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A new application of texture unit coding to mass classification for mammograms

A new application of texture unit coding to mass classificat...

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2004 International Conference on Image Processing, ICIP 2004

作者： Chen, Yuan Chang, Chein-I. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250

Texture is one of important features of masses in mammograms. A recent texture unit-based texture spectrum approach, referred to as Texture Unit Coding (TUC) has shown promise in texture classification. This paper presents a new application of the TUC to mass classification in mammograms. The TUC generates a texture spectrum for a texture image that can be used to describe the characteristics of masses. It also develops an information divergence (ID)-based discrimination criterion to measure the discrepancy between two texture spectra, a concept yet to explore in texture analysis. The TUC along with ID are further applied to mass classification in mammograms where the MiniMammographic Database provided by the Mammographie Image Analysis Society (MIAS) is used for experiments. ©2004 IEEE.

关键词： Mammography

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Robust extraction of the optic nerve head in optical coherence tomography

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International Workshop on computer Vision Approaches to Medical Image Analysis, CVAMIA 2004 and International Workshop on Mathematical Methods in Biomedical Image Analysis, MMBIA 2004 held in conjunction with 8th European Conference on computer Vision, ECCV 2004

作者： Herzog, Artemas Boyer, Kim L. Roberts, Cynthia The Ohio State University Signal Analysis and Machine Perception Laboratory Department of Electrical and Computer Engineering United States Department of Ophthalmology United States

ISBN: (纸本)3540226753

Glaucoma is a leading cause of blindness. While glaucoma is a treatable and controllable disease, there is still no cure available. Early diagnosis is important in order to prevent severe vision loss. Many current diagnostic techniques are subjective and variable. This provides motivation for a more objective and repeatable method. Optical Coherence Tomography (OCT) is a relatively new imaging technique that is proving useful in diagnosing, monitoring, and studying glaucoma. OCT, like ultrasound, suffers from signal dependent noise which can make accurate, automatic segmentation of images difficult. In this article we propose a method to automatically extract the optic nerve and retinal boundaries from axial OCT scans through the optic nerve head. We also propose a method to automatically segment the curve to extract the nerve head profile that is important in diagnosing and monitoring glaucoma. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Optical tomography

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Multifractal spectra of lightning strike maps using entropy and wavelet analyses

Multifractal spectra of lightning strike maps using entropy ...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： A. Faghfouri W. Kinsner D. Swatek Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada Manitoba Hydro Winnipeg MAN Canada

This paper describes a multifractal analysis of physical lightning strike maps obtained for Manitoba through the Canadian Lightning Detection Network. Cloud-to-ground discharges or lightning strikes are physical phenomena which may have adverse effects on power transmission and delivery. Predicting the geographical and temporal distribution of lightning strike maps through modelling can help power system designers to improve the protection of existing and new power systems and transmission lines. In order to compare the model to physical data, their characterization is required. Since lightning strike maps are highly nonlinear, nonstationary and stochastic, ordinary analyses and measures are insufficient to characterize these phenomena. Since self affinity of the lightning strike maps is the indication of multifractality, complexity measures such as the Renyi fractal dimension spectrum (RS) and Mandelbrot singularity spectrum (MS) are appropriate for such fractal analysis. In this paper, we investigate the multifractality of lightning strike maps in Manitoba through the RS and MS. Both methods generate similar results and show that the maps are multifractal. Comparing the range of results with a similar phenomenon, diffusion limited aggregates (DLA), supports the accuracy of calculations as well.

关键词： Fractals Lightning Entropy Wavelet analysis Power system modeling Power system protection Power system analysis computing Power system measurements Transmission line measurements Power transmission

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Classification of transients in power systems using multifractal analysis

Classification of transients in power systems using multifra...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： L.S. Safavian W. Kinsner H. Turanli Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada Manitoba Hydro Winnipeg MAN Canada

This paper presents a study of a method for feature extraction and classification of voltage disturbances based on multifractal analysis of a voltage waveform with a transient. In this work, the variance fractal dimension trajectory is used to characterize a transient and to extract its features. The features extracted are a trajectory of fractal dimensions that are calculated over a number of overlapping windows along the transient signal. Based on their extracted features, classification of the transients is carried out using a statistical maximum likelihood classifier, which discriminates between three classes of voltage disturbances such as faults, breaker operations and capacitor switchings. The performance of the classifier is considered with both raw signals and also signals contaminated by noise.

