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PubMed2002

Local energy as a measure of back symmetry in scoliosis.

The Cobb angle has been the most commonly used method in measuring the severity of scoliosis and its progression. However, in recent years a number of researchers have chosen to monitor scoliosis by examining the severity of the surface deformity resulting from the scoliosis. Each of these approaches has been limited by errors introduced in manual location of landmarks. Scoliosis results in an asymmetry of the back. It would be very desirable to have a computer-based method of measuring this asymmetry. This paper investigates the use of wavelets and the concept of local energy to measure asymmetry associated with scoliosis. The local energy model uses wavelet theory to obtain information about shading and boundaries of objects in an image. Edges and sharp discontinuities are areas of high local energy in an image. Features such as scapular prominence, shoulder edges, waist creases and other anomalies that contribute to the scoliotic back asymmetry have high local energy. A preliminary study was completed to determine if this approach was applicable to measurement of back asymmetry. Two-dimensional local energy images were created from photographs of the backs of patients with scoliosis. The local energy was integrated across each image and a left-to right line of symmetry was calculated. This line of symmetry was then correlated with the scoliotic score developed by our group. This technique shows promise of providing an automatic method of measuring scoliosis progression.

Back↗
PubMed2005

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.

Algorithms↗
PubMed2006

Light field compression using disparity-compensated lifting and shape adaptation.

We propose disparity-compensated lifting for wavelet compression of light fields. With this approach, we obtain the benefits of wavelet coding, such as scalability in all dimensions, as well as superior compression performance. Additionally, the proposed approach solves the irreversibility limitations of previous light field wavelet coding approaches, using the lifting structure. Our scheme incorporates disparity compensation into the lifting structure for the transform across the views in the light field data set. Another transform is performed to exploit the coherence among neighboring pixels, followed by a modified SPIHT coder and rate-distortion optimized bitstream assembly. A view-sequencing algorithm is developed to organize the views for encoding. For light fields of an object, we propose to use shape adaptation to improve the compression efficiency and visual quality of the images. The necessary shape information is efficiently coded based on prediction from the existing geometry model. Experimental results show that the proposed scheme exhibits superior compression performance over existing light field compression techniques.

Algorithms↗
PubMedDate not supplied

Wavelet-based progressive compression scheme for triangle meshes: wavemesh.

This paper proposes a new lossy to lossless progressive compression scheme for triangular meshes, based on a wavelet multiresolution theory for irregular 3D meshes. Although remeshing techniques obtain better compression ratios for geometric compression, this approach can be very effective when one wants to keep the connectivity and geometry of the processed mesh completely unchanged. The simplification is based on the solving of an inverse problem. Optimization of both the connectivity and geometry of the processed mesh improves the approximation quality and the compression ratio of the scheme at each resolution level. We show why this algorithm provides an efficient means of compression for both connectivity and geometry of 3D meshes and it is illustrated by experimental results on various sets of reference meshes, where our algorithm performs better than previously published approaches for both lossless and progressive compression.

Algorithms↗
PubMed2005

A parallel decision tree-based method for user authentication based on keystroke patterns.

We propose a Monte Carlo approach to attain sufficient training data, a splitting method to improve effectiveness, and a system composed of parallel decision trees (DTs) to authenticate users based on keystroke patterns. For each user, approximately 19 times as much simulated data was generated to complement the 387 vectors of raw data. The training set, including raw and simulated data, is split into four subsets. For each subset, wavelet transforms are performed to obtain a total of eight training subsets for each user. Eight DTs are thus trained using the eight subsets. A parallel DT is constructed for each user, which contains all eight DTs with a criterion for its output that it authenticates the user if at least three DTs do so; otherwise it rejects the user. Training and testing data were collected from 43 users who typed the exact same string of length 37 nine consecutive times to provide data for training purposes. The users typed the same string at various times over a period from November through December 2002 to provide test data. The average false reject rate was 9.62% and the average false accept rate was 0.88%.

Algorithms↗
PubMed2003

Application of wavelet transforms and an approximate deconvolution method for the resolution of noisy overlapped peaks in DNA capillary electrophoresis.

A new procedure for resolving noisy overlapped peaks in DNA separations by capillary electrophoresis (CE) is developed. The procedure combines both a wavelet-based denoising method that effectively denoises the signal and a novel approximate deconvolution technique that resolves the fragment peaks and improves the ability to separate highly overlapped peaks early in the electrophoresis process. Different kinds of overlapped peaks with and without noise simulated by computer as well as some DNA experimental electropherograms were submitted to the new procedure. A second order differential operator with variable coefficients is applied to the entire electrophoresis signal at any given time and approximate deconvolutions of the individual Gaussian peaks are performed. The operator incorporates the effect of the superposition and gives exact annihilation in the neighborhood of each peak. Overlapped peaks with a resolution higher than 0.46 can be resolved directly. Also, the method can determine the peak components of signals with a signal to noise ratio higher than 1.4

DNA Fragmentation↗
PubMed2002

Wavelet compression in medical terahertz pulsed imaging.

