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PubMed2005

Applications of GRID in clinical neurophysiology and Electrical Impedance Tomography of brain function.

The computational requirements in Neurophysiology are increasing with the development of new analysis methods. The resources the GRID has to offer are ideally suited for this complex processing. A practical implementation of the GRID, Condor, has been assessed using a local cluster of 920 PCs. The reduction in processing time was assessed in spike recognition of the Electroencephalogram (EEG) in epilepsy using wavelets and the computationally demanding task of non-linear image reconstruction with Electrical Impedance Tomography (EIT). Processing times were decreased by 25 and 40 times respectively. This represents a substantial improvement in processing time, but is still sub optimal due to factors such as shared access to resources and lack of checkpoints so that interrupted jobs had to be restarted. Future work will be to use these methods in non-linear EIT image reconstruction of brain function and methods for automated EEG analysis, if possible with further optimized GRID middleware.

Computer Systems↗
PubMedDate not supplied

Optimal time-frequency projections for localized tomography.

An algorithm for recovering a function from essentially localized values of its Radon transform and sparse nonlocal values was outlined in Reference 13. That algorithm utilized the time-frequency properties of wavelets, coupled with the range theorems for the Radon transform, to localize essentially the dependence of the Radon transform. In this paper we utilize alternative time-frequency projections which were introduced by Coifman and Meyer (4). We present evidence that these bases are optimal according to our criterion for localized tomography. These bases require significantly less data than the wavelet bases that were used in Reference 13. Finally, we present numerical results supporting this work.

Algorithms↗
PubMed2003

[Application of complexity sequence in sleep staging based on sleep EEG data].

In this paper an approach of time-window complexity sequence is applied to sleep EEG analysis. This approach can reduce the loss of state information due to the nonstationarity of EEG signal and the unevenness of state space, and can overcome certain limitations of the complexity itself to some extent. It will help to extract the state features of EEG in different sleep stages. In addition, we preprocess EEG by adopting ICA and wavelet transform (WT). The results show that some physiological artifact in EEG can be eliminated effectively by these methods, and the sleep staging based on sleep EEG data will be more exact.

Algorithms↗
PubMed2005

Heart tissue viability monitoring in vivo by using combined fluorescence, thermography and electrical activity measurements.

A prototype system for in vivo monitoring of the heart tissue viability by using combined measurements of fluorescence, thermography and electrical activity has been elaborated for cardiac surgery. The fluorescence imaging of nicotinamide adenine dinucleotide NAD(P)H in the blue light range (lambda=467 nm) by using UV light (lambda=347 nm) excitation was used to detect metabolic disturbances. The method of the principal component analysis was used for the processing of the fluorescence image sequences. Far infrared (lambda=7.5-13 microm) imaging was used to evaluate temperature dynamics of the tissue surface during circulation disturbances. Evaluation of the epicardial electrogram shape by using continuous wavelet transform was used to detect and evaluate ischemia-caused disturbances of the electrical activity of the tissue. The combination of temperature, fluorescence and electrical activity estimates obtained from synchronically registered parameters during the experiments on model systems and experimental animals yielded qualitatively new results for the evaluation of cardiac tissue viability and enabled to achieve a versatile evaluation of the heart tissue viability.

Animals↗
PubMed2003

Bilateral symmetry analysis of breast MRI.

Mammographic interpretation often uses symmetry between left and right breasts to indicate the site of potential tumour masses. This approach has not been applied to breast images obtained from MRI. We present an automatic technique for breast symmetry detection based on feature extraction techniques which does not require any efforts to co-register breast MRI data. The approach applies computer-vision techniques to detect natural biological symmetries in breast MR scans based on three objective measures of similarity: multiresolution non-orthogonal wavelet representation, three-dimensional intensity distributions and co-occurrence matrices. Statistical distributions that are invariant to feature localization are computed for each of the extracted image features. These distributions are later compared against each other to account for perceptual similarity. Studies based on 51 normal MRI scans of randomly selected patients showed that the sensitivity of symmetry detection rate approached 94%. The symmetry analysis procedure presented in this paper can be applied as an aid in detecting breast tissue changes arising from disease.

Breast↗
PubMed2001

Multiscale computing.

Multiscale computing (MSC) involves the computation, manipulation, and analysis of information at different resolution levels. Widespread use of MSC algorithms and the discovery of important relationships between different approaches to implementation were catalyzed, in part, by the recent interest in wavelets. We present two examples that demonstrate how MSC can help scientists understand complex data. The first is from acoustical signal processing and the second is from computer graphics.

Computer Graphics↗
PubMed1999

Visual and automatic investigation of epileptiform spikes in intracranial EEG recordings.

