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Results for “Gaussian process”

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PubMed2005

A universal noise removal algorithm with an impulse detector.

We introduce a local image statistic for identifying noise pixels in images corrupted with impulse noise of random values. The statistical values quantify how different in intensity the particular pixels are from their most similar neighbors. We continue to demonstrate how this statistic may be incorporated into a filter designed to remove additive Gaussian noise. The result is a new filter capable of reducing both Gaussian and impulse noises from noisy images effectively, which performs remarkably well, both in terms of quantitative measures of signal restoration and qualitative judgements of image quality. Our approach is extended to automatically remove any mix of Gaussian and impulse noise.

Algorithms↗

PubMed2006

A fast and effective model for wavelet subband histograms and its application in texture image retrieval.

This paper presents a novel, effective, and efficient characterization of wavelet subbands by bit-plane extractions. Each bit plane is associated with a probability that represents the frequency of 1-bit occurrence, and the concatenation of all the bit-plane probabilities forms our new image signature. Such a signature can be extracted directly from the code-block code-stream, rather than from the de-quantized wavelet coefficients, making our method particularly adaptable for image retrieval in the compression domain such as JPEG2000 format images. Our signatures have smaller storage requirement and lower computational complexity, and yet, experimental results on texture image retrieval show that our proposed signatures are much more cost effective to current state-of-the-art methods including the generalized Gaussian density signatures and histogram signatures.

Algorithms↗

PubMed2004

An adaptive Hinfinity controller design for bank-to-turn missiles using ridge Gaussian neural networks.

A new autopilot design for bank-to-turn (BTT) missiles is presented. In the design of autopilot, a ridge Gaussian neural network with local learning capability and fewer tuning parameters than Gaussian neural networks is proposed to model the controlled nonlinear systems. We prove that the proposed ridge Gaussian neural network, which can be a universal approximator, equals the expansions of rotated and scaled Gaussian functions. Although ridge Gaussian neural networks can approximate the nonlinear and complex systems accurately, the small approximation errors may affect the tracking performance significantly. Therefore, by employing the Hinfinity control theory, it is easy to attenuate the effects of the approximation errors of the ridge Gaussian neural networks to a prescribed level. Computer simulation results confirm the effectiveness of the proposed ridge Gaussian neural networks-based autopilot with Hinfinity stabilization.

Algorithms↗

PubMed1988

SPECT image noise power: effects of nonstationary projection noise and attenuation compensation.

The effects of nonstationary projection noise and attenuation compensation are included in a theoretic calculation of the radial noise power spectrum (NPS) of single photon emission computed tomographic (SPECT) images. The nonstationary projection noise is shown to cause a relatively large d.c. component in the NPS, especially for small objects; whereas, attenuation compensation increases the total noise variance while only changing the d.c. component slightly. The theoretic calculation agrees well with a radial NPS estimated from 1,250 SPECT images simulated from projections of random Gaussian noise, even though the effects of discrete data collection and reconstruction were not included in the theoretical model.

Computer Simulation↗

PubMed2001

Estimation of single motor unit conduction velocity from surface electromyogram signals detected with linear electrode arrays.

This work addresses the problem of estimating the conduction velocity (CV) of single motor unit (MU) action potentials from surface EMG signals detected with linear electrode arrays during voluntary muscle contractions. In ideal conditions, that is without shape or scale changes of the propagating signals and with additive white Gaussian noise, the maximum likelihood (ML) is the optimum estimator of delay. Nevertheless, other methods with computational advantages can be proposed; among them, a modified version of the beamforming algorithm is presented and compared with the ML estimator. In real cases, the resolution in delay estimation in the time domain is limited because of the sampling process. Transformation to the frequency domain allows a continuous estimation. A fast, high-resolution implementation of the presented multichannel techniques in the frequency domain is proposed. This approach is affected by a negligible decrease in performance with respect to ideal interpolation. Application of the ML estimator, based on two-channel information, to ten firings of each of three MUs provides a CV estimate affected by a standard deviation of 0.5 m s(-1); the modified beamforming and ML estimators based on five channels provide a CV standard deviation of less than 0.1 m s(-1) and allow the detection of statistically significant differences between the CVs of the three MUs. CV can therefore be used for MU classification.

