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PubMed2005

SIMPLISMA and ALS applied to two-way nonlinear wavelet compressed ion mobility spectra of chemical warfare agent simulants.

Ion mobility spectrometry is a rapid scanning measurement method for which compression methods that facilitate the handling of large collections of data are beneficial. Peak distortion in reconstructed ion mobility spectra from linear wavelet compression is problematic in that artifact peaks may cause false positive alarms. Peak shifting also may cause false alarms if target peaks shift out of or interfering peaks shift into detection windows. Nonlinear wavelet compression (NLWC) preserves peak shape and can lessen the degree of distortion, shifting, and artifact peaks in the reconstructed spectra. NLWC was applied to achieve high compression and fidelity in the reconstructed spectra. Another benefit is that NLWC improves signal-to-noise ratios and thus the models built from compressed data are improved. By compressing both the drift time order and the spectrum acquisition order, greater compressions maybe achieved. A two-way nonlinear wavelet compression method that incorporates alternating least squares (2W-NLWC-ALS) algorithm was devised by applying ALS to partially reconstructed wavelet coefficients generated from two-way NLWC. The number of components in a data set can be determined automatically using ASIMPLISMA. The smaller ALS models are saved as the final compressed data and can be used to reconstruct the entire data set efficiently without maintaining the compressed wavelet coefficient matrix of the original data set. The 2W-NLWC-ALS algorithm provides greater compression ratios compared to regular wavelet compression and interpretable models. Using this method, large volumes of data can be acquired and easily evaluated through a simple compressed model. A compression ratio of 510 ppm, root-mean-square error (E(RMS)) of 6.3 mV (full-scale signal is usually 1 V or larger), and relative root-mean-square error (RE(RMS)) of 1.62% were achieved for data sets collected by CAM. A compression ratio of 46 ppm, E(RMS) of 9.2 mV, and RE(RMS) of 0.42% were achieved for data sets collected with an ITEMISER instrument. The 2W-NLWC-ALS algorithm is an efficient compression method that provides the benefits of a simple model.

Algorithms↗
PubMed2003

An estimation of the influence of force decrease on the mean power spectral frequency shift of the EMG during repetitive maximum dynamic knee extensions.

Frequency analysis of myoelectric (ME) signals, using the mean power spectral frequency (MNF), has been widely used to characterize peripheral muscle fatigue during isometric contractions assuming constant force. However, during repetitive isokinetic contractions performed with maximum effort, output (force or torque) will decrease markedly during the initial 40-60 contractions, followed by a phase with little or no change. MNF shows a similar pattern. In situations where there exist a significant relationship between MNF and output, part of the decrease in MNF may per se be related to the decrease in force during dynamic contractions. This study estimated force effects on the MNF shifts during repetitive dynamic knee extensions. Twenty healthy volunteers participated in the study and both surface ME signals (from the right vastus lateralis, vastus medialis, and rectus femoris muscles) and the biomechanical signals (force, position, and velocity) of an isokinetic dynamometer were measured. Two tests were performed: (i) 100 repetitive maximum isokinetic contractions of the right knee extensors, and (ii) five gradually increasing static knee extensions before and after (i). The corresponding ME signal time-frequency representations were calculated using the continuous wavelet transform. Compensation of the MNF variables of the repetitive contractions was performed with respect to the individual MNF-force relation based on an average of five gradually increasing contractions. Whether or not compensation was necessary was based on the shape of the MNF-force relationship. A significant compensation of the MNF was found for the repetitive isokinetic contractions. In conclusion, when investigating maximum dynamic contractions, decreases in MNF can be due to mechanisms similar to those found during sustained static contractions (force-independent component of fatigue) and in some subjects due to a direct effect of the change in force (force-dependent component of fatigue). In order to compare MNF shifts during sustained static and repetitive dynamic contractions it is necessary to estimate the force-dependent component of fatigue of dynamic contractions. Our results are preliminary and have to be confirmed in larger experiments using single dynamic contractions when determining the MNF-force relationship of the unfatigued situation.

Adolescent↗
PubMed1997

A wavelet-based multiresolution regularized least squares reconstruction approach for optical tomography.

