Statistical modelling of spectrum occupancy

A novel method of modelling spectrum occupancy is identified. Good agreement is demonstrated between a conceptual formula for new two-dimensional transition probabilities and estimates from experimental data. Application to radio system design and frequency management is explained.<>     

A systematic optimization strategy for microwave device modelling

The degree of ill-conditioning in the small-signal GaAs MESFET equivalent circuit model is formally quantified using a systematically formulated principal components sensitivity analysis procedure. With this procedure it is possible to estimate for the first time how reliable the component values are in the optimized model. On this basis the extraction of the MESFET equivalent circuit model is compared using electrical model components and physical model parameters. An optimization strategy which improves the condition number of the model so that rapid convergence and accurate models are ensured is presented. This technique transforms the axes of the model from the equivalent circuit components, which are correlated, to the uncorrelated principal component aces, which can be systematically scaled to eliminate ill-conditioning. Using this technique it is possible to obtain accurate estimates of the insensitive model parameters such as the parasitic resistances without resorting to direct measurement techniques     

New modelling strategy for representing asymmetric traffic loads on LANs

A new technique for modelling asymmetric traffic load distributions on local area networks (LANs) is presented. The traffic model which is analytical and easy to implement into discrete event computer simulations also has the benefit of providing expressions for the higher mathematical moments of the traffic load distribution.<>     

Statistical channel modelling and performance evaluation in satellite personal communications

This paper is concerned with channel modelling for satellite personal communications and with the associated problem of performance evaluation. Channel characteristics for personal communications tend to differ from those traditionally accepted for vehicular communications. In this paper we report on modelling aspects for both wideband and narrowband personal communications. Then we consider performance evaluation for low-altitude earth orbit (LEO) satellite systems in terms of bit error probability and outage probability. To evaluate the outage probability for LEO systems, a tight and simple upper bound is finally provided. © 1998 John Wiley & Sons, Ltd.     

Statistical modelling of polarisation induced fading in interferometric fibre sensors

The probability functions associated with the polarisation parameters of an optical fibre interferometer, and the concomitant polarisation fading problems which arises have been experimentally and theoretically investigated. Good agreement between experimental results and theoretical models are obtained.<>     

Approaching Artery Rigid Dynamics in IVUS

Tissue biomechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation. Since intravascular ultrasound (IVUS) sequences allow visualizing vessel morphology and reflect its dynamics, this technique represents a useful tool for evaluation of tissue mechanical properties. Image misalignment introduced by vessel–catheter motion is a major artifact for a proper tracking of tissue deformation. In this work, we focus on compensating and assessing IVUS rigid in-plane motion due to heart beating. Motion parameters are computed by considering both the vessel geometry and its appearance in the image. Continuum mechanics laws serve to introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical cases.      

User-Agent Cooperation in Multiagent IVUS Image Segmentation

Automated interpretation of complex images requires elaborate knowledge and model-based image analysis, but often needs interaction with an expert as well. This research describes expert interaction with a multiagent image interpretation system using only a restricted vocabulary of high-level user interactions. The aim is to minimize inter- and intra-observer variability by keeping the total number of interactions as low and simple as possible. The multiagent image interpretation system has elaborate high-level knowledge-based control over low-level image segmentation algorithms. Agents use contextual knowledge to keep the number of interactions low but, when in doubt, present the user with the most likely interpretation of the situation. The user, in turn, can correct, supplement, and/or confirm the results of image-processing agents. This is done at a very high level of abstraction such that no knowledge of the underlying segmentation methods, parameters or agent functioning is needed. High-level interaction thereby replaces more traditional contour correction methods like inserting points and/or (re)drawing contours. This makes it easier for the user to obtain good results, while inter- and intra-observer variability are kept minimal, since the image segmentation itself remains under control of image-processing agents. The system has been applied to intravascular ultrasound (IVUS) images. Experiments show that with an average of 2-3 high-level user interactions per correction, segmentation results substantially improve while the variation is greatly reduced. The achieved level of accuracy and repeatability is equivalent to that of manual drawing by an expert.      

Automatic bifurcation detection in coronary IVUS sequences

In this paper, we present a fully automatic method which identifies every bifurcation in an intravascular ultrasound (IVUS) sequence, the corresponding frames, the angular orientation with respect to the IVUS acquisition, and the extension. This goal is reached using a two-level classification scheme: first, a classifier is applied to a set of textural features extracted from each image of a sequence. A comparison among three state-of-the-art discriminative classifiers (AdaBoost, random forest, and support vector machine) is performed to identify the most suitable method for the branching detection task. Second, the results are improved by exploiting contextual information using a multiscale stacked sequential learning scheme. The results are then successively refined using a-priori information about branching dimensions and geometry. The proposed approach provides a robust tool for the quick review of pullback sequences, facilitating the evaluation of the lesion at bifurcation sites. The proposed method reaches an F-Measure score of 86.35%, while the F-Measure scores for inter- and intraobserver variability are 71.63% and 76.18%, respectively. The obtained results are positive. Especially, considering the branching detection task is very challenging, due to high variability in bifurcation dimensions and appearance.     

Statistical modelling of the wavelet coefficients with different bases and decomposition levels

Various wavelet coefficient statistics are useful to increase the compression efficiency of images. The distribution of the wavelet coefficients within a sub-band affects how the decompression values should be adjusted. A generalised Gaussian distribution model is seen to be applicable from a theoretical point of view, and a convenient way is provided to estimate the parameters from the empirical data. This knowledge is applied to examine the best statistical modelling of the wavelet coefficients for different wavelet bases and decomposition levels.     

Fast Rigid Registration of Vascular Structures in IVUS Sequences

Intravascular ultrasound (IVUS) technology permits visualization of high-resolution images of internal vascular structures. IVUS is a unique image-guiding tool to display longitudinal view of the vessels, and estimate the length and size of vascular structures with the goal of accurate diagnosis. Unfortunately, due to pulsatile contraction and expansion of the heart, the captured images are affected by different motion artifacts that make visual inspection difficult. In this paper, we propose an efficient algorithm that aligns vascular structures and strongly reduces the saw-shaped oscillation, simplifying the inspection of longitudinal cuts; it reduces the motion artifacts caused by the displacement of the catheter in the short-axis plane and the catheter rotation due to vessel tortuosity. The algorithm prototype aligns $hbox{3.16}$ frames/s and clearly outperforms state-of-the-art methods with similar computational cost. The speed of the algorithm is crucial since it allows to inspect the corrected sequence during patient intervention. Moreover, we improved an indirect methodology for IVUS rigid registration algorithm evaluation.      

An automated method for lumen and media-adventitia border detection in a sequence of IVUS frames

In this paper, we present a method for the automated detection of lumen and media-adventitia border in sequential intravascular ultrasound (IVUS) frames. The method is based on the use of deformable models. The energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. A simulated annealing scheme is included to ensure convergence at a global minimum. The method overcomes distortions in the expected image pattern, due to the presence of calcium, employing a specialized structure of the neural network and boundary correction schemas which are based on a priori knowledge about the vessel geometry. The proposed method is evaluated using sequences of IVUS frames from 18 arterial segments, some of them indicating calcified regions. The obtained results demonstrate that our method is statistically accurate, reproducible, and capable to identify the regions of interest in sequences of IVUS frames.     

Electromagnetic theorems for complex anisotropic media

Complex anisotropic media can generally be described by a6 times 6macroscopic constitutive tensorhat{C}. Usinghat{C}properties, a reaction integral formula is derived from which an anisotropic reaction theorem (modified reciprocity theorem) is developed. Reduction of thehat{C}medium into a reciprocal medium is discussed including tensor symmetry attributes and limiting cases. The anisotropic reaction theorem is utilized to derive a zero reaction theorem, and then treated in relation to the moment method. Mutual and self-impedance elements of a network are also derived in terms of reaction integrals, symmetry covered using the anisotropic reaction theorem, and impedance elements related to moment calculations. Use of spectral domain analysis is also covered.     

Well-posed anisotropic diffusion for image denoising

A nonlinear iterative smoothing filter based on a second-order partial differential equation is introduced. It smooths out the image according to an anisotropic diffusion process. The approach is based on a smooth approximation of the total variation (TV) functional which overcomes the non-differentiability of the TV functional at the origin. In particular, the authors perform linear smoothing over smooth areas but selective smoothing over candidate edges. By relating the smoothing parameter to the time step, they arrive at a CFL condition which guarantees the causality of the discrete scheme. This allows the adoption of higher time discretisation steps, while ensuring the absence of artefacts deriving from the non-smooth behaviour of the TV functional at the origin. In particular, it is shown that the proposed approach avoids the typical staircase effects in smooth areas which occur in the standard time-marching TV scheme     

Dispersion relation for general anisotropic media

The dispersion relation is derived for an anisotropic medium with arbitrary tensor permittivity and permeability. Particular cases and applications to layered media are discussed.     

Explicit birefringence analysis for anisotropic fibers

A hyper-perturbation approach is used to find the Taylor expansion formulas for the dispersion curves of arbitrarily indexed optical fibers. These formulas are then used to give analytically the birefringence characteristics of optical fibers with biaxially anisotropic core and cladding. The dependence of the fiber birefringence on the index difference, index anisotropy, and the normalized frequency is explicitly determined. Simple, accurate analytic formulas have been presented for anisotropic fibers with step- and parabolic-index profiles. Numerical results are in good agreement with the literature results     

Forbidden directions for TM waves in anisotropic conducting media

We investigate the wave propagation properties of nonuniform plane waves in an (unbounded homogeneous) anisotropic conducting material. Such waves (for which amplitudes vary across surfaces of constant phase) characterize the refracted field in an imperfect dielectric, like the earth when a uniform electromagnetic plane wave is incident from the air. The results, presented in terms of polar diagrams of the attenuation, slowness, energy velocity, and quality factor predict the existence of “stopbands” beyond a given degree of nonuniformity (i.e., combinations of propagation and attenuation directions where there is no wave propagation). This is a peculiar, effect due to the joint presence of anisotropy and conductivity that may have application in the design of synthetic materials acting as absorbers of electromagnetic radiation     

A State-of-the-Art Review on Segmentation Algorithms in Intravascular Ultrasound (IVUS) Images

Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.