A Shift-Invariant Neural Network for the Lung Field Segmentation in Chest Radiography

We have developed a computerized method using a neural network for the segmentation of lung fields in chest radiography. The lung is the primary region of interest in routine chest radiography diagnosis. Since computer is expected to perform disease pattern search automatically, it is important to design appropriate algorithms to delineate the region of interest. A reliable segmentation method is essential to facilitate subsequent searches for image patterns associated with lung diseases. In this study, we employed a shift invariant neural network coupled with error back-propagation training method to extract the lung fields. A set of computer algorithms were also developed for smoothing the initially detected edges of lung fields. Our preliminary results indicated that 86% of the segmented lung fields globally matched the original chest radiographs. We also found that the method facilitates the development of computer algorithms in the field of computer-aided diagnosis.     

Fractal modeling and segmentation for the enhancement of microcalcifications in digital mammograms

The objective of this research is to model the mammographic parenchymal and ductal patterns and enhance the microcalcifications using a deterministic fractal approach. According to the theory of deterministic fractal geometry, images can be modeled by deterministic fractal objects which are attractors of sets of two-dimensional (2-D) affine transformations. The iterated functions systems and the collage theorem are the mathematical foundations of fractal image modeling. Here, a methodology based on fractal image modeling is developed to analyze and model breast background structures. The authors show that general mammographic parenchymal and ductal patterns can be well modeled by a set of parameters of affine transformations. Therefore, microcalcifications can be enhanced by taking the difference between the original image and the modeled image. The authors' results are compared with those of the partial wavelet reconstruction and morphological operation approaches. The results demonstrate that the fractal modeling method is an effective way to enhance microcalcifications. It may also be able to improve the detection and classification of microcalcifications in a computer-aided diagnosis system.     

Design of multicast delivery for providing VCR functionality ininteractive video-on-demand systems

Multicast delivery is one of the solutions to reduce the cost in a large video-on-demand (VoD) system. However, multicast transmission makes much more difficult the implementation of interactive functions for individual users and introduces start-up delays for the users, which contradicts the idea of on-demand services. In this paper, we first try to explore and evaluate the performance of different multicast VoD systems. A new scheme called single-rate multicast double-rate unicast (SRMDRU) is then developed to minimize the system resources for supporting full VCR functionality in a multicast VoD system. This scheme also allows multicast systems to support true VoD services so customers can be served as soon as the system receives the requests. Computer simulations show that the multicast systems using the SRMDRU scheme perform much better than other multicast systems in terms of system blocking probabilities     

Optical coherence tomography system with no high-precision scanning stage and stage controller

Optical coherence tomography (OCT) is a novel technique for noninvasive imaging based on the use of a low-coherence interferometer. Conventionally, obtaining high-resolution images requires the use of high-precision sample and scanning stages and a stage controller for simultaneous measurement of the refractive index and the thickness of an optical sample. However, in this study a novel optical-fiber-type OCT system is developed that does not need both a high-precision scanning stage and a stage controller. Additionally, two signal demodulation processes are described. Compared with that of conventional OCT systems, the current configuration eliminates the high-precision scanning stage and stage controller and is therefore cheaper and less complex. Also, this new technique could be applied to conventional OCTs in biotissue scanning.     

High-performance fluidic adaptive lenses

High-performance fluidic lenses with an adjustable focal length spanning a very wide range (30 mm to infinite) are demonstrated. We show that the focal length, F-number, and numerical aperture can be dynamically controlled by changing the shape of the fluidic adaptive lens without moving the lens position mechanically. The shortest focal length demonstrated is less than 30 mm for a 20-mm lens aperture. The fluidic adaptive lens has a nearly perfect spherical profile and shows a resolution better than 40 line pairs/mm in a plano-convex structure and 57 line pairs/mm in a biconvex structure.     

A study of space-tapered arrays

Previous works on nonuniformly spaced arrays are first critically reviewed, then an exhaustive study of a few small arrays is made. The results reveal that among a large number of possible element arrangements, only very few yield reasonably low sidelobe level. Although the majority of these few arrays are characterized by space-tapering, an overwhelming number of space-tapered arrays do not have low sidelobe level. Some statistical studies are made in order to relate the sidelobe level to the element arrangement. Finally, in the light of rather complete information of these arrays, a comparative study is made on some designs which are proposed by a few authors. The results show that none of them are truly optimum.     

Multiple scattering of EM waves by spheres part II--Numerical and experimental results

In [8], both low- and high-frequency solutions to the two-sphere problem were presented in a form suitable for efficient computer solution, Here, numerical results are presented using a method which has enabled the first appearance of reliable results for the scattered field from two spheres of radii larger than one wavelength and as large as ten or more. Radar cross sections (RCS) are computed for numerous configurations of two spheres of various materials. Results for scattering by three collinear spheres are also given. An experimental program was undertaken and is briefly described. Whenever possible, these results are compared with the theory. In all cases the agreement is excellent. Depolarization due to multiple scattering is also investigated, revealing some interesting effects and practical applications to scattering range calibration.     

Efficient analysis for infinite microstrip dipole arrays

A moment method analysis of infinite microstrip dipole arrays which uses an efficient technique to evaluate the generalised impedance matrix is described. A particularly simple formulation is obtained through the use of the periodic Green function. Results for the reflection coefficient magnitude against scan angle are given for a typical array.     

Bayes analysis for fault location in distributed systems

The authors propose a simple and practical probabilistic model, using multiple incomplete test concepts, for fault location in distributed systems using a Bayes analysis procedure. Since it is easier to compare test results among processing units, their model is comparison-based. This approach is realistic and complete in the sense that it does not assume conditions such as permanently faulty units, complete tests, and perfect or nonmalicious environments. It can handle, without any overhead, fault-free systems so that the test procedure can be used to monitor a functioning system. Given a system S with a specific test graph, the corresponding conditional distribution between the comparison test results (syndrome) and the fault patterns of S can be generated. To avoid the complex global Bayes estimation process, the authors develop a simple bitwise Bayes algorithm for fault location of S, which locates system failures with linear complexity, making it suitable for hard real-time systems. Hence, their approach is appealing both from the practical and theoretical points of view     

A two-phase algorithm and performance bounds for the star-starconcentrator location problem

The introduction of concentrators in a centralized telecommunication network provides a cost-effective way to connect the network. The star-star (SS) network model is considered, and the star-star concentrator location problem (SSCLP) is then examined. The SSCLP is NP-complete and can be formulated as a 0-1 integer programming problem. A two-phase algorithm is developed to solve the SSCLP. In the first phase, dualizing the side constraints produces a Lagrangian problem that is easy to solve and has an optimal value that is a lower bound (for minimization problems) on the optimal value of the original SSCLP. Heuristics then are applied to produce an upper bound (feasible solution) to the SSCLP. In the second phase, a branch-and-bound method is used to refine the solution space to obtain a tighter lower bound. First, an enumeration heuristic is applied to improve the best feasible solution obtained from the first phase. Then, a procedure for deriving bounding problems is presented and various branching strategies are discussed. Computational examples with up to 100 terminals and 30 potential concentrators are considered. All the network designs obtained are shown to be within 2% of optimal