This paper concerns the robustness of discrete wavelet transform (DWT) compression in terahertz pulsed imaging (TPI). TPI datasets consist of terahertz time-domain series which are sampled at each 'pixel' of the image, leading to file sizes which are typically of the order of several megabytes (MB) per image. This makes efficient compression highly desirable for both transmission and storage. However, since the data may be required for diagnostic purposes it is essential that no relevant information is lost or artefacts introduced. We show that for a nylon step wedge the estimates of refractive index and absorption coefficients are not significantly altered when the terahertz data are reconstructed from only 20% of DWT coefficients.

Algorithms↗
PubMed2001

Beats, kurtosis and visual coding.

Techniques adapted from standard higher-order statistical methods are applied to natural-image data in an attempt to discover exactly what makes 'wavelet' representations of natural scenes sparse. Specifically, this paper describes a measure known as the phase-only second spectrum, a fourth-order statistic which quantifies harmonic beat interactions in data, and uses it to show that there are statistical consistencies in the phase spectra of natural scenes. The orientation-averaged phase-only second spectra of natural images appear to show power-law behaviour rather like image power spectra, but with a spectral exponent of approximately -1 instead of -2. They also appear to display a similar form of scale-invariance. Further experimental results indicate that the form of these spectra can account for the observed sparseness of bandpass-filtered natural scenes. This implies an intimate relationship between the merits of sparse neural coding and the exploitation of non-Gaussian 'beats' structures by the visual system.

Algorithms↗
PubMed2001

Abnormal early stages of task stimulus processing in children with attention-deficit hyperactivity disorder--evidence from event-related gamma oscillations.

OBJECTIVES: Attention-related differences in early stages of stimulus processing were assessed in healthy controls and children with attention-deficit hyperactivity disorder (ADHD) by analyzing phase-locked gamma band (31-63 Hz) responses to auditory stimuli in a selective-attention task. METHODS: A total of 28 children aged 9-12 years (ADHD and matched healthy controls) pressed a button in response to each target stimulus presented at the attended side (right or left). Auditory gamma band responses (GBRs) within 0-120 ms were analyzed at 8 electrodes with wavelet transform. Effects of attended channel, stimulus type, and group were evaluated for GBR power and phase-locking. RESULTS: For both groups, GBRs had a frontal-central distribution, were significantly larger and more strongly phase-locked to target than to non-target stimuli, and did not differentiate the attended from the unattended channel. ADHD children produced larger and more strongly phase-locked GBRs than controls only to right-side stimuli, irrespective of whether these were the attended or the ignored stimuli. CONCLUSIONS: The association between auditory GBR and motor task stimulus in children suggests that phase-locked gamma oscillations may reflect processes of sensory-motor integration. ADHD-related deviations of GBRs indicate that early mechanisms of auditory stimulus processing are altered in ADHD, presumably as a result of impaired motor inhibition.

Acoustic Stimulation↗
PubMed2004

Reduced oscillatory gamma-band responses in unmedicated schizophrenic patients indicate impaired frontal network processing.

OBJECTIVE: Integration of sensory information by cortical network binding appears to be crucially involved in target detection. Studies in schizophrenia using functional and diffusion tensor neuroimaging, event-related potentials and EEG coherence indicate an impairment of cortical network coupling in this disorder. Previous electrophysiological investigations in animals and humans suggested that gamma activity (oscillations at around 40 Hz) is essential for cortical network binding. Studies in medicated schizophrenia provide evidence for a reduced gamma activity in the context of auditory stimulus processing. This is the first investigation of oscillatory activations in the gamma-band in an auditory oddball paradigm in unmedicated schizophrenic patients. METHODS: EEG gamma-band responses (GBRs) of 15 drug-free schizophrenic patients and 15 age- and gender-matched healthy controls were compared. A wavelet transform based on Morlet wavelets was employed for the calculation of oscillatory GBRs. RESULTS: In response to standard stimuli, early evoked GBRs (20-100 ms), which are supposed to reflect auditory cortex activation, did not show significant group differences. However, schizophrenic patients showed reduced evoked GBRs in a late latency range (220-350 ms), particularly after target stimuli. This deficit occurred over right frontal scalp regions. Furthermore, significant correlations were observed between oscillatory GBRs and clinical parameters in schizophrenic patients. CONCLUSIONS: The results are consistent with a relative preserved stimulus processing in the auditory cortex as reflected by the early GBR. The reduced late GBR is compatible with an abnormal interaction within a frontal lobe network, as was postulated by previous neuroimaging studies. SIGNIFICANCE: The present study provides evidence for disturbed processing within frontal cortical regions in unmedicated schizophrenic patients as indicated by reduced evoked EEG GBRs.

