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At least 1,063 records · Page 59Linked to original sources
PubMed2005

Evaluating the effect of a wavelet enhancement method in characterization of simulated lesions embedded in dense breast parenchyma.

Presence of dense parenchyma in mammographic images masks lesions resulting in either missed detections or mischaracterizations, thus decreasing mammographic sensitivity and specificity. The aim of this study is evaluating the effect of a wavelet enhancement method on dense parenchyma for a lesion contour characterization task, using simulated lesions. The method is recently introduced, based on a two-stage process, locally adaptive denoising by soft-thresholding and enhancement by linear stretching. Sixty simulated low-contrast lesions of known image characteristics were generated and embedded in dense breast areas of normal mammographic images selected from the DDSM database. Evaluation was carried out by an observer performance comparative study between the processed and initial images. The task for four radiologists was to classify each simulated lesion with respect to contour sharpness/unsharpness. ROC analysis was performed. Combining radiologists' responses, values of the area under ROC curve (Az) were 0.93 (95% CI 0.89, 0.96) and 0.81 (CI 0.75, 0.86) for processed and initial images, respectively. This difference in Az values was statistically significant (Student's t-test, P<0.05), indicating the effectiveness of the enhancement method. The specific wavelet enhancement method should be tested for lesion contour characterization tasks in softcopy-based mammographic display environment using naturally occurring pathological lesions and normal cases.

Breast↗
PubMed2004

Analysis on multiresolution mosaic images.

Image mosaicing is the act of combining two or more images and is used in many applications in computer vision, image processing, and computer graphics. It aims to combine images such that no obstructive boundaries exist around overlapped regions and to create a mosaic image that exhibits as little distortion as possible from the original images. In the proposed technique, the to-be-combined images are first projected into wavelet subspaces. The images projected into the same wavelet space are then blended. Our blending function is derived from an energy minimization model which balances the smoothness around the overlapped region and the fidelity of the blended image to the original images. Experiment results and subjective comparison with other methods are given.

Algorithms↗
PubMed2004

A simple wavelet-based test for evoked responses.

Statistically valid detection of evoked responses from magnetoencephalographic (MEG) sensors is complicated by temporal autocorrelation. By decorrelating time series and transforming them toward normality, the discrete wavelet transform (DWT) allows the analyst to test for an association between stimulus and sensor time series with appropriate degrees of freedom. Eswaran et al. (Neurosci. Lett. 2002a;331:128-32) used a 151-channel fetal MEG system to obtain serial recordings from 10 pregnant subjects. There were 3-8 recordings per subject. In each recording session, the fetus was stimulated by 500Hz and 1KHz tones with a relative frequency of 80-20%, respectively. In this new analysis of the same data, the fetal MEG signals were compared to two different stimulus waveforms: the frequent tone and the Novel stimulus, defined as a change in pitch. WaveDetect was developed to determine whether there was a significant association between the stimuli and the MEG traces. This test is performed by taking the DWT of each series and then computing the Spearman correlation between the wavelet coefficients for an appropriate scale. A significant response (i.e., correlated stimulus-sensor pair) was detected from each patient. This result suggests that the combination of serial recordings and WaveDetect may ensure reliable detection of auditory evoked responses.

Acoustic Stimulation↗
PubMed2004

M-CGH: analysing microarray-based CGH experiments.

BACKGROUND: Microarray-based comparative genomic hybridisation (array CGH) is a technique by which variation in relative copy numbers between two genomes can be analysed by competitive hybridisation to DNA microarrays. This technology has most commonly been used to detect chromosomal amplifications and deletions in cancer. Dedicated tools are needed to analyse the results of such experiments, which include appropriate visualisation, and to take into consideration the physical relation in the genome between the probes on the array. RESULTS: M-CGH is a MATLAB toolbox with a graphical user interface designed specifically for the analysis of array CGH experiments, with multiple approaches to ratio normalization. Specifically, the distributions of three classes of DNA copy numbers (gains, normal and losses) can be estimated using a maximum likelihood method. Amplicon boundaries are computed by either the fuzzy K-nearest neighbour method or a wavelet approach. The program also allows linking each genomic clone with the corresponding genomic information in the Ensembl database http://www.ensembl.org. CONCLUSIONS: M-CGH, which encompasses the basic tools needed for analysing array CGH experiments, is freely available for academics http://www.uio.no/~junbaiw/mcgh, and does not require any other MATLAB toolbox.

Chromosomes, Artificial, Bacterial↗
PubMed2006

Application of adaptive neuro-fuzzy inference system for epileptic seizure detection using wavelet feature extraction.

Intelligent computing tools such as artificial neural network (ANN) and fuzzy logic approaches are demonstrated to be competent when applied individually to a variety of problems. Recently, there has been a growing interest in combining both these approaches, and as a result, neuro-fuzzy computing techniques have been evolved. In this study, a new approach based on an adaptive neuro-fuzzy inference system (ANFIS) was presented for epileptic seizure detection. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Some conclusions concerning the impacts of features on the detection of epileptic seizures were obtained through analysis of the ANFIS. The results are highly promising, and a comparative analysis suggests that the proposed modeling approach outperforms ANN model in terms of training performances and classification accuracies. The results confirmed that the proposed ANFIS model has some potential in epileptic seizure detection. The ANFIS model achieved accuracy rates which were higher than that of the stand-alone neural network model.

Electroencephalography↗
PubMed1999

Spectrogram enhancement algorithm: a soft thresholding-based approach.

Enhancing the spectrogram by denoising the Doppler ultrasound signal is a preliminary step, and important for further processing. Because the spectrogram may be based on the short-time fast Fourier transform (FFT) of the Doppler ultrasound signal, whose power spectrum density is time-varying, traditional denoising algorithms that simply optimize the mean-squared error are not appropriate, and they may exhibit considerable undesirable, noise-induced frequency components. A soft thresholding-based denoising algorithm is put forward in this paper, that achieves almost the minimax mean square error (MSE) over a wide range of function classes having norms measuring smoothness (i.e., it meets both the requirement of smoothness and MSE). Due to the importance of noise level estimation while applying this method, several robust L-estimators are compared and the median absolute deviation (MAD) method is chosen to estimate the noise level. The simulation study shows better performance of the later algorithm under various quantification measures, compared to the FFT thresholding and the hard thresholding wavelet method, and the results of clinical data also confirm it.

Algorithms↗
PubMed2006

Quality-aware images.

We propose the concept of quality-aware image, in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical quality-aware image encoding, decoding and quality analysis system, which employs: 1) a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and 2) a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.

Algorithms↗
PubMed1991

Temporal and spatial properties of suppressive rod-cone interaction.

Recordings were obtained from rods and horizontal cells of Xenopus, using an eyecup preparation. The enhancement of cone signals produced by rod backgrounds was measured using flickering red spots of varying intensity and diameter, and the experiments were repeated with cone stimuli consisting of alteration of wavelengths of 660 and 605 nm, adjusted for equal effects on rods or cones ("silent substitution"). Rods responded to red flicker with discrete wavelets up to 5 Hz. The characteristics of suppressive rod-cone interaction (SRCI) depend on the precise stimulus parameters. In particular, the reported low-pass attenuation of SRCI is absent with silent substitution. An analysis of the responses to backgrounds in horizontal cells, and the effects of the red light flashes in rods, led to the conclusion that the characteristics of SRCI are determined partially by the fact that "cone" stimuli excite rods and vice versa. This result simplifies the mechanism of SRCI and permits a comparison between the studies of SRCI using electroretinograms and horizontal cells.

Animals↗
PubMed2002

Applications of nonequilibrium response spectroscopy to the study of channel gating. Experimental design and optimization.

A novel experimental technique known as non-equilibrium response spectroscopy (NRS) based on ion channel responses to rapidly fluctuating voltage waveforms was recently described (Millonas & Hanck, 1998a). It was demonstrated that such responses can be affected by subtle details of the kinetics that are otherwise invisible when conventional stepped pulses are applied. As a consequence, the kinetics can be probed in a much more sensitive way by supplementing conventional techniques with measurements of the responses to more complex voltage waveforms. In this paper we provide an analysis of the problem of the design and optimization of such waveforms. We introduce some methods for determination of the parametric uncertainty of a class of kinetic models for a particular data set. The parametric uncertainty allows for a characterization of the amount of kinetic information acquired through a set of experiments which can in turn be used to design new experiments that increase this information. We revisit the application of dichotomous noise (Millonas & Hanck, 1998a, b), and further consider applications of a more general class of continuous wavelet -based waveforms. A controlled illustration of these methods is provided by making use of a simplified "toy" model for the potassium channel kinetics.

Animals↗
PubMed2005

Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery.

It is well-known that speckle is a multiplicative noise that degrades the visual evaluation in ultrasound imaging. The recent advancements in ultrasound instrumentation and portable ultrasound devices necessitate the need of more robust despeckling techniques for enhanced ultrasound medical imaging for both routine clinical practice and teleconsultation. The objective of this work was to carry out a comparative evaluation of despeckle filtering based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts in the assessment of 440 (220 asymptomatic and 220 symptomatic) ultrasound images of the carotid artery bifurcation. In this paper a total of 10 despeckle filters were evaluated based on local statistics, median filtering, pixel homogeneity, geometric filtering, homomorphic filtering, anisotropic diffusion, nonlinear coherence diffusion, and wavelet filtering. The results of this study suggest that the first order statistics filter lsmv, gave the best performance, followed by the geometric filter gf4d, and the homogeneous mask area filter lsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by the two experts. More specifically, filters lsmv or gf4d can be used for despeckling asymptomatic images in which the expert is interested mainly in the plaque composition and texture analysis; and filters lsmv, gf4d, or lsminsc can be used for the despeckling of symptomatic images in which the expert is interested in identifying the degree of stenosis and the plaque borders. The proper selection of a despeckle filter is very important in the enhancement of ultrasonic imaging of the carotid artery. Further work is needed to evaluate at a larger scale and in clinical practice the performance of the proposed despeckle filters in the automated segmentation, texture analysis, and classification of carotid ultrasound imaging.

Algorithms↗
PubMed2005

Quantitative ultrasound can assess the regeneration process of tissue-engineered cartilage using a complex between adherent bone marrow cells and a three-dimensional scaffold.

Articular cartilage (hyaline cartilage) defects resulting from traumatic injury or degenerative joint disease do not repair themselves spontaneously. Therefore, such defects may require novel regenerative strategies to restore biologically and biomechanically functional tissue. Recently, tissue engineering using a complex of cells and scaffold has emerged as a new approach for repairing cartilage defects and restoring cartilage function. With the advent of this new technology, accurate methods for evaluating articular cartilage have become important. In particular, in vivo evaluation is essential for determining the best treatment. However, without a biopsy, which causes damage, articular cartilage cannot be accurately evaluated in a clinical context. We have developed a novel system for evaluating articular cartilage, in which the acoustic properties of the cartilage are measured by introducing an ultrasonic probe during arthroscopy of the knee joint. The purpose of the current study was to determine the efficacy of this ultrasound system for evaluating tissue-engineered cartilage in an experimental model involving implantation of a cell/scaffold complex into rabbit knee joint defects. Ultrasonic echoes from the articular cartilage were converted into a wavelet map by wavelet transformation. On the wavelet map, the percentage maximum magnitude (the maximum magnitude of the measurement area of the operated knee divided by that of the intact cartilage of the opposite, nonoperated knee; %MM) was used as a quantitative index of cartilage regeneration. Using this index, the tissue-engineered cartilage was examined to elucidate the relations between ultrasonic analysis and biochemical and histological analyses. The %MM increased over the time course of the implant and all the hyaline-like cartilage samples from the histological findings had a high %MM. Correlations were observed between the %MM and the semiquantitative histologic grading scale scores from the histological findings. In the biochemical findings, the chondroitin sulfate content increased over the time course of the implant, whereas the hydroxyproline content remained constant. The chondroitin sulfate content showed a similarity to the results of the %MM values. Ultrasonic measurements were found to predict the regeneration process of the tissue-engineered cartilage as a minimally invasive method. Therefore, ultrasonic evaluation using a wavelet map can support the evaluation of tissue-engineered cartilage using cell/scaffold complexes.

Animals↗
PubMed2002

Life span of ventricular fibrillation frequencies.

The nature and organization of electrical activity during ventricular fibrillation (VF) are important and controversial subjects dominated by 2 competing theories: the wavebreak and the dominant mother rotor hypothesis. To investigate spatiotemporal characteristics of ventricular fibrillation (VF), transmembrane potentials (V(m)) were recorded from multiple sites of perfused rabbit hearts using a voltage-sensitive dye and a photodiode array or a CCD camera, and the time-frequency characteristics of V(m) were analyzed by short-time fast Fourier transform (FFT) or generalized time-frequency representation with a cone-shaped kernel. The analysis was applied to all pixels to track VF frequencies in time and space. VF consisted of blobs, which are groups of contiguous pixels with a common frequency and an ill-defined shape. At any time t, several VF frequency blobs coexisted in the field of view, and the number of coexisting blobs was on average 5.9+/-2.1 (n=8 hearts) as they appeared and disappeared discontinuously with time and were not fixed in space. The life span of frequency blobs from birth to either annihilation or breakup to another frequency had a half-life of 0.39+/-0.13 second (n=4 hearts). The Ca2+ channel blocker nifedipine increased the stability of VF frequencies and reduced the number of frequency blobs progressing to a single frequency. In conclusion, VF consists of dynamically changing frequency blobs, which have a short life span and can be modified by pharmacological interventions, suggesting that VF is maintained by dynamically changing multiple wavelets.

Action Potentials↗
PubMed2006

Nonstatistical effects in the dissociation of ethyl radical: Finding order in chaos.

How does one identify order in complex dynamical systems? A Born-Oppenheimer molecular dynamics simulation of the dissociation of ethyl radical, C(2)H(5), produces an ensemble of classical trajectories which are decomposed in the time-frequency domain using wavelets. A time-dependent scalar metric, the normalized instantaneous orbital complexity, is constructed and shown to correlate not only to the more conventional Lyapunov exponents but also to the dissociation time for an individual trajectory. The analysis of the ensemble of trajectories confirms that the long-lived trajectories are associated with a low degree of ergodicity. While the analysis of molecular dissociation dynamics is the narrow focus of the present work, the method is more general for discovery and identification of ordered regimes within large sets of chaotic data.

Journal Article↗
PubMed2000

Electrocardiographic waveform analysis for predicting the success of defibrillation.

A new electrocardiographic predictor of the likelihood that an electrical shock would restore a perfusing rhythm is described. The intent was to develop a prognosticator that would be displayed during precordial compression. We anticipated that such a predictor would allow more selective timing of electrical shocks and reduce electrical injury to the myocardium caused by repetitive shocks. In a porcine model of cardiac arrest because of ventricular fibrillation, electrocardiographic recordings of ventricular fibrillation wavelets were analyzed and transformed into an amplitude spectrum area (AMSA). An AMSA value of 21 mV x Hz predicted restoration of perfusing rhythm with a positive predictive value equivalent to that of coronary perfusion pressure. More important, the negative predictive value that a shock would fail to reestablish spontaneous circulation was 96%. AMSA, therefore, has the potential for guiding optimal timing of defibrillation.

Animals↗
PubMed1995

Wavelet variations on the Shannon sampling theorem.

The Shannon sampling theorem asserts that a continuous square-integrable function on the real line which has a compactly supported Fourier transform is uniquely determined by its restriction to a uniform lattice of points whose density is determined by the support of the Fourier transform. This result can be extended to the wavelet representation of functions in two ways. First, under the same type of conditions as for the Shannon theorem, the scaling coefficients of a wavelet expansion will determine uniquely the given square-integrable function. Secondly, for a more general function, there is a unique extension from a given set of scaling coefficients to a full wavelet expansion which minimizes the local obstructions to translation invariance in a variational sense.

Fourier Analysis↗
PubMedDate not supplied

Multiscale analysis for singularity detection in pulmonary microvascular pressure transients.

This paper addresses the problem of pulmonary microvascular pressure estimation. The "why" and "how" of multiscale approaches in the context of singularity detection are discussed. From a linear viewpoint, the scalogram technique and the multiresolution representation for singularity detection are discussed in general under the wavelet framework. A technique as well as a criterion for the segmentation and the extraction of the region of interest or the optimal scale is proposed. A new nonlinear multiscale technique for singularity detection is also proposed. This multiscale representation is based on rank order filters and on mathematical morphology operators in particular. A scaling parameter is introduced for such operators as in the linear continuous wavelet transform leading to what we call morpholograms. Experiments performed on pulmonary artery pressure transients illustrate how the proposed technique can give a synopsis of the signal characteristics through the scales.

Algorithms↗
PubMed2000

Thalamic and cortical high-frequency (600 Hz) somatosensory-evoked potential (SEP) components are modulated by slight arousal changes in awake subjects.

Human somatosensory-evoked potentials (SEP) recorded at the scalp after conventional electrical median-nerve stimulation contain a low-amplitude (<500 nV), high-frequency (approximately 600 Hz) burst of repetitive wavelets, which are superimposed onto the primary cortical response N20. Previous electroencephalographic (EEG) studies have shown: (1) that these wavelets are generated near the hand area of the primary somatosensory cortex and in deep fibers of thalamocortical afferences; and (2) that only the 600-Hz burst, but not the N20 is decreased during sleep. Since the thalamus is involved in regulating both, selective attention and arousal, the present study aimed at characterizing the effects of focused attention and slight arousal changes on the 600-Hz oscillations. A dipole-source analysis of 64-channel SEP recordings after electric right-median-nerve stimulation allowed the comparison of brainstem, thalamic, and two cortical (one tangential, one radial) source activities in ten awake human subjects under two slightly different arousal states (eyes open vs. eyes closed), each tested for three conditions of focused attention (directed towards rare acoustic and right- or left-hand somatosensory target stimuli). While the N20 was not modified at all, the source strength of the high-frequency wavelet burst was significantly increased for eyes opened versus eyes closed, at the thalamic source site as well as for the tangentially oriented cortical source. In contrast, there were no significant differences between conditions with different attentional targets. This evidence for modulatory effects of increased arousal (eyes open) on both thalamic and cortically generated high-frequency SEP activity fits the hypothesis that the 600-Hz SEP burst at least partially represents an arousal-dependent signal generated at the thalamic level and transmitted to the primary somatosensory cortex.

Adult↗