In this paper, we present a wavelet-based multigrid approach to solve the perturbation equation encountered in optical tomography. With this scheme, the unknown image, the data, as well as the weight matrix are all represented by wavelet expansions, thus yielding a multiresolution representation of the original perturbation equation in the wavelet domain. This transformed equation is then solved using a multigrid scheme, by which an increasing portion of wavelet coefficients of the unknown image are solved in successive approximations. One can also quickly identify regions of interest (ROI's) from a coarse level reconstruction and restrict the reconstruction in the following fine resolutions to those regions. At each resolution level a regularized least squares solution is obtained using the conjugate gradient descent method. This approach has been applied to continuous wave data calculated based on the diffusion approximation of several two-dimensional (2-D) test media. Compared to a previously reported one grid algorithm, the multigrid method requires substantially shorter computation time under the same reconstruction quality criterion.

Algorithms↗
PubMed2006

Semi-regular representation and progressive compression of 3-D dynamic mesh sequences.

We propose an algorithm that represents three-dimensional dynamic objects with a semi-regular mesh sequence and compresses the sequence using the spatiotemporal wavelet transform. Given an irregular mesh sequence, we construct a semi-regular mesh structure for the first frame and then map it to subsequent frames based on the hierarchical motion estimation. The regular structure of the resulting mesh sequence facilitates the application of advanced coding schemes and other signal processing techniques. To encode the mesh sequence compactly, we develop an embedded coding scheme, which supports signal-to-noise ratio and temporal scalability modes. Simulation results demonstrate that the proposed algorithm provides significantly better compression performance than the static mesh coder, which encodes each frame independently.

Algorithms↗
PubMed2004

BCI Competition 2003--Data set III: probabilistic modeling of sensorimotor mu rhythms for classification of imaginary hand movements.

Brain-computer interfaces require effective online processing of electroencephalogram (EEG) measurements, e.g., as a part of feedback systems. We present an algorithm for single-trial online classification of imaginary left and right hand movements, based on time-frequency information derived from filtering EEG wideband raw data with causal Morlet wavelets, which are adapted to individual EEG spectra. Since imaginary hand movements lead to perturbations of the ongoing pericentral mu rhythm, we estimate probabilistic models for amplitude modulation in lower (10 Hz) and upper (20 Hz) frequency bands over the sensorimotor hand cortices both contra- and ipsilaterally to the imagined movements (i.e., at EEG channels C3 and C4). We use an integrative approach to accumulate over time evidence for the subject's unknown motor intention. Disclosure of test data labels after the competition showed this approach to succeed with an error rate as low as 10.7%.

Algorithms↗
PubMedDate not supplied

[The cortical interactions in short time intervals during the search for verbal associations].

Cortical connectivity was studied in tasks of generating the use of words in comparison with reading aloud the same words. These tasks were used earlier in PET and high-density ERP recording studies, which described both the functional anatomy and time course of involvement of cortical areas in word processing. We developed a new method for studying the synchrony of EEG spectral components within the short time intervals compatible with the duration of particular cognitive operations. The wavelet transform of the ERP records and calculation of correlations between the wavelet curves were used to reveal connections between cortical areas. Three stages of intracortical communications developing over the course of task performance were discovered: between the right and left frontal areas (0-200 ms after the stimulus presentation), between the left frontal and left posterior temporo-parietal areas (250-500 ms), and, finally, between the left temporal and right fronto-centro-temporal areas. These findings are in good agreement with the results of the previous PET and ERP studies and supplement them with the circuitry of cortical information transfer. Also, they suggest some differences in information processing during automated reading and performance of more complicated use-generation task.

Adolescent↗
PubMed2004

Removal of major interference sources in aqueous near-infrared spectroscopy techniques.

This work describes a hybrid procedure for eliminating major interference sources in aqueous near-infrared (NIR) spectra, that include aqueous influence, noise, and systemic variations irrelevant to concentration. The scheme consists of two parts: extension of wavelet prism (WPe) and orthogonal signal correction (OSC). First, WPe is employed to remove variations due to aqueous absorbance and noise; then OSC is applied to remove systemic spectral variations irrelevant to concentration. Although water possesses strong absorption bands that overshadow and overlap the absorption bands of analytes, along with noise and systematic interference, successful calibration models can be generated by employing the method proposed here. We show that the elimination of major interference sources from the aqueous NIR spectra results in a substantial improvement in the precision of prediction, and reduces the required number of PLS components in the model. In addition, the strategy proposed here can be applied to various analytical data for quantitative purposes as well.