Acoustic Stimulation↗
PubMed1997

Fast detection of venous air embolism in Doppler heart sound using the wavelet transform.

The introduction of air bubbles into the systemic circulation can result in significant morbidity. Real-time monitoring of continuous heart sound in patients detected by precordial Doppler ultrasound is, thus, vital for early detection of venous air embolism (VAE) during surgery. In this study, the multiscale feature of wavelet transforms (WT's) is exploited to examine the embolic Doppler heart sound (DHS) during intravenous air injections in dogs. As both humans and dogs share similar physiological conditions, our methods and results for dogs are expected to be applicable to humans. The WT of DHS at scale 2j (j = 1, 2) selectively magnified the power of embolic, but not the normal, heart sound. Statistically, the enhanced embolic power was found to be sensitive (P < 0.01 at 0.01 ml of injected air) and correlated significantly (P < 0.0005, r = 0.83) with the volume of injected air from 0.01 to 0.10 ml. A fast detection algorithm of O(N) complexity with unit complexity constant for VAE was developed (processing speed = 8 ms per heartbeat), which confirmed the feasibility of real-time processing for both humans and dogs.

Algorithms↗
PubMed2006

Heart sound cancellation from lung sound recordings using time-frequency filtering.

During lung sound recordings, heart sounds (HS) interfere with clinical interpretation of lung sounds over the low frequency components which is significant especially at low flow rates. Hence, it is desirable to cancel the effect of HS on lung sound records. In this paper, a novel HS cancellation method is presented. This method first localizes HS segments using multiresolution decomposition of the wavelet transform coefficients, then removes those segments from the original lung sound record and estimates the missing data via a 2D interpolation in the time-frequency (TF) domain. Finally, the signal is reconstructed into the time domain. To evaluate the efficiency of the TF filtering, the average power spectral density (PSD) of the original lung sound segments with and without HS over four frequency bands from 20 to 300 Hz were calculated and compared with the average PSD of the filtered signals. Statistical tests show that there is no significant difference between the average PSD of the HS-free original lung sounds and the TF-filtered signal for all frequency bands at both low and medium flow rates. It was found that the proposed method successfully removes HS from lung sound signals while preserving the original fundamental components of the lung sounds.

Adolescent↗
PubMed2006

Optimal classification of long echo time in vivo magnetic resonance spectra in the detection of recurrent brain tumors.

We describe the optimal high-level postprocessing of single-voxel (1)H magnetic resonance spectra and assess the benefits and limitations of automated methods as diagnostic aids in the detection of recurrent brain tumor. In a previous clinical study, 90 long-echo-time single-voxel spectra were obtained from 52 patients and classified during follow-up (30/28/32 normal/non-progressive tumor/tumor). Based on these data, a large number of evaluation strategies, including both standard resonance line quantification and algorithms from pattern recognition and machine learning, were compared in a quantitative evaluation. Results from linear and non-linear feature extraction, including ICA, PCA and wavelet transformations, and also the data from resonance line quantification were combined systematically with different classifiers such as LDA, chemometric methods (PLS, PCR), support vector machines and ensemble methods. Classification accuracy was assessed using a leave-one-out cross-validation scheme and the area under the curve (AUC) of the receiver operator characteristic (ROC). A regularized linear regression on spectra with binned channels reached 91% classification accuracy compared with 83% from quantification. Interpreting the loadings of these regressions, we find that lipid and lactate signals are too unreliable to be used in a simple machine rule. Choline and NAA are the main source of relevant information. Overall, we find that fully automated pattern recognition algorithms perform as well as, or slightly better than, a manually controlled and optimized resonance line quantification.

Algorithms↗
PubMed2004

EEG early evoked gamma-band synchronization reflects object recognition in visual oddball tasks.

EEG was recorded in 3 visual oddball experiments during presentation of natural photos of butterflies and plants in order to study the early gamma activity evoked by familiar and novel stimuli. In all three experiments a picture of one specific butterfly served as the target and the subjects' task was to silently count them. In Experiment 1 neutral stimuli were individual pictures of butterflies from other species, in Experiment 2 neutral stimuli were individual pictures of plants and in Experiment 3 both types of neutral stimuli were applied. Phase-locking factor was computed by complex sinusoid wavelet method. Consistent with other studies, significant phase-locked gamma-synchronization was found at 80-140 ms post stimulus interval in the 20-50 Hz range at parietal and occipital sites in response to the repeating target. Non-target stimuli did not evoke similar activity in the gamma-frequency range. The observed difference can be explained if we assume that the repeated experience of an object may lead to the rapid formation of a neural assembly representing the object causing the repetition priming effect. In our study the single target stimulus was introduced to the subjects before the experiment, whereas individual non-target stimuli were unfamiliar images. Thus, subjects could form a neural representation of the target only. We suggest, that the early phase-locked gamma-activity in the 20-50 Hz range might reflect the activation of the neural representation of the familiar target stimulus.

