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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： J. McNames T. Thong M. Aboy Biomedical Signal Processing Laboratory Electrical and Computer Engineering Portland State University Portland OR USA Biomedical Engineering OGI School of Science and Engineering Oregon Health and Sciences University Portland OR USA

Biomedical signals are frequently corrupted with artifact that occurs rarely, but is impulsive and large amplitude when it does occur. Because the artifact spans a broad frequency range that overlaps with the signal spectrum, linear filters cannot remove it. Because it is large in amplitude, it dominates characterizations of the signals based on second-order statistics such as correlation and spectral analysis. In this study we assess the ability of impulse rejection filters to remove the effect of synthetic PVCs in interbeat interval series from patients with a normal sinus rhythm. The simulation results demonstrate that the PVCs severely corrupt the estimated heart rate power spectral density (PSD), impulse rejection filters are effective at removing this effect, and the filter performance is robust to the choice of user-specified parameters.

关键词： Spectral analysis Nonlinear filters Heart rate variability Biomedical engineering Rhythm Autocorrelation Mathematical model Signal processing Biomedical signal processing Statistical analysis

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Adaptive lossless video compression using an integer wavelet transform

Adaptive lossless video compression using an integer wavelet...

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IEEE International Conference on Image processing

作者： S.-G. Park E.J. Delp H. Yu Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Corporate Research Group Thomson Inc. Indianapolis IN USA

In this paper, we describe an adaptive lossless compression algorithm for color video sequences utilizing backward adaptive temporal prediction and an integer wavelet transform. We exploit two redundancies in color video sequences, specifically spatial and temporal redundancies. We show that an adaptive scheme exploiting the two redundancies has better compression performance than lossless compression of individual image frames. The result of the proposed scheme is compared to current video compression algorithms.

关键词： Video compression Wavelet transforms Image coding Redundancy Video sequences Image edge detection Decorrelation Frequency Image processing Laboratories

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Full-field mammogram analysis based on the identification of normal regions

Full-field mammogram analysis based on the identification of...

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IEEE International Symposium on Biomedical Imaging

作者： Y. Sun C. Babbs E.J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Basic Medical Sciences School of Veterinary Medicine Purdue University West Lafayette IN USA

We present a new method for full-field mammogram analysis. A mammogram is analyzed region by region and is classified as normal or abnormal. We present methods for extracting features that can be used to distinguish normal and abnormal regions of a mammogram. We describe our classifier technique that uses a unique reclassification method to boost the classification performance. We have tested this technique on a set of ground-truth full-field mammograms.

关键词： Feature extraction Breast cancer Cancer detection Mammography Biomedical imaging Image analysis Delta-sigma modulation Spatial databases Image databases Optical scattering

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Progressive compression of 3D dynamic mesh sequences

Progressive compression of 3D dynamic mesh sequences

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IEEE International Conference on Image processing

作者： Jeong-Hyu Yang Chang-Su Kim Sang-Uk Lee Signal Processing Laboratory School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea Department of Information Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

ISBN: (纸本)0780385543

An algorithm to compress 3D mesh sequences for dynamic objects is proposed in this work. Given an irregular mesh sequence, we construct a semi-regular mesh structure for the first frame and then map it to the subsequent frames bused on the hierarchical motion estimation. The regular structure of the resulting mesh sequence enables us to employ the zero-tree coding scheme to compress the motion compensation residuals efficiently. Simulation results demonstrate that the proposed algorithm provides significantly better compression performance than the static coder that encodes each frame independently.

关键词： Motion estimation Video coding Laser modes Image motion analysis Shape Geometry Tracking Topology Mesh generation

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Activation detection in multi-subject studies of fMRI using GLRT

Activation detection in multi-subject studies of fMRI using ...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S.M. Shams G.A. Hossein-Zadeh H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics University of Tehran School of Cognitive Sciences Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics and Medical Image Analysis Laboratory Henry Ford Health System University of Tehran School of Cognitive Sciences Iran

A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the flexibility of method in detecting different shapes of hemodynamic response. The proposed multivariate method can be applied to group studies where the conventional cross-correlation method cannot be used due to its univariate property. This method is applied to both experimental and simulated fMRI data and the results are compared to those of general linear model (GLM). We show that the proposed method detects more significant activated regions in analyzing experimental data and more true voxels in simulated data

关键词： Testing Hemodynamics Brain modeling Process control Intelligent control Physics computing Mathematics Time series analysis Magnetic resonance imaging Data analysis

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Normal mammogram classification based on a support vector machine utilizing crossed distribution features

Normal mammogram classification based on a support vector ma...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： W. Chiracharit Y. Sun P. Kumhom K. Chamnongthai C. Babbs E.J. Delp Electronics and Telecom. Engineering Department King Mongkut's University of Technology Thonburi Bangkok Thailand Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University IN USA Department of Basic Medical Sciences School of Veterinary Medicine Purdue University IN USA

Automatic classification of normal mammograms, which constitute a majority of screening mammograms, is a new approach to computer-aided diagnosis of breast cancer. This approach may be limited, however, by non-separable "crossed" distributions of features that are extracted from digitized mammograms. This work presents a method of mapping such non-separable input features into a new set of separable features that can be utilized, together with ordinary "uncrossed" features, by a support vector machine (SVM) classifier. The results of the proposed scheme show improved performance with 80% sensitivity and 95% specificity.