Fructose↗
PubMed1995

Scalp-recorded oscillatory potentials evoked by transient pattern-reversal visual stimulation in man.

Replicable oscillatory potentials, time-locked to pattern stimuli (9.0 degrees central; counterphase reversal at 2.13 Hz) were dissociated from conventional, broad-band VEPs recorded in healthy volunteers at occipital scalp locations by high-pass digital filtering at 17.0-20.0 Hz. Nine consecutive wavelets were identified with a 56.4 +/- 8.4 msec mean latency of the first replicable wavelet and mean peak-to-peak amplitude varying between 0.9 and 2.0 muV. The first 2 wavelets had significantly shorter latencies than wave N70 of unfiltered VEP, whereas the last 2 wavelets had longer latencies than N145. Latency and amplitude values varied as a function of contrast and spatial frequency of the stimulus, with shorter latencies and larger amplitudes at 60-90% contrast level and tuning of amplitude at 5.0 c/deg. All wavelets were correlated with wave P100 of unfiltered VEP, while a correlation with N70 of VEP was observed only for those wavelets with latencies in the range of wave P100. Two patients with documented brain lesions involving the visual system are described as examples of oscillatory responses occurring irrespective of filter bandpass and instead of the expected conventional VEP when the generation of these is interfered with by brain pathology. A substantial cortical contribution to the origin of the oscillatory response is conceivable. It is suggested that the oscillatory response to pattern-reversal stimulation reflects events in the visual system that are parallel to, and partly independent of, the conventional VEP, with potential application in research or for clinical purposes.

Adolescent↗
PubMed2005

A spatially adaptive nonparametric regression image deblurring.

We propose a novel nonparametric regression metthod for deblurring noisy images. The method is based on the local polynomial approximation (LPA) of the image and the paradigm of intersecting confidence intervals (ICI) that is applied to define the adaptive varying scales (window sizes) of the LPA estimators. The LPA-ICI algorithm is nonlinear and spatially adaptive with respect to smoothness and irregularities of the image corrupted by additive noise. Multiresolution wavelet algorithms produce estimates which are combined from different scale projections. In contrast to them, the proposed ICI algorithm gives a varying scale adaptive estimate defining a single best scale for each pixel. In the new algorithm, the actual filtering is performed in signal domain while frequency domain Fourier transform operations are applied only for calculation of convolutions. The regularized inverse and Wiener inverse filters serve as deblurring operators used jointly with the LPA-design directional kernel filters. Experiments demonstrate the state-of-art performance of the new estimators which visually and quantitatively outperform some of the best existing methods.

Algorithms↗
PubMed2004

Simultaneous storage of medical images in the spatial and frequency domain: a comparative study.

BACKGROUND: Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. METHODS: The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. RESULTS: It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. CONCLUSION: The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient.

Algorithms↗
PubMed2004

Spectral properties of myoelectric signals from different motor units in the leg extensor muscles.

Myoelectric signals measured using intramuscular electromyograms (EMGs) in animals have shown that faster motor units generate higher frequencies in their power spectra. However, evidence to relate myoelectric frequency and motor unit type from the surface electromyograms typically measured from man have remained elusive. The purpose of this study was to determine if spectral properties from surface EMG could be related to the different motor units in the muscles of the leg extensors in man. Reflex experiments (both tendon tap and electrically stimulated) and graded isometric contractions were used to generate muscle contractions with different patterns of motor unit recruitment. EMG was recorded from the vastus lateralis and medialis, rectus femoris, medial and lateral gastrocnemius and soleus muscles. The EMGs were resolved into their intensities in time-frequency space using wavelet techniques. The intensity spectra were calculated for the reflex responses and for different contractile forces. The spectra were compared using principle component analyses and ANCOVA. Electrical stimulation can result in preferentially faster motor units being recruited, and in this study resulted in higher myoelectric frequencies than for the stretch reflex. During ramped contractions the motor units are recruited in an orderly fashion from slow to fast. As the faster motor units were recruited then higher frequency components appeared within the myoelectric intensity spectra. For all muscles tested there were significant correlations between the stage in contraction and the EMG frequency. Both approaches demonstrated higher frequency components in the myoelectric spectra when the faster motor units could be assumed to be active.