Adult↗
PubMed2000

A new method for characterizing replacement rate variation in molecular sequences. Application of the Fourier and wavelet models to Drosophila and mammalian proteins.

We propose models for describing replacement rate variation in genes and proteins, in which the profile of relative replacement rates along the length of a given sequence is defined as a function of the site number. We consider here two types of functions, one derived from the cosine Fourier series, and the other from discrete wavelet transforms. The number of parameters used for characterizing the substitution rates along the sequences can be flexibly changed and in their most parameter-rich versions, both Fourier and wavelet models become equivalent to the unrestricted-rates model, in which each site of a sequence alignment evolves at a unique rate. When applied to a few real data sets, the new models appeared to fit data better than the discrete gamma model when compared with the Akaike information criterion and the likelihood-ratio test, although the parametric bootstrap version of the Cox test performed for one of the data sets indicated that the difference in likelihoods between the two models is not significant. The new models are applicable to testing biological hypotheses such as the statistical identity of rate variation profiles among homologous protein families. These models are also useful for determining regions in genes and proteins that evolve significantly faster or slower than the sequence average. We illustrate the application of the new method by analyzing human immunoglobulin and Drosophilid alcohol dehydrogenase sequences.

Alcohol Dehydrogenase↗
PubMed2004

Design of signal-adapted multidimensional lifting scheme for lossy coding.

This paper proposes a new method for the design of lifting filters to compute a multidimensional nonseparable wavelet transform. Our approach is stated in the general case, and is illustrated for the 2-D separable and for the quincunx images. Results are shown for the JPEG2000 database and for satellite images acquired on a quincunx sampling grid. The design of efficient quincunx filters is a difficult challenge which has already been addressed for specific cases. Our approach enables the design of less expensive filters adapted to the signal statistics to enhance the compression efficiency in a more general case. It is based on a two-step lifting scheme and joins the lifting theory with Wiener's optimization. The prediction step is designed in order to minimize the variance of the signal, and the update step is designed in order to minimize a reconstruction error. Application for lossy compression shows the performances of the method.

Algorithms↗
PubMed2005

Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform.

Mass spectrometry is being used to find disease-related patterns in mixtures of proteins derived from biological fluids. Questions have been raised about the reproducibility and reliability of peak quantifications using this technology. We collected nipple aspirate fluid from breast cancer patients and healthy women, pooled them into a quality control sample, and produced 24 replicate SELDI spectra. We developed a novel algorithm to process the spectra, denoising with the undecimated discrete wavelet transform (UDWT), and evaluated it for consistency and reproducibility. UDWT efficiently decomposes spectra into noise and signal. The noise is consistent and uncorrelated. Baseline correction produces isolated peak clusters separated by flat regions. Our method reproducibly detects more peaks than the method implemented in Ciphergen software. After normalization and log transformation, the mean coefficient of variation of peak heights is 10.6%. Our method to process spectra provides improvements over existing methods. Denoising using the UDWT appears to be an important step toward obtaining results that are more accurate. It improves the reproducibility of quantifications and supplies tools for investigation of the variations in the technology more carefully. Further study will be required, because we do not have a gold standard providing an objective assessment of which peaks are present in the samples.

Algorithms↗
PubMed2006

3D computerized segmentation of lung volume with computed tomography.

Three-dimensional (3D)-based detection and diagnosis has an important role for significantly improving the detection and diagnosis of lung cancer upon computed tomography (CT). This report presents a 3D-based method for segmenting and visualizing lung volume by using CT images. An anisotropic filtering method was developed on CT slices to enhance the signal-to-noise ratio, and a wavelet transform-based interpolation method was used combined with volume rendering to construct the 3D volumetric data based on entire CT slices. Then an adaptive 3D region-growing algorithm was designed to segment lung volume, incorporated by automatic seed-locating methods through fuzzy logic algorithms and 3D morphological closing approaches. In addition, a 3D visualization tool was designed to view volumetric data, projections, or intersections of the lung volume at any view angle. This segmentation method was tested on single-detector CT images by percentage of volume overlap and percentage of volume difference. The experiment results show that the developed 3D-based segmentation method is effective and robust. This study lays the groundwork for 3D-based computerized detection and diagnosis of lung cancer with CT imaging. In addition, this approach can be integrated into a picture archiving and communication system serving as a visualization tool for radiologists' reading and interpretation.

Algorithms↗