关键词： Power system transients Transient analysis Power system analysis computing Fractals Feature extraction Voltage signal analysis Capacitors Power system faults Frequency

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Multifractal characterization for classification of network traffic

Multifractal characterization for classification of network ...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： R.L. Barry W. Kinsner Telecommunications Research Laboratories Winnipeg MAN Canada Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

In this paper, a novel multifractal approach to the classification of self-affine network traffic is presented. The fundamental advantages of using multifractal measures include their boundedness and a very high compression ratio of a signature of the traffic, thereby leading to faster implementations, and the ability to add new traffic classes without redesigning the traffic classifier. The variance fractal dimension trajectory is used to provide a multifractal "signature" for each type of traffic over its duration, and the modelling of its statistical histograms provides further compression and generalization. Principal component analysis is used to reduce the dimensionality of the data, and the K-means clustering algorithm is used to assign classes to the data. A probabilistic neural network (PNN) with a locally optimal spread parameter is trained with these signatures, and a plot of the PNN percentage correct classification accuracy as the number of assigned classes increases reveals that there are most likely three classes in the traffic recording. Finally, an optimized PNN is trained with 50 % of the multifractal signatures sampled at regular intervals from the trajectory, and achieves a representative classification accuracy of 94.8 % when classifying previously unobserved self-affine network traffic.

关键词： Fractals Telecommunication traffic Communication system traffic control Neural networks Clustering algorithms Statistical analysis Local area networks Wide area networks Data compression Laboratories

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Multifractal characterization and fuzzy classification of lightning strike maps

Multifractal characterization and fuzzy classification of li...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： A. Faghfouri W. Kinsner D. Swatek Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada Insulation Engineering and Testing Department Manitoba Hydro Winnipeg MAN Canada

This paper investigates optimal classification of lightning strike maps (LSMs), using regular and fuzzy K-means classifiers. It also describes a novel approach for measurements of the physical LSMs. Lightning strikes are physical phenomena, which have adverse effects on power transmission. Modelling and classification of the LSMs can lead to prediction of their time-space behaviour, and enhance the protection of the existing and new power systems and transmission lines. Prediction requires the classification of the simulated results and physical data, and comparing them together using characterization. Since the LSMs are highly nonlinear, nonstationary, and stochastic, ordinary models and analyses are incapable of simulating and characterizing these phenomena. Since self-affinity of such maps is an indication of multifractality, percolation models and complexity measures such as the Renyi fractal dimension spectrum (RS) and Mandelbrot singularity spectrum (MS) are utilized. The data of the LSMs have been obtained through the Canadian Lightning Detection Network (CLDN) for Manitoba in the year 2002. The data have been characterized by both the RS and MS. Features have been extracted using the RS. Classification employed the regular and fuzzy K-means methods. For each classification method, 50 tests have been utilized, and classification performance for 2 to 15 classes has been investigated through Davis-Bouldin criterion. The fuzzy K-means classifier identified 6 optimal classes with a confidence level of 0.78, while the regular K-means algorithm could not distinguish the classes.

关键词： Fractals Lightning Power system modeling Power system simulation Predictive models Power system protection Transmission line measurements Power transmission Power system analysis computing Power system measurements

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How to effectively utilize information to design hyperspectral target detection and classification algorithms

How to effectively utilize information to design hyperspectr...

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2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

作者： Chang, Chein-I. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States

ISBN: (纸本)0780383508

Hyperspectral imagery offers a means of uncovering enormous spectral information that can be used for various applications in data exploitation. How effectively such information is used affects the way image analysis algorithms are designed. In this paper, we take up this issue and focus on algorithms designed and developed for target detection and classification in hyperspectral imagery. In order to effectively characterize the information available before and after the data are processed, the a priori information and a posteriori information are used in accordance with how the information is obtained. A piece of information is referred to as a priori information if it is provided by known knowledge before data are processed. On the other hand, a piece of information is referred to as a posteriori information if it is unknown a priori, but can be obtained directly from the data in an unsupervised fashion during the course of data processing. Since a priori information is known beforehand, it can be further decomposed into two types of information, desired and undesired a priori information. The desired a priori information is the knowledge that will assist, improve and enhance data analysis, whereas the undesired a priori information is the knowledge that hinders, interferes or destructs analysis during data processing. This paper investigates how these three types of information play their roles in design and development of several hyperspectral target detection and classification algorithms. Experiments are also conducted to validate their utility. © 2004 IEEE.

