Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images

Human investigators instinctively segment medical images into their anatomical components, drawing upon prior knowledge of anatomy to overcome image artifacts, noise, and lack of tissue contrast. The authors describe: 1) the development and use of a brain tissue probability model for the segmentation of multiple sclerosis (MS) lesions in magnetic resonance (MR) brain images, and 2) an empirical comparison of the performance of statistical and decision tree classifiers, applied to MS lesion segmentation. Based on MR image data obtained from healthy volunteers, the model provides prior probabilities of brain tissue distribution per unit voxel in a standardized 3-D "brain space". In comparison to purely data-driven segmentation, the use of the model to guide the segmentation of MS lesions reduced the volume of false positive lesions by 50-80%     

Adaptive filtering of evoked potentials with radial-basis-function neural network prefilter

Evoked potentials (EPs) are time-varying signals typically buried in relatively large background noise. To extract the EP more effectively from noise, we had previously developed an approach using an adaptive signal enhancer (ASE) (Chen et al., 1995). ASE requires a proper reference input signal for its optimal performance. Ensemble- and moving window-averages were formerly used with good results. In this paper, we present a new method to provide even more effective reference inputs for the ASE. Specifically, a Gaussian radial basis function neural network (RBFNN) was used to preprocess raw EP signals before serving as the reference input. Since the RBFNN has built-in nonlinear activation functions that enable it to closely fit any function mapping, the output of RBFNN can effectively track the signal variations of EP. Results confirmed the superior performance of ASE with RBFNN over the previous method.     

How small the contacts could be optimal for nanoscale organic transistors?

We report on a study seeking an optimized contact configuration for organic transistors that minimizes contact effects but maintains smallest contact size. We begin with the bulk access resistance in staggered transistors which results from the charge transport through the organic semiconductor film. Bulk access resistance is an intrinsic contributor to the contact resistance which has been little understood due to lack of a reliable study tool. In this work, we utilize the inner transported power inside the semiconductor film as a medium to investigate the contact resistance and the relevant contact effects. We examine the influences of the organic film thickness (t_SC), the channel length (L), the underlying charge transport and various organic semiconductor materials with variable carrier mobility. A roughly optimal contact length (L_C) of L_C0 ≈ 6t_SC is obtained. The results reveal that besides the device architecture the underlying charge transport should be also taken into account in designing organic transistors for practical application.     

Outage Performance and Cooperative Diversity Under Amplify and Forward Relaying in Cognitive Radio Networks

This paper investigates the outage and diversity performance in a cognitive radio (CR) network, in which data are transmitted through amplify-and-forward protocol. A fixed CR node is selected as relay to combat fading effect. The CR user transmits or relays data when the result of cooperative spectrum sensing indicates that primary user (PU) channel is free and the relay node stops performing the protocol as soon as the PU is detected to be active. A closed-form expression of outage probability for the CR network is calculated based on which diversity order is derived. The results show that the proposed scheme suffers a loss in diversity order. To compensate for this loss, a repetition-based scheme is proposed in a delay-insensitive system at the cost of the challenge in implementation. In this case, we evaluate the outage performance and the average transmit duration and then compare them with the ones in the delay-sensitive system. Asymptotic analysis is also presented to show the outage performance advantage of using a relay over the one without using it. The numerical results presented in the paper verify our analysis.     

Electrically Activated Paper Actuators

This paper describes the design and fabrication of electrically controlled paper actuators that operate based on the dimensional changes that occur in paper when the moisture absorbed on the surface of the cellulose fibers changes. These actuators are called “Hygroexpansive Electrothermal Paper Actuators” (HEPAs). The actuators are made from paper, conducting polymer, and adhesive tape. They are lightweight, inexpensive, and can be fabricated using simple printing techniques. The central element of the HEPAs is a porous conducting path (used to provide electrothermal heating) that changes the moisture content of the paper and causes actuation. This conducting path is made by embedding a conducting polymer (PEDOT:PSS) within the paper, and thus making a paper/polymer composite that retains the porosity and hydrophilicity of paper. Different types of HEPAs (straight, precurved, and creased) achieved different types of motions (e.g., bending motion, accordion type motion). A theoretical model for their behavior is proposed. These actuators have been used for the manipulation of liquids and for the fabrication of an optical shutter.     

Ice‐Templated Scaffolds with Microridged Pores Direct DRG Neurite Growth

Successful spinal cord repair is thought to be promoted with hierarchically structured scaffolds. These should combine aligned porosity with additional linear features on the micrometer scale to guide axons across multiple length scales. Such scaffolds are generated through the carefully controlled directional solidification of an aqueous biopolymer solution, followed by lyophilization. Under specific freezing conditions this yields a highly regular and aligned lamellar architecture. This architecture exhibits uniform ridges of controlled height and width on the lamellar surface. These ridges run parallel to the pore axis, serving as secondary guidance features. The ridges are capable of linearly aligning 62.4% of chick dorsal root ganglia neurites to within ±10° of the ridge direction. Notably, neurites sprouting perpendicular to the ridge are guided into alignment with these microridged features.     

将RF信号转换为数字信号的CMOS转换器

从频率计数与合成到传感器信号调整等很多应用都需要将RF信号转换为数字逻辑电平。在这些情况下,设计者一般采用一个高速电压比较器完成RF到数字信号的转换工作。由于电压比较器具有高增益,它们一般有很好的灵敏度,但也会带来一些问题。高速比较器价格高,很难找到现成的商品,并且易于被快速淘汰。     

MnO2-Based Electrochemical Supercapacitors on Flexible Carbon Substrates

Manganese dioxide films were grown on large area flexible carbon aerogel substrates. Characterization by x-ray diffraction confirmed α-MnO₂ growth. Three types of films were compared as a function of hexamethylenetetramine (HMTA) concentration during growth. The highest concentration of HM TA produced MnO₂ flower-like films, as observed by scanning electron microscopy, whose thickness and surface coverage lead to both a higher specific capacitance and higher series resistance. Specific capacitance was measured to be 64 F/g using a galvanostatic setup, compared to the 47 F/g-specific capacitance of the carbon aerogel substrate. Such supercapacitor devices can be fabricated on large area sheets of carbon aerogel to achieve high total capacitance.     

A Tree-Based Data Collecting Network Structure for Wireless Sensor Networks

In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly correlated, and hence energy saving using in-network data fusion becomes possible. A traditional data fusion scheme starts with dividing the network into clusters, followed by electing a sensor node as cluster head in each cluster. A cluster head is responsible for collecting data from all its cluster members, performing data fusion on these data and transmitting the fused data to the base station. Assuming that a sensor node is only capable of handling a single node-to-node transmission at a time and each transmission takes T time-slots, a cluster head with n cluster members will take at least nT time-slots to collect data from all its cluster members. In this paper, a tree-based network structure and its formation algorithms are proposed. Simulation results show that the proposed network structure can greatly reduce the delay in data collection.