Motion correction for coronary stent reconstruction from rotational X-ray projection sequences

This paper presents a new method for 3-D tomographic reconstruction of stent in X-ray cardiac rotational angiography. The method relies on 2-D motion correction from two radiopaque markerballs located on each side of the stent. The two markerballs are on a guidewire and linked to the balloon, which is introduced into the artery. Once the balloon has been inflated, deflated, and the stent deployed, a rotational sequence around the patient is acquired. Under the assumption that the guidewire and the stent have the same 3-D motion during rotational acquisition, we developed an algorithm to correct cardiac stent motion on the 2-D X-ray projection images. The 3-D image of the deployed stent is then reconstructed with the Feldkamp algorithm using all the available projections. Although the correction is an approximation, we show that the intrinsic geometrical error of our method has no visual impact on the reconstruction when the 2-D markerball centers are exactly detected and the markerballs have the same 3-D motion as the stent. Qualitative and quantitative results on simulated sequences under different realistic conditions demonstrate the robustness of the method. Finally, results from animal data acquired on a rotational angiography device are presented.     

Fabrication of AD/DA microfluidic converter using deep reactive ion etching of silicon and low temperature wafer bonding

The purpose of this work is to describe an original process that has been designed for the fabrication of a microfluidic converter. The fabrication is based on deep reactive ion etching of silicon and low temperature full wafer adhesive bonding. The technology development includes an improvement of the bonding process in order to produce an adaptive strength of SU-8 bond which not only ensures absence of debonding failures during the silicon deep etching procedure and the subsequent dicing procedure, but also avoids the potential SU-8 overflow leakage into channels due to the bonding step. Besides, the originality of the work is not only in the process but also in the design of the device. Common actuation method for microfluidic system is either based on closed-channel continuous-flow microfluidic (CMF) or droplet-based microfluidic (DMF). Both of them have advantages and disadvantages, and their integration on a single system is in dire need. In this paper, we briefly discuss the concept of microfluidic converter, integrating CMF with DMF, which can: (i) continuously preload reagents, (ii) independently manipulate several droplets, (iii) recombine and export samples into closed-channel continuous flow, making it ideal for interfacing to liquid-handling instruments and micro-analytical instruments.     

In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head

In vivo measurements of equivalent resistivities of skull (rho(skull)) and brain (rho(brain)) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that rho(skull)/rho(brain) is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in rho(brain)(average = 301 omega x cm, SD = 13%) and rho(skull)(average = 12230 omega x cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of rho(skull)/rho(brain) corresponding to different subjects. Earlier results show the necessity of calibrating rho(brain) and rho(skull) by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.     

Velocity selective filters recursively implemented in the spatiotemporal domain.

Energy-based methods for motion estimation in image sequences process the input data either in the spatiotemporal or in the frequency domain. In both cases, the algorithms already described in the literature often require a huge number of elementary operations. In this paper, we describe a class of velocity selective filters which yield an accurate detection of the edges moving in the sequence. We first present a filtering scheme based on a convolution operation computed on a finite size neighborhood and describe its properties in the spatiotemporal and frequency domains. Then, we show that filters with similar properties can be implemented recursively, i.e., as convolutions computed on infinite-size neighborhoods. As an example, we finally show the filters' responses in the case of two superimposed translational motions.     

Scalable Data Processing for Community Sensing Applications

Participatory Sensing is a new computing paradigm that aims to turn personal mobile devices into advanced mobile sensing networks. For popular applications, we can expect a huge number of users to both contribute with sensor data and request information from the system. In such scenario, scalability of data processing becomes a major issue. In this paper, we present a system for supporting participatory sensing applications that leverages cluster or cloud infrastructures to provide a scalable data processing infrastructure. We propose and evaluate three strategies for data processing in this architecture.     

Digital signature to help network management using flow analysis

Because of constant growth in proportion and complexity of networks, flow analysis has become an indispensable tool for network management mechanisms. Through this resource, a traffic characterization, called digital signature of network segment using flow analysis (DSNSF), is accomplished. The models used for this purpose are the ant colony optimization metaheuristic, the Holt–Winters forecasting method and the statistical procedure, principal component analysis. The obtained DSNSF by each model is compared with the actual traffic of packets and bits and then subjected to specific evaluations in order to measure its accuracy. The experimental results show that the three methods could achieve good correlation indices and low normalized mean square error values between the DSNSF curve and the real traffic movement, indicating a good adaptability and efficiency in characterizing a network traffic segment. Copyright © 2015 John Wiley & Sons, Ltd.     

Effect of bit-to-bit dependence on packet error rate using asynchronous DS-CDMA for mobile packet radio networks

The probability of packet success for asynchronous direct sequence code division multiple access (DS-CDMA) over the multipath fading channel is investigated under different fading conditions and for different cases. We studied the bit-to-bit dependence caused by the multipath fading and by the multiple access interference (MAI) originating from the chip and phase offsets between the desired and interfering signals. We investigated the effect of using the Gaussian versus the improved Gaussian process on the computation of probability of packet success as well as the effect of the bit-to-bit dependence within a packet. The improved Gaussian approximation provides more accurate values for the probability of bit error for any number of simultaneous users, while it also allows us to incorporate the effects of bit-to-bit dependence into the calculations of the probability of packet success.This paper was presented in part at the 17th Biennial Symposium on Communiations, Kingston, June 1994. This work was supported by a strategic grant (STR-0100720) from the Natural Sciences and Engineering Research Council (NSERC) of Canada.     

Transient-enhanced diffusion in shallow-junction formation

Shallow junctions are formed in crystalline Si by low-energy ion implantation of B⁺, P⁺, or As⁺ species accompanied by electrical activation of dopants by rapid thermal annealing and the special case of spike annealing. Diffusion depths were determined by secondary ion-mass spectroscopy (SIMS). Electrical activation was characterized by sheet resistance, Hall coefficient, and reverse-bias diode-leakage measurements. The B⁺ and P⁺ species exhibit transient-enhanced diffusion (TED) caused by transient excess populations of Si interstitials. The electrically activated fraction of implanted dopants depends mainly on the temperature for B⁺ species, while for P⁺ species, it depends on both temperature and P⁺ dose. The relatively small amount of diffusion associated with As⁺ implants is favorable for shallow-junction formation with spike annealing.     

Design and Test of a Certifiable ASIC for a Safety-Critical Gas Burner Control System

The purpose of this paper is to present a methodology and tools for the design and test of an EN298 compliant ASIC chip for a safety-critical gas burner control system. Safe operation, as far as the critical variable is concerned, is guaranteed in the presence of two simultaneous faults. Emphasis is put on circumventing methodology, EDA (Electronic Design Automation) and foundry limitations and on product certification requirements.     

A stochastic method for Bayesian estimation of hidden Markov random field models with application to a color model.

We propose a new stochastic algorithm for computing useful Bayesian estimators of hidden Markov random field (HMRF) models that we call exploration/selection/estimation (ESE) procedure. The algorithm is based on an optimization algorithm of O. Fran?ois, called the exploration/selection (E/S) algorithm. The novelty consists of using the a posteriori distribution of the HMRF, as exploration distribution in the E/S algorithm. The ESE procedure computes the estimation of the likelihood parameters and the optimal number of region classes, according to global constraints, as well as the segmentation of the image. In our formulation, the total number of region classes is fixed, but classes are allowed or disallowed dynamically. This framework replaces the mechanism of the split-and-merge of regions that can be used in the context of image segmentation. The procedure is applied to the estimation of a HMRF color model for images, whose likelihood is based on multivariate distributions, with each component following a Beta distribution. Meanwhile, a method for computing the maximum likelihood estimators of Beta distributions is presented. Experimental results performed on 100 natural images are reported. We also include a proof of convergence of the E/S algorithm in the case of nonsymmetric exploration graphs.