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

作者： A. Saflekos D. Tzovaras S. Malassiotis M.G. Strintzis Information Processing Laboratory Department of Electrical and Computer Engineering University of Thessaloniki Thessaloniki Greece

A novel 3D motion compensation algorithm for the coding of 3D medical image sequences is presented. The temporal correlation existing between successive in time 3D data sets is exploited using a 3D cube matching algorithm (CMA). In order to cope with more complex motions and to adapt compensation to the high-activity regions, a 3D warping based motion estimation technique is introduced. The methods are evaluated experimentally for the coding of an 3D image sequence of a beating heart.

关键词： Image coding Biomedical imaging Motion estimation Image sequences Propagation losses Magnetic resonance imaging Motion compensation Heart Image storage Space technology

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A new time series classification approach

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SIGNAL processing 1996年第2期54卷 191-199页

作者： Plataniotis, KN Androutsos, D Venetsanopoulos, AN Lainiotis, DG Department of Electrical and Computer Engineering Digital Signal & Image Processing Laboratory University of Toronto 10 King's College Rd. Toronto Ontario M5S 3G4 Canada Intelligent Systems Technology 3207 S. Hwy. A1A Melbourne Beach FL-32951 USA

A new, robust and computationally attractive approach to the problem of time series classification is discussed in this paper. Both the Bayesian as well as a new adaptive classification scheme for source selection are... 详细信息

关键词： time series classification neural networks logistic function

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Disparity field and depth map coding for multiview image sequence compression

Disparity field and depth map coding for multiview image seq...

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IEEE International Conference on Image processing

作者： D. Tzovaras N. Grammalidis M.G. Strintzis Electrical and Computer Engineering Department Information Processing Laboratory Aristotle University of Thessaloniki Thessaloniki Greece

Methods are proposed for coding of the depth map and disparity fields for stereo or multiview image communication applications. Block-based and wireframe modeling techniques are examined for the coding of isolated depth map information and 2-D and 3-D motion compensation techniques for the coding of depth map sequences are evaluated.

关键词： Interpolation Image coding Cameras Optical receivers Optical transmitters Motion compensation Image communication Layout Image sequences Geometrical optics

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Hierarchical prioritized predictive image coding

Hierarchical prioritized predictive image coding

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IEEE International Conference on Image processing

作者： S.N. Efstratiadis M.G. Strintzis Information Processing Laboratory Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece

Hierarchical prioritized predictive image coding methods are presented for progressive image transmission. The three main coder stages are hierarchical transform, prioritized coefficient coding and adaptive multiple distribution entropy coding (AMDEC). Following a hierarchical subband decomposition of the original image, the quantized coefficients are scalar quantized and then coded using novel hierarchical partition priority coding (HPPC) and predictive HPPC (PHPPC) algorithms. Given a suitable partitioning of their absolute range, the quantized detail coefficients are ordered based on both their decomposition level and partition and, then, are DPCM coded along with the corresponding address map. The use of space filling scanning further reduces the coding cost. Finally, AMDEC is applied to the HPPC/PHPPC output. Experimental results demonstrate the performance of the proposed compression methods.

关键词： Image coding Image communication Entropy coding Partitioning algorithms Prediction algorithms Filling Costs Image storage Predictive coding Image quality

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Synthesis of stressed speech from isolated neutral speech using HMM-based models

Synthesis of stressed speech from isolated neutral speech us...

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International Conference on Spoken Language, ICSLP

作者： S.E. Bou-Ghazale J.H.L. Hansen Robust Speech Processing Laboratory Department of Electrical and Computer Engineering Duke University Durham NC USA

A novel approach is proposed for modeling speech parameter variations between neutral and stressed conditions and employed in a technique for stressed speech synthesis. The proposed method consists of modeling the variations in pitch contour, voiced speech duration and average spectral structure using hidden Markov models (HMMs). While HMMs have traditionally been used for recognition applications, here they are used to statistically model the characteristics needed for generating pitch contour and spectral slope patterns to modify the speaking style of isolated neutral words. An algorithm is developed based on an analysis-synthesis speech model, and HMM pitch and spectral stress characteristics for stress perturbation. Informal listener evaluations of the stress-modified speech confirm the HMM's ability to capture the parameter variations under stressed conditions. The proposed HMM models are both speaker- and word-independent, but unique to each speaking style. While the modeling scheme is applicable to a variety of stress and emotional speaking styles, the evaluations presented in this study focus on angry, Lombard-effect and loud-spoken speech.

关键词： Speech synthesis Hidden Markov models Stress Speech analysis Speech processing Robustness Speech coding Autocorrelation Laboratories Character recognition

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3D segmentation and labeling using self-organizing Kohonen network for volumetric measurements on brain CT imaging to quantify TBI recovery

3D segmentation and labeling using self-organizing Kohonen n...