Action Potentials↗

PubMed1993

1H-nuclear magnetic resonance studies of human synovial fluid in arthritic disease states as an aid to confirming metabolic activity in the synovial cavity.

1. A 1H-n.m.r. method was used to measure concentrations of valine, alanine, lactate, acetate, hyaluronan and lipids in synovial fluid obtained, during the normal course of examination from the knee joints of patients attending rheumatology and orthopaedic clinics. Fluid was available from 16 patients with osteoarthritis, 18 patients with rheumatoid arthritis, four patients with meniscal tear and one patient each with systemic lupus erythematosis, mono-arthritis, synovitis and loose bodies. Four normal specimens were obtained for comparison. 2. Valine, alanine and acetate levels all showed a normal Gaussian distribution, reflecting the distributions within the serum of the sample population. 3. Lactate concentrations divided into two distinct patterns. At concentrations below 2.5 mmol/l the lactate levels showed a Gaussian distribution, reflecting the distribution in normal serum. The normal synovial fluid specimens belong to this distribution. Above 2.5-3.0 mmol/l, lactate levels were asymmetric in distribution with a long tail at higher concentrations. These high levels of lactate can be explained by the generation of lactate through anaerobic metabolism within the synovial cavity. This metabolic process is triggered by a general inflammatory condition such as in rheumatoid arthritis. 4. The distribution of n.m.r.-observable lipid concentrations in rheumatoid arthritis and osteoarthritis each shows a normal distribution and the mean concentration is significantly higher in rheumatoid arthritis. 5. An increased n.m.r.-observable hyaluronan concentration is associated with an inflammatory situation. 6. It is concluded that raised levels of lactate and n.m.r.-observable hyaluronan and lipids are useful markers to aid the clinical distinction between rheumatoid arthritis and osteoarthritis.(ABSTRACT TRUNCATED AT 250 WORDS)

Acetates↗

PubMedDate not supplied

Computerized radiographic assessment of pulmonary blood flow in patients with and those without mitral stenosis.

The authors investigated whether a computerized analysis system can be used with chest radiography for estimating the redistribution of pulmonary blood flow in patients with and those without mitral stenosis (MS). Their system uses four-directional Laplacian-Gaussian filtering and binarization. As a physical measure, the radiographic index, which reflects the area of opacity in selected regions of interest (ROIs), was used. Fifteen men with MS and 15 men without MS were included in the study. ROIs were selected in the right upper and lower lung zones on radiographs, and the images were processed with the system. The radiographic indexes were determined in each ROI. As a measure of pulmonary blood flow redistribution, the upper-to-lower lung zone radiographic index ratio (U/L) was calculated. The U/L values correlated with pulmonary capillary wedge pressure values (r = .405, P = .025). The mean U/L value of the MS group was significantly higher than that of the non-MS group (1.16 +/- 0.14 vs 1.05 +/- 0.09, respectively; P = .016). These preliminary results indicate that this system can be used for quantitative estimation of the redistribution of pulmonary blood flow.

Aged↗

PubMed2000

Effects of masker frequency and duration in forward masking: further evidence for the influence of peripheral nonlinearity.

Forward masking has often been thought of in terms of neural adaptation, with nonlinearities in the growth and decay of forward masking being accounted for by the nonlinearities inherent in adaptation. In contrast, this study presents further evidence for the hypothesis that forward masking can be described as a linear process, once peripheral, mechanical nonlinearities are taken into account. The first experiment compares the growth of masking for on- and off-frequency maskers. Signal thresholds were measured as a function of masker level for three masker-signal intervals of 0, 10, and 30 ms. The brief 4-kHz sinusoidal signal was masked by a 200-ms sinusoidal forward masker which had a frequency of either 2.4 kHz (off-frequency) or 4 kHz (on-frequency). As in previous studies, for the on-frequency condition, the slope of the function relating signal threshold to masker level became shallower as the delay between the masker and signal was increased. In contrast, the slopes for the off-frequency condition were independent of masker-signal delay and had a value of around unity, indicating linear growth of masking for all masker-signal delays. In the second experiment, a broadband Gaussian noise forward masker was used to mask a brief 6-kHz sinusoidal signal. The spectrum level of the masker was either 0 or 40 dB (re: 20 microPa). The gap between the masker and signal was either 0 or 20 ms. Signal thresholds were measured for masker durations from 5 to 200 ms. The effect of masker duration was found to depend more on signal level than on gap duration or masker level. Overall, the results support the idea that forward masking can be modeled as a linear process, preceded by a static nonlinearity resembling that found on the basilar membrane.

