Assessment of myocardial lesion size during in vitro radio frequency catheter ablation

We report our experience with a system that utilizes changes in several biophysical characteristics of cardiac tissue to determine lesion formation and to estimate lesion size both on and off-line in vitro during radio frequency (RF) energy delivery. We analyzed the reactive and resistive components of tissue impedance and tracked the change of phase angle during RF ablation. We correlated the amount of tissue damage with these and other biophysical parameters and compared them with off-line analysis. We found that there are irreversible changes in the reactive and resistive components of impedance that occurred during tissue ablation. The irreversible changes of these components are greater in magnitude, and correlate better with the size of lesions than that of impedance alone that is currently used. Numerically, the best single on-line and off-line correlation for combined perpendicular and parallel electrode orientation was with phase angle. On-line and off-line capacitance and susceptance correlations were essentially similar suggesting that they may be useful as lesion size predictors, given these parameter's persistent change without temperature sensitivity. This study indicates that it is technically feasible to assess lesion formation using biophysical parameters.     

Image classification using correlation tensor analysis

Images, as high-dimensional data, usually embody large variabilities. To classify images for versatile applications, an effective algorithm is necessarily designed by systematically considering the data structure, similarity metric, discriminant subspace, and classifier. In this paper, we provide evidence that, besides the Fisher criterion, graph embedding, and tensorization used in many existing methods, the correlation-based similarity metric embodied in supervised multilinear discriminant subspace learning can additionally improve the classification performance. In particular, a novel discriminant subspace learning algorithm, called correlation tensor analysis (CTA), is designed to incorporate both graph-embedded correlational mapping and discriminant analysis in a Fisher type of learning manner. The correlation metric can estimate intrinsic angles and distances for the locally isometric embedding, which can deal with the case when Euclidean metric is incapable of capturing the intrinsic similarities between data points. CTA learns multiple interrelated subspaces to obtain a low-dimensional data representation reflecting both class label information and intrinsic geometric structure of the data distribution. Extensive comparisons with most popular subspace learning methods on face recognition evaluation demonstrate the effectiveness and superiority of CTA. Parameter analysis also reveals its robustness.     

B-spline explicit active surfaces: an efficient framework for real-time 3-D region-based segmentation

A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also show that this framework allows evolving the active contour using local region-based terms, thereby overcoming the limitations of the original method while preserving computational speed. The feasibility of real-time 3-D segmentation is demonstrated using simulated and medical data such as liver computer tomography and cardiac ultrasound images.     

DFC++ Processing Framework Concept

Development of modern Software Defined Radio (SDR) based communication systems can be accelerated significantly by the use of processing frameworks. The evolution of SDR and the involved departure from digital representations of classical radio architecture towards more abstract software systems raises new requirements of increased flexibility and versatility. The proposed Data Flow Control for C++ (DFC++) processing framework concept addresses those requirements by employing modern programming techniques and flow control mechanisms to allow for variable data rates, dynamic paths, and flexible component designs. Another important trend is the integration of various embedded platforms in the software radio domain. The rapidly increasing performance and efficiency of embedded processors enables the deployment of SDR systems in more space and power constrained environments. Therefore covering a heterogeneous hardware selection becomes increasingly important for processing frameworks. By relying exclusively on C++ and minimizing external dependencies, DFC++ is specifically aiming for excellent portability and adaptability to support a wide range of current and future software radio projects while maintaining high performance and ease of use. This paper introduces the key aspects of the DFC++ concept and implementation with focus on the reference pointer based data transport mechanisms responsible for the propagation of user data between different processing components.     

Analytical comparison of sensor signal processing enhancements forNDT synthetic aperture ultrasonic imaging

The results of a detailed analytical study of the effects of sensor processing techniques on clutter suppression and image enhancement for nondestructive testing (NDT) systems are presented. A relatively simple beamforming/diffraction model is developed for near-field, wideband, synthetic aperture ultrasonic imaging in NDT systems. The physical model is used to quantitatively evaluate a variety of front-end sensor signal processing tradeoffs for the enhanced detection and sizing of defects. It is shown using statistical microscopic scattering calculations that a combination of increased spatial sampling and rectangular windowing can increase the signal-to-clutter ratio by ~10 dB while maintaining crack size resolutions well below future projected specifications. The sensor signal processing image enhancements are demonstrated by the construction of simulated strip-map SAFT (synthetic aperture focusing technique) images of metallic crack defects in the presence of large numbers of randomly distributed clutter (simulated grain boundary) scatterers.     