关键词： Support vector machines Support vector machine classification Training data Data mining Biomedical engineering Biomedical imaging computer aided diagnosis Breast cancer Aging Mammography

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Heart rate variability analysis of effect of nicotine using periodograms

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

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： T. Thong I.O. Yung D.P. Zajdel R.M. Ellingson J. McNames M. Aboy B.S. Oken Department of Biomedical Engineering Oregon Health and Sciences University Beaverton OR USA School of Medicine Oregon Health and Sciences University Portland OR USA Department of Neurology Oregon Health and Sciences University Portland OR USA Biomedical Signal Processing Laboratory Electrical and Computer Engineering Portland State University Portland OR USA

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 nicotine-naive 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： Heart rate Heart rate variability Sampling methods Interpolation Biomedical engineering Autonomic nervous system Neurotransmitters Spectral analysis Mesh generation Fourier transforms

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Performance Analysis of a Myrinet-Based Cluster

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Cluster Computing 2003年第4期6卷 299-313页

作者： Gunawan, Teddy Surya Cai, Wentong Parallel and Distributed Processing Laboratory School of Computer Engineering Nanyang Technological University Singapore

In recent years, there has been a growing interest in the cluster system as an accepted form of supercomputing, due to its high performance at an affordable cost. This paper attempts to elaborate performance analysis of Myrinet-based cluster. The communication performance and effect of background load on parallel applications were analyzed. For point-to-point communication, it was found that an extension to the Hockney's model was required to estimate the performance. The proposed model suggested that there should be two ranges to be used for the performance metrics to cope with the cache effect. Moreover, based on the extension of the point-to-point communication model, the Xu and Hwang's model for collective communication performance was also extended. Results showed that our models can make better estimation of the communication performance than the previous models. Finally, the interference of other user processes to the cluster system is evaluated by using synthetic background load generation programs.

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Automatic word spacing using syllable n-grame and word statistics [n-grame read n-gram]

Automatic word spacing using syllable n-grame and word stati...

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IEEE International Conference on Natural Language processing and Knowledge engineering (NLP-KE)

作者： Mi-Young Kang Sung-Ja Choi Hee-Keun Heo Sung-Shin Lim Hyuk-Chul Kwon Korean Language Processing Laboratory School of Electrical & Computer Engineering Pusan National University Busan South Korea

ISBN: (纸本)0780379020

In this study, we have proposed an automatic word spacing system for the Korean language, which uses syllable n-gram and word statistics extracted from a large amount of processed corpora. The optimal spacing points of a sentence are decided mainly by using the Viterbi algorithm. As the statistical studies performance is sensitive to the training corpus and shows data sparseness problem, we have tried to enlarge the training corpora, used parameters found by examining test data and proposed an adjusting method of the 'longest match strategy' based on the viable prefix. These increase the system's accuracy. Our corpora, covering various language registers, were made up of 33643884 words. The pilot test was conducted with test data derived from different sources. 94.24% precision in word-unit correction were obtained on average for spacing test data.

关键词： Statistics Testing Natural languages Viterbi algorithm Information retrieval Frequency estimation Error correction Statistical analysis Natural language processing Speech synthesis

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A real-time multisensory image segmentation algorithm with an application to visual and X-ray inspection

A real-time multisensory image segmentation algorithm with a...

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Lecture Notes in computer Science

作者： Ding, Yuhua Vachtsevanos, George J. Yezzi Jr., Anthony J. Daley, Wayne Heck-Ferri, Bonnie S. School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332 United States Food Processing Technology Division Electro-Optics Environment and Materials Laboratory Georgia Tech Research Institute Atlanta GA 30332-0837 United States

A new multisensory image segmentation algorithm is presented. In this algorithm, the images from different sensors are segmented in a sequential manner using curve evolution methods. There are no fusion rules involved and no controlling weights to adjust. It is effective in eliminating errors in single modality segmentation, and is fast enough for segmentation in real-time applications. The algorithm is applied to real-time fan bone detection in deboned poultry meat based on visual and x-ray images. Results show that the fusion-based inspection algorithm is efficient, accurate, and robust to registration errors. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Image segmentation

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