PURPOSE: Performance of automatic spike-detection algorithms and interrater reliability of human EEG reviewers were investigated previously by using scalp EEG recordings. However, it is not known, whether the findings of these studies hold for intracranial recordings. To address this question, we analyzed spike detection in intracranial recordings by two human reviewers and three automatic systems covering major lines in the development of automatic spike-detection systems. METHODS: Intracranial recordings from subdural and intrahippocampal depth electrode contacts in seven patients were analyzed by two reviewers and three spike-detection systems: (a) The rule-based system by Gotman, (b) a two-stage system consisting of a linear predictor and a second rule-based stage, and (c) a system using wavelet coefficients of the intracranial EEG data. RESULTS: Agreement between the two human reviewers with respect to spike identification was <50%. The automatic systems achieved agreements of 24% (Gotman), 26% (wavelet detector), and 32% (two-stage system) with the individual human reviewers. In spite of the small proportion of agreements, the same anatomic regions were identified by human and automatic EEG analysis as generators for the majority of spikes. CONCLUSIONS: The poor agreement between the human EEG reviewers suggests that the definition of spikes and spike-like episodes in intracranial electrodes is far from unequivocal. Nevertheless, localizing information is highly consistent by either visual or automatic spike detection, independent of the algorithm used for automatic spike detection.

Adult↗
PubMed2005

Characteristic wave detection in ECG signal using morphological transform.

BACKGROUND: Detection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG). METHODS: A multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative. RESULTS: We demonstrated through experiments that the Q wave, R peak, S wave, the onsets and offsets of the P wave and T wave could be reliably detected in the multiscale space by the MMD detector. Compared with the results obtained via with wavelet transform-based and adaptive thresholding-based techniques, an overall better performance by the MMD method was observed. CONCLUSION: The developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition.

Algorithms↗
PubMed2004

Computer-assisted bone age assessment: graphical user interface for image processing and comparison.

The current study is part of a project resulting in a computer-assisted analysis of a hand radiograph yielding an assessment of skeletal maturity. The image analysis is based on features selected from six regions of interest. At various stages of skeletal development different image processing problems have to be addressed. At the early stage, feature extraction is based on Lee filtering followed by the random Gibbs fields and mathematical morphology. Once the fusion starts, wavelet decomposition methods are implemented. The user interface displays the closest neighbors to each image under consideration. Results show the sensitivity of different regions to both stages of development and certain feature sensitivity within each region. At the early stage of development, the distal features are more reliable indicators, whereas at the stage of epiphyseal fusion, a larger dynamic range of middle features makes them more sensitive. In the current study, a graphical user interface has been designed and implemented for testing the image processing routines and comparing the results of quantitative image analysis with the visual interpretation of extracted regions of interest. The user interface may also serve as a teaching tool. At the later stage of the project it will be used as a classification tool.

Adolescent↗
PubMed2006

Factorial coding of natural images: how effective are linear models in removing higher-order dependencies?

The performance of unsupervised learning models for natural images is evaluated quantitatively by means of information theory. We estimate the gain in statistical independence (the multi-information reduction) achieved with independent component analysis (ICA), principal component analysis (PCA), zero-phase whitening, and predictive coding. Predictive coding is translated into the transform coding framework, where it can be characterized by the constraint of a triangular filter matrix. A randomly sampled whitening basis and the Haar wavelet are included in the comparison as well. The comparison of all these methods is carried out for different patch sizes, ranging from 2x2 to 16x16 pixels. In spite of large differences in the shape of the basis functions, we find only small differences in the multi-information between all decorrelation transforms (5% or less) for all patch sizes. Among the second-order methods, PCA is optimal for small patch sizes and predictive coding performs best for large patch sizes. The extra gain achieved with ICA is always less than 2%. In conclusion, the edge filters found with ICA lead to only a surprisingly small improvement in terms of its actual objective.

Algorithms↗
PubMed1992

Time normalization in voice analysis.

The harmonics-to-noise ratio (HNR) has been widely accepted for quantifying the irregular or noise component of voice. HNR, however, is usually inflated by cycle-to-cycle variations of fundamental frequency period because zero padding is used for time normalization of the wavelet. In this study, a new method was developed for analyzing waveform perturbations of voice. In this method, noise components of voice were calculated from the discrepancies between wavelets after they had been optimally aligned in time. The optimal time normalization of wavelets was accomplished using procedures of dynamic time warping (DTW). This method was evaluated using both synthetic and natural voices, and significant reductions in noise were obtained. The harmonics-to-noise ratio obtained using DTW for time normalization was also shown to be independent of fundamental frequency perturbations.

Acoustics↗
PubMed2004

RRM analysis of protoporphyrinogen oxidase.

Enzymes are crucial in accelerating metabolic reactions in living organisms. Protoporphyrinogen oxidase (PpOI) is an enzyme that catalyses the production of protoporphyrin IX (PpIX), a protein used in a cancer treatment known as photodynamic therapy (PDT). In this study, a structure-function analysis of PpOI was carried out using the Resonant Recognition Model (RRM), a physico-mathematical approach for analysis of proteins interactions. This method is based on the finding that the distribution of delocalised electron energies along the protein plays a crucial role in determining the protein's biological activity. Two digital signal processing (DSP) methods were used: Fourier Transform (FT) and Continuous Wavelet Transform (CWT). Here we have determined the characteristic frequencies and the "hot spot" amino acids, and predicted the location of proteins' active site(s). Several proteins that potentially belong to the PpOI functional group were also analysed to distinguish their viability in this role.

Algorithms↗
PubMed2003

[Preliminary experimental analysis of myocardial function evaluation based on integrated backscatter].