Elastic and plastic contributions to X-ray Line broadening of InGaAsP/InP Heterostructures

The coherency state of MOCVD grown InGaAsP/InP double-heterostructure wafers was examined and their effects on the structural properties were determined in this study. Lattice mismatches were measured using {511} asymmetric and (400) symmetric x-ray reflections. The chemical lattice misfit and the elastic strain were also calculated. Misfit dislocations were examined by both x-ray topography and photoluminescence imaging. The x-ray full width at half maximum (FWHM) varied with the degree of mismatch. The largest FWHM was obtained for samples containing the misfit dislocations. It was found that FWHM is influenced not only by the plastic deformation, but also by the elastic strain. To model the dependence of the FWHM, the radius of curvature was measured, and its contribution to the x-ray line broadening was calculated. Also, the contribution from misfit dislocations was taken into account. This model assumes that the dislocations are planar and interact weakly with each other. Good agreement between measured and calculated values was obtained. Thus, it is concluded that the major contribution to x-ray line broadening ofelastically strained sample is the lattice curvature induced by misfit strain, and that the dominant factor affecting x-ray FWHM ofplastically deformed sample is lattice relaxation induced by misfit dislocation.     

A 0.9-V microcontroller for portable applications

A 0.9-1.6-V, 1-MHz, 8-b microcontroller based on the 68HC08 architecture is presented. In addition to standard digital microcontroller functions, the chip features RAM, ROM, phase-locked loop (PLL) clock synthesis, and liquid crystal displays (LCD) drive capabilities operating from the voltage supply range of a single AA or AAA battery. The design used a library of CMOS microcontroller building blocks, converted into a low-voltage technology using unilateral transistors. The design approach was to optimize the conversion strategy for each functional block and to provide new designs when the conversion was insufficient. The chip exceeded specifications with blocks showing full functionality down to 0.7 V     

Effect of organic/inorganic coating on moisture diffusion in a chip-on-board package with globtop

The moisture diffusion in globtop material for a chip-on-board (COB) package coated with SiN_x and silicone, respectively, or coated with SiN_x plus silicone were measured by embedding a humidity sensor in the globtop and recording the capacitive change in three different temperature/humidity environments. The experimental results were simulated by Fick’s diffusion law with finite-element method modeling. The moisture diffusion coefficients and activation energies were calculated to quantitatively compare the moisture-resistance effects of different coatings. For example, at 85°C/85% RH, the moisture diffusion coefficients for the uncoated reference, SiN_x-coated, silicone-coated, and silicone/SiN_x double-layered coated samples are 1E-5, 0.8E-5, 0.7E-5, and 0.2E-5 mm²/s, respectively. The experimental and simulation results show that double-layered coating with silicone/SiN_x has excellent moisture-resistance properties because it not only smoothes the steps on a printed circuit board (PCB) but also keeps the good moisture resistance of the inorganic films.     

Wiener filters in canonical coordinates for transform coding,filtering, and quantizing

Canonical correlations are used to decompose the Wiener filter into a whitening transform coder, a canonical filter, and a coloring transform decoder. The outputs of the whitening transform coder are called canonical coordinates; these are the coordinates that are reduced in rank and quantized in our finite-precision version of the Gauss-Markov theorem. Canonical correlations are, in fact, cosines of the canonical, angles between a source vector and a measurement vector. They produce new formulas for error covariance, spectral flatness, and entropy     

Knowledge maps for knowledge mining: application toR&D/technology management

Most of the world's archive of knowledge sources remains untouched by those who could greatly benefit from accessing and utilizing this information. The fundamental barriers to access and utilization by these users involve the content and format of this information. These users are not particularly interested in data compilations, research methods, and discussions of related literature. Instead, they are interested in the knowledge available from these sources in terms of concepts and principles that can enhance their planning, decision making, and allocation of resources. The article focuses on meeting these needs via a six step knowledge mining methodology that relies upon user oriented knowledge maps. This concept is illustrated in the context of R&D/technology management