Action Potentials↗
PubMed2001

An automatic sequential recognition method for cortical auditory evoked potentials.

The detection of cortical auditory evoked potentials (CAEP), which are part of the electroencephalogram (EEG) in reaction to acoustic stimuli, has important applications such as determining objective audiograms. The detection is usually performed by a human operator, with support from often basic signal processing methods. This paper presents a novel mechanism for the detection of CAEPs, which is fully automatic and stops the measurement when a given confidence is reached. This proposed detector comprises of three stages. First, a feature extraction by a wavelet transform parameterizes the time domain EEG signal by only few transform coefficients. This feature vector is then classified by a neural network which yields a binary vote on every EEG segment. Finally, a sequential statistical test is performed on successive classifications; this stops the measurement if a specified decision confidence has been reached. The adjustment of the detector according to a clinical database is discussed. Thus adjusted, the proposed CAEP detection scheme is applied to a study, and compared with a human operator. The results demonstrate that this method can attain similar results, but outperforms the human expert for stimulation levels close to the hearing threshold.

Adult↗
PubMed2005

Tile-boundary artifact reduction using odd tile size and the low-pass first convention.

It is well known that tile-boundary artifacts occur in wavelet-based lossy image coding. However, until now, their cause has not been understood well. In this paper, we show that boundary artifacts are an inescapable consequence of the usual methods used to choose tile size and the type of symmetric extension employed in a wavelet-based image decomposition system. This paper presents a novel method for reducing these tile-boundary artifacts. The method employs odd tile sizes (2N + 1 samples) rather than the conventional even tile sizes (2N samples). It is shown that, for the same bit rate, an image compressed using an odd tile length low-pass first (OTLPF) convention has significantly less boundary artifacts than an image compressed using even tile sizes. The OTLPF convention can also be incorporated into the JPEG 2000 image compression algorithm using extensions defined in Part 2 of this standard.

Algorithms↗
PubMed2006

Simulating deformations of MR brain images for validation of atlas-based segmentation and registration algorithms.

Simulated deformations and images can act as the gold standard for evaluating various template-based image segmentation and registration algorithms. Traditional deformable simulation methods, such as the use of analytic deformation fields or the displacement of landmarks followed by some form of interpolation, are often unable to construct rich (complex) and/or realistic deformations of anatomical organs. This paper presents new methods aiming to automatically simulate realistic inter- and intra-individual deformations. The paper first describes a statistical approach to capturing inter-individual variability of high-deformation fields from a number of examples (training samples). In this approach, Wavelet-Packet Transform (WPT) of the training deformations and their Jacobians, in conjunction with a Markov random field (MRF) spatial regularization, are used to capture both coarse and fine characteristics of the training deformations in a statistical fashion. Simulated deformations can then be constructed by randomly sampling the resultant statistical distribution in an unconstrained or a landmark-constrained fashion. The paper also describes a model for generating tissue atrophy or growth in order to simulate intra-individual brain deformations. Several sets of simulated deformation fields and respective images are generated, which can be used in the future for systematic and extensive validation studies of automated atlas-based segmentation and deformable registration methods. The code and simulated data are available through our Web site.

Algorithms↗
PubMed2002

Transition from ventricular fibrillation to ventricular tachycardia: a simulation study on the role of Ca(2+)-channel blockers in human ventricular tissue.

We study the effect of blocking the L-type Ca(2+)-channel on fibrillation in simulations in two-dimensional (2D) isotropic sheets of ventricular tissue and in a three-dimensional anisotropic anatomical model of human ventricles, using a previously developed model of human ventricular cells. Ventricular fibrillation (VF) was obtained as a result of spiral wave breakup and consisted of a varying number of chaotically wandering wavelets activating tissue at a frequency of about 6.0 Hz. We show that blocking the Ca(2+)-current by 75% can convert ventricular fibrillation into a periodic regime with a small number of stable spiral waves, ranging from six in 2D sheets of 25 x 25 cm to a single spiral in the anatomical model of human ventricles. The dominant frequency during this process changed to about 10.0 Hz in the 2D simulations, but to only 5.0 Hz in the whole heart simulations where a single spiral wave anchored around an anatomical obstacle. We show that the observed effects were due to a flattening of the electrical restitution curve, which prevented the generation of wave breaks and stabilized the activation patterns.