OBJECTIVE: To demonstrate the feasibility of the method to detect myocardial function based on integrated backscatter. METHOD: Using the experimental system developed by our research group, the RF signal of B-mode image was sampled and digitized. Wavelet transform method was adopted for cyclic variation of integrated backscatter (CVIB) calculation. The CVIB image of the region of interest (ROI) was obtained. RESULT: The CVIB results of 11 cases with myocardial infarction were provided by data and image. Results of 23 normal people including 8 middle-aged and 15 young were also given for comparison. CONCLUSION: The method based on integrated backscatter can differentiate ischemic myocardium from normal people and it has potential to be used in clinic.

Adolescent↗
PubMed2003

Bowel sounds analysis: a novel noninvasive method for diagnosis of small-volume ascites.

Ascites is more difficult to detect when only a small quantity is present. The aim of this pilot study was to determine the optimal bowel sound characteristics in order to distinguish no ascites from small-volume ascites by advanced processing of bowel sound wave patterns. This analysis results in the definition of the normal range of bowel sound patterns, thus providing a novel, simple, and noninvasive way of determining on abnormal pattern, which may reflect presence of small volume ascites. Cirrhotic patients with radiologically proven small-volume ascites and a control group were subjected to bowel sound recordings. The latter were analyzed using a denoising wavelet transform-based filter and a higher-order crossings-based technique in a blinded fashion for linearly distinguishing the two classes. Scatter plots of third-order zero crossings reflect distinct changes seen in the denoised bowel sound pattern between patients and controls due to altered transmission path, providing a distinct separation of all cirrhotic patients with small ascites from controls (P < 0.0001). We conclude that the proposed bowel sounds analysis appears to provide new information regarding the changes of the bowel sound patterns due to the presence of small-volume ascites, potentially contributing towards a safe, effective, noninvasive, and easily implemented alternative method for the diagnosis of small volume ascites at the bedside.

Adult↗
PubMed1997

Focal hepatic lesions: effect of three-dimensional wavelet compression on detection at CT.

PURPOSE: To evaluate the effect of three-dimensional, wavelet-based compression on the detection of focal hepatic lesions at computed tomography (CT). MATERIALS AND METHODS: CT images obtained in 69 patients with focal hepatic lesions were studied (35 consecutive cases and 34 cases selected to be difficult on the basis of lesion size or contrast). Image data were compressed by means of a three-dimensional, wavelet-based algorIthm at ratios of 10:1, 15:1, and 20:1. Normal and abnormal sections (on original and compressed images) were reviewed by using an interactive workstation. Four readers rated the presence or absence of a lesion with a five-point scale. RESULTS: At receiver operating characteristic analysis, no statistically significant difference was detected for all cases considered together. Differences approached but did not reach statistical significance for the diagnostic performance of one reader with compressed images (15:1, P = .054; 20:1, P = .051). For the subset of difficult cases, a significant difference was observed with 20:1 compressed images for one reader (P = .026). Diagnostic performance of readers was less certain in normal than in abnormal cases with both original and compressed images (difference was significant for 15:1 [P = .035] and 20:1 [P < .0001] compressed images). CONCLUSION: Three-dimensional wavelet compression is satisfactory at ratios of at least 10:1. Additional studies with a larger sample would help confirm findings with higher ratios.

Cysts↗
PubMed1997

Landscape Structure and Historical Processes Along Diked European Valleys: A Case Study of the Arc/Isere Confluence (Savoie, France)

/ The valleys of European piedmonts constitute changing narrow corridors within which water, matter, nutrients, energy, and species flow. The dispersion patterns of these flows have been significantly disturbed since the end of the 18th century. Thus, western European valleys have been changed into complex mosaics by implementation of socioeconomical programs. In order to define future actions allowing the preservation of this "ecocomplex" (Blandin and Lamotte 1988), it is necessary to gather precise information of the landscape dynamics. Hence, the study of the European river valleys must be based upon two major steps: (1)the analysis of the present landscape with suitable remote sensing techniques, allowing us to map the complex mosaic of narrow corridors; and (2) the analysis of temporal landscape development patterns since the first engineering works that have transformed the braided channel system. In this paper, the efficiency of the addition of two techniques is highlighted: (1) the "wavelet merging method" from multispectral and panchromatic SPOT images for the floodplain land-cover mapping, and (2) the historical reconstruction techniques from old maps and archive documents in order to analyze the cumulative impacts of engineering works on landscape diversity. To illustrate the method, a particularly complex case study is chosen: the Arc/Isere confluence (downstream from Albertville, Savoie, France). Remote sensing, field survey, and historical reconstruction allowed us to distinguish two types of spatial units: (1) the "functional sets" characterized by independent state factors (edaphic, hydrological, and topographic) and supporting a limited number of vegetation types (spontaneous or cultivated), and (2) the functional unit (= ecotope), which corresponds to a unique combination of vegetation type/functional set.KEY WORDS: Landscape ecology; Floodplains; Vegetation; Land use; Remote sensing; Historical reconstruction; Mapping; Merging methods; Human impacts; Alps; Isere river; France

Journal Article↗