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

作者： M.N. Ahmed A.A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

In this paper, we present a new system to segment and label CT brain slices using a self-organizing Kohonen network. Our aim is to extract reliable and robust measures from CT images of Traumatic Brain Injury (TBI) patients that can accurately describe the morphological changes in the brain as recovery progresses. Segmentation is performed by assigning a feature pattern to each voxel, consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is input to Kohonen network for an unsupervised classification of the voxels into regions.

关键词： Labeling Volume measurement Image segmentation Computed tomography Layout Electric variables measurement engineering in Medicine and Biology Society Brain injuries Data mining Filters

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Neural network classification of spatio-temporal EEG readiness potentials

Neural network classification of spatio-temporal EEG readine...

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Southern Biomedical engineering Conference

作者： A.B. Barreto A.M. Taberner L.M. Vicente Digital Signal Processing Laboratory Electrical & Computer Engineering Department Florida International University Miami FL USA

The detection of spatio-temporal scalp EEG patterns associated with voluntary motion preparation towards the development of a brain-computer interface (BCI) is explored. The rationale for the use of a spatio-temporal approach to this detection problem is explained. The need for a temporal or dynamic classifier is confirmed by demonstration of the lack of robustness in static neural network classifiers with respect to time alignment of the patterns under analysis. The results from dynamic classifiers, such as the Time Delay Neural Network (TDNN) and the Gamma Neural Network are presented in terms of their Receiver Operating Characteristic (ROC) Curves.

关键词： Neural networks Electroencephalography Rhythm Biological neural networks Motion detection Eyes Digital signal processing Brain computer interfaces computer interfaces Scalp

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Classification of spatio-temporal EEG readiness potentials towards the development of a brain-computer interface

Classification of spatio-temporal EEG readiness potentials t...

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IEEE Southeastcon

作者： A.B. Barreto A.M. Taberner L.M. Vicente Digital Signal Processing Laboratory Electrical & Computer Engineering Department Florida International University Miami FL USA

The existence of characteristic changes in the EEG of a subject preparing for the execution of a voluntary movement is reviewed. Some of those changes, i.e., the "readiness potentials" (RPs), are suggested as a possible link between the internal processes associated with different forms of motion preparation and a digital signal processing system designed to classify the different intended movements. Such a system can potentially be used to provide input to a specialized graphic user interface, constituting a brain-computer interface (BCI). Our current work on neural-network classification of RPs is summarized and the results are presented.

关键词： Electroencephalography Brain computer interfaces Digital signal processing Physiology Aggregates Rhythm Laboratories Process design Signal design Graphics

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Implications of a segmentation-based motion compensation scheme for the case of a block transform encoder

Implications of a segmentation-based motion compensation sch...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： M. Sipitca Department of Electrical and Computer Engineering Digital Signal Processing Laboratory Georgia Institute of Technology Atlanta GA USA

Sipitca and Madisetti (see VCIP '96, Orlando, Florida, 1996) have proposed the use of analog position sensors for a more accurate motion compensation on videoconferencing sequences. We investigate the results of including such a motion compensation scheme in a transform based encoder. The more successful motion compensation makes the resulting displaced frame difference (DFD) less correlated. In fact, the autocorrelation function goes practically to zero for a lag larger than 4-5 pels. Therefore, the 4/spl times/4 DCT can be used instead of the 8/spl times/8 DCT. This helps in dealing better with the relatively small regions where the DFD takes on larger values-on the border regions and in the new information regions. Finally, a block swapping algorithm and an appropriate error measure are introduced.

关键词： Motion compensation computer aided software engineering Head Design for disassembly Discrete cosine transforms Image segmentation Microphones Image edge detection Paper technology Digital signal processing

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ScaleNet-multiscale neural network architecture for time series prediction

ScaleNet-multiscale neural network architecture for time ser...

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IEEE Convention of the electrical and ELectronic Engineers in Israel

作者： A.B. Geva A.K. Altman Electrical and Computer Engineering Department Ben-Gurion University of the Negev Beersheba Israel Electrical Engineering Department The Physiological Signal Processing Laboratory Technion-Israel Institute of Technology Israel

The effectiveness ofthe multiscale neural network (NN) architecture for time series prediction of nonlinear dynamic systems has been investigated. The prediction task is simplified by decomposing the time series into separate scales of wavelets, and predicting each scale by a separate multilayer perceptron NN. The different scales of the wavelet transform provides an interpretation of the series structures and information about the history of the series, using fewer coefficients than other methods. In the next stage, the predictions of all the scales are combined, applying another perceptron NN, in order to predict the original time series. Each network is trained by the backpropagation algorithm using the Levenberg-Marquadt method. The weights and biases are initialized by new clustering methods, which improved the prediction results compared to random initialization. Three sets of data were analyzed: the sunspots benchmark, fluctuations in a far-infrared laser and a numerically generated series (set A and D in the Santa Fe competition). Taking the ultimate goal to be the accuracy of the prediction, we find that our suggested architecture outperforms traditional nonlinear statistical approaches.

关键词： Neural networks Multilayer perceptrons Wavelet transforms History Backpropagation algorithms Clustering methods Data analysis Fluctuations Iron Accuracy

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