Calcium↗
PubMed2000

Spatial correlation analysis of atrial activation patterns during sustained atrial fibrillation in conscious goats.

In this study we applied both linear and nonlinear spatial correlation measures to characterize epicardial activation patterns of sustained atrial fibrillation in instrumented conscious goats. It was investigated if nonlinearity was involved in the spatial coupling of atrial regions and to what extent fibrillation was organized in the experimental model of sustained atrial fibrillation (AF) in instrumented goats. Data were collected in five goats during experiments to convert AF by continuous infusion of cibenzoline. Spatial organization during AF was quantified with the linear spatial cross correlation function and the nonlinear spatial cross redundancy which was calculated using the Grassberger-Procaccia correlation integral. Two different types of correlation were evaluated to distinguish simultaneous interaction from non-simultaneous interaction, for instance resulting from propagation of fibrillation waves. The nonlinear association length and the linear correlation length were estimated along the principal axes of iso-correlation contours in two-dimensional correlation maps of the nonlinear spatial redundancy and the linear spatial correlation function, respectively. To quantitatively assess the degree of nonlinearity, the association length was also estimated from the linearized spatial redundancy using multivariate surrogate data. The differences between the nonlinear and linearized association lengths indicated that a nonlinear component in the spatial organization of AF predominantly existed in the right atrium. The degree of organization characterized by association length along the short principal axis was higher in the right atrium (15 +/- 7 mm) than in the left atrium (8 +/- 4 mm). The spatial extension of coherent atrial patches was estimated from a surface of association equal to the area spanned by the principal axes of iso-correlation contours from the redundancy, including the effects from non-simultaneous interaction. Interpreting this area as the spatial domain of a fibrillation wavelet, the results suggest that the mapped region was activated on average by two wavelets in the left atrium and by one wavelet in the right atrium. Therefore, the activation pattern of sustained AF in goats was relatively organized, consistent with type II of AF. It is suggested that the surface of association is a measure of the number of independent wavelets present in the atria during sustained AF, and that larger association lengths result from fewer and larger reentrant circuits.

Animals↗
PubMed2004

Multiresolution moment filters: theory and applications.

We introduce local weighted geometric moments that are computed from an image within a sliding window at multiple scales. When the window function satisfies a two-scale relation, we prove that lower order moments can be computed efficiently at dyadic scales by using a multiresolution wavelet-like algorithm. We show that B-splines are well-suited window functions because, in addition to being refinable, they are positive, symmetric, separable, and very nearly isotropic (Gaussian shape). We present three applications of these multiscale local moments. The first is a feature-extraction method for detecting and characterizing elongated structures in images. The second is a noise-reduction method which can be viewed as a multiscale extension of Savitzky-Golay filtering. The third is a multiscale optical-flow algorithm that uses a local affine model for the motion field, extending the Lucas-Kanade optical-flow method. The results obtained in all cases are promising.

Algorithms↗
PubMed2004

A novel featureless approach to mass detection in digital mammograms based on support vector machines.

In this work, we present a novel approach to mass detection in digital mammograms. The great variability of the appearance of masses is the main obstacle to building a mass detection method. It is indeed demanding to characterize all the varieties of masses with a reduced set of features. Hence, in our approach we have chosen not to extract any feature, for the detection of the region of interest; in contrast, we exploit all the information available on the image. A multiresolution overcomplete wavelet representation is performed, in order to codify the image with redundancy of information. The vectors of the very-large space obtained are then provided to a first support vector machine (SVM) classifier. The detection task is considered here as a two-class pattern recognition problem: crops are classified as suspect or not, by using this SVM classifier. False candidates are eliminated with a second cascaded SVM. To further reduce the number of false positives, an ensemble of experts is applied: the final suspect regions are achieved by using a voting strategy. The sensitivity of the presented system is nearly 80% with a false-positive rate of 1.1 marks per image, estimated on images coming from the USF DDSM database.

Algorithms↗