传感器进行调校,针对大中型煤矿生产过程中需要调校的矿用气体传感器数量大、调校耗时长的现状,提出了一种基于单片机与现场可编程门阵列（FPGA）的64路气体传感器调校系统,介绍了系统的整体设计并详细阐述了该系统的气路控制模块和传感器输出信号采集模块,使用Verilog语言在QuartusⅡ工具中实现FPGA的逻辑设计、仿真和综合。结果证明：该系统能有效地完成对64路气体传感器同时调校的目的,很大程度节省了人力消耗,提高了调校效率,节约了调校时间。