Auditory Threshold↗

PubMed2001

Noninvasive electrical imaging of the heart: theory and model development.

The aim of this work is to begin quantifying the performance of a recently developed activation imaging algorithm of Huiskamp and Greensite [IEEE Trans. Biomed. Eng. 44:433-446]. We present here the modeling and computational issues associated with this process. First, we present a practical construction of the appropriate transfer matrix relating an activation sequence to body surface potentials from a general boundary value problem point of view. This approach makes explicit the role of different Green's functions and elucidates features (such as the anisotropic versus isotropic distinction) not readily apparent from alternative formulations. A new analytic solution is then developed to test the numerical implementation associated with the transfer matrix formulation presented here and convergence results for both potentials and normal currents are given. Next, details of the construction of a generic porcine model using a nontraditional data-fitting procedure are presented. The computational performance of this model is carefully examined to obtain a mesh of an appropriate resolution to use in inverse calculations. Finally, as a test of the entire approach, we illustrate the activation inverse procedure by reconstructing a known activation sequence from simulated data. For the example presented, which involved two ectopic focii with large amounts of Gaussian noise (100 microV rms) present in the torso signals, the reconstructed activation sequence had a similarity index of 0.880 when compared to the input source.

Algorithms↗

PubMed1981

Rapid electric responses of oats to phytochrome show membrane processes unrelated to pelletability.

The electric potential difference changes observed on etiolated oat coleoptiles in response to phytochrome transformation have been further studied using contacts on the coleoptile surface. Results are given, at 0.4 second resolution, for the first 1.5 minutes after saturating flashes of light each lasting 1 second.Responses to initial red (662 nanometers), to far red (about 700 nanometers and above) 10 minutes later, and to second red 10 minutes later still, all have time courses that are approximately Gaussian sigmoid in shape. The response to far red is of opposite sign to the response to red. Approximate magnitudes of the three changes, 1 minute after the light flash, are +6 millivolts for red, -10 millivolts for far red, +3.5 millivolts for the second red. It is argued that the observations reflect a hyperpolarization of the plasmalemma of coleoptile cells following red light and depolarization following far red. The response to red is not produced by a change in membrane permeability to K(+). The mechanism could include a change to Na(+) or Cl(-) permeability or a modulation of an electrogenic pump: enhanced H(+) extrusion, Ca(2+) extrusion, or Cl(-) uptake. The response to far red could be produced by the reverse of one of those changes.The Gaussian curve is fitted to the data to determine the time at which the responses begin. Each response begins 4.5 seconds after the start of the flash of light. These delays are not related to the time course of phytochrome pelletability or redistribution in the cell. The delays may be due to some interaction of the transformed phytochrome with the plasma-lemma. Alternatively, the transformed phytochrome may interact quickly with some other structure which initiates a signal that takes 4.5 seconds to reach the plasmalemma.

Journal Article↗

PubMed2001

Water modeled signal removal and data quantification in localized MR spectroscopy using a time-scale postacquistion method.

We have previously shown the continuous wavelet transform (CWT), a signal-processing tool, which is based upon an iterative algorithm using a lorentzian signal model, to be useful as a postacquisition water suppression technique. To further exploit this tool we show its usefulness in accurately quantifying the signal metabolites after water removal. However, due to the static field inhomogeneities, eddy currents, and "radiation damping," the water signal and the metabolites may no longer have a lorentzian lineshape. Therefore, another signal model must be used. As the CWT is a flexible method, we have developed a new algorithm using a gaussian model and found that it fits the signal components, especially the water resonance, better than the lorentzian model in most cases. A new framework, which uses the two models, is proposed. The framework iteratively extracts each resonance, starting by the water peak, from the raw signal and adjusts its envelope to both the lorentzian and the gaussian models. The model giving the best fit is selected. As a consequence, the small signals originating from metabolites when selecting, removing, and quantifying the dominant water resonance from the raw time domain signal are preserved and an accurate estimation of their concentrations is obtained. This is demonstrated by analyzing (1H) magnetic resonance spectroscopy unsuppressed water data collected from a phantom with known concentrations at two different field strengths and data collected from normal volunteers using two different localization methods.