关键词： Classification (of information)

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Discrimination and identification for subpixel targets in hyperspectral imagery

Discrimination and identification for subpixel targets in hy...

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2004 International Conference on Image Processing, ICIP 2004

作者： Chang, Chein-I. Liu, Weimin Chang, Chein-Chi Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 Department of Civil and Environmental Engineering University of Maryland Baltimore County Baltimore MD 21250

Spectral measures have been used in material identification and discrimination. They are effective if the spectral signatures are calibrated and not contaminated. However, it may not be true in many real applications, specifically, for mixed pixels and subpixel targets. This paper investigates the issue of discrimination and identification for subpixel targets and further develops sample spectral covariance/correlation matrix-based hyperspectral measures to account for spectral variability within subpixel targets. Two types of measures are of interest and studied, Mahalanobis distance-based hyperspectral measures and matched filter-based hyperspectral measures. In order to substantiate the proposed measures, a real data-based comparative analysis is conducted and compared to two spectral similarity measures, spectral angle mapper (SAM) and spectral information divergence (SID) for performance evaluation. The experiments show that both Mahalanobis distance-based hyperspectral measures and matched filter-based hyperspectral measures work very effectively and outperformed the SAM and the SID in discrimination and identification for subpixel targets. ©2004 IEEE.

关键词： Imaging techniques

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Spectral Management of Entangled Two-Photon States

Spectral Management of Entangled Two-Photon States

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Frontiers in Optics, FiO-2004

作者： Carrasco, S. Torres, J.P. Torner, L. Sergienko, A.V. Saleh, B.E.A. Teich, M.C. ICFO-Institut de Ciencies Fotoniques Department of Signal Theory and Communications Universitat Politecnica de Catalunya Barcelona08034 Spain Quantum Imaging Laboratory Department of Electrical & Computer Engineering Department of Physics Boston University BostonMA02215 United States

We put forward a new approach for manipulating the spectral profile of entangled photon pairs. Such spectral properties are mediated by the geometry of non-collinear spontaneous parametric down conversion and by selec... 详细信息

ISBN: (纸本)1557527792

关键词： Quantum entanglement

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Heart rate variability analysis of effect of nicotine using lomb- welch periodograms

Heart rate variability analysis of effect of nicotine using ...

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Conference Proceedings - 26th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2004

作者： Thong, Tran Yung, Iris O. Zajdel, Daniel P. Ellingson, Roger M. McNames, James Aboy, Mateo Oken, Barry S. Department of Biomedical Engineering Oregon Health and Science University Beaverton OR School of Medicine Oregon Health and Science University Portland OR Department of Neurology Oregon Health and Science University Portland OR Biomed. Signal Processing Laboratory Electrical and Computer Engineering Portland State University Portland OR

Heart rate variability (HRV) is frequently used to measure autonomic nervous system (ANS) activity. However, little is known about the mechanism underlying pharmacologically induced changes in HRV. Previous research has shown that nicotine exposure stimulates the ANS, mediating a wide spectrum of physiological and behavioral effects, including altered respiratory sinus arrhythmia and enhanced arousal and attention. Using Lomb-Welch periodograms, the effect of nicotine on the ANS in 14 nicotinenaive human subjects are studied. Results showed an increase in the low frequency (LF) to high frequency (HF) ratio with little change in mean heart rate. Results suggest that nicotine affects both sympathetic and parasympathetic reactivities and that the LF/HF best characterizes early ANS activated nicotine changes in HRV. The Lomb-Welch periodogram of the HRV is also compared to the conventional interpolated Welch periodogram. The attenuation of the high frequency components due to interpolation of the non-uniform R-R intervals is found to be a function of the power of the high frequency components, increasing with increasing power. Thus analyses using Welch periodograms that make use of the high frequency components may yield erroneous results.

关键词： Biomedical engineering

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