Artifacts↗

PubMed1986

Explaining discrepancies between longitudinal and cross-sectional models.

Data from longitudinal studies may be analyzed both cross-sectionally and longitudinally. Discrepancies between estimates obtained from these analyses pose questions about the validity of cross-sectional estimates of change. In some cases these discrepancies are the result of period effects, cohort effects, or selective dropout. In others, they are the result of incomplete modeling of the process and are spurious rather than substantive. In this report, we show that when the true relation between a dependent variable and age is non-linear (e.g. quadratic), but is modeled as linear, the estimated age effect will be a function of the age distribution. In a continuous-time idealization, if the age distribution is Gaussian, the estimated age effects agree. If the age distribution is symmetric and the non-linearity is quadratic, cross-sectional and longitudinal results agree. Otherwise they do not. We illustrate these points by analysis of the relation between aging and pulmonary function in middle and old age using data from a large, prospective, longitudinal study.

Adult↗

PubMed2005

Learning letter identification in peripheral vision.

Performance for a variety of visual tasks improves with practice. The purpose of this study was to determine the nature of the processes underlying perceptual learning of identifying letters in peripheral vision. To do so, we tracked changes in contrast thresholds for identifying single letters presented at 10 degrees in the inferior visual field, over a period of six consecutive days. The letters (26 lowercase Times-Roman letters, subtending 1.7 degrees) were embedded within static two-dimensional Gaussian luminance noise, with rms contrast ranging from 0% (no noise) to 20%. We also measured the observers' response consistency using a double-pass method on days 1, 3 and 6, by testing two additional blocks on each of these days at luminance noise of 3% and 20%. These additional blocks were the exact replicates of the corresponding block at the same noise contrast that was tested on the same day. We analyzed our results using both the linear amplifier model (LAM) and the perceptual template model (PTM). Our results showed that following six days of training, the overall reduction (improvement across all noise levels) in contrast threshold for our seven observers averaged 21.6% (range: 17.2-31%). Despite fundamental differences between LAM and PTM, both models show that learning leads to an improvement of the perceptual template (filter) such that the template is more capable of extracting the crucial information from the signal. Results from both the PTM analysis and the double-pass experiment imply that the stimulus-dependent component of the internal noise does not change with learning.

Adult↗

PubMed2001

Quantitative comparison of algorithms for tracking single fluorescent particles.

Single particle tracking has seen numerous applications in biophysics, ranging from the diffusion of proteins in cell membranes to the movement of molecular motors. A plethora of computer algorithms have been developed to monitor the sub-pixel displacement of fluorescent objects between successive video frames, and some have been claimed to have "nanometer" resolution. To date, there has been no rigorous comparison of these algorithms under realistic conditions. In this paper, we quantitatively compare specific implementations of four commonly used tracking algorithms: cross-correlation, sum-absolute difference, centroid, and direct Gaussian fit. Images of fluorescent objects ranging in size from point sources to 5 microm were computer generated with known sub-pixel displacements. Realistic noise was added and the above four algorithms were compared for accuracy and precision. We found that cross-correlation is the most accurate algorithm for large particles. However, for point sources, direct Gaussian fit to the intensity distribution is the superior algorithm in terms of both accuracy and precision, and is the most robust at low signal-to-noise. Most significantly, all four algorithms fail as the signal-to-noise ratio approaches 4. We judge direct Gaussian fit to be the best algorithm when tracking single fluorophores, where the signal-to-noise is frequently near 4.

Algorithms↗

PubMed2026

PyEvoMotion: a Python tool for population-based time-course analysis of genome evolution.

SUMMARY: We present PyEvoMotion, an open-source Python tool for inferring molecular clock models with time-dependent Gaussian noise from high-throughput genomic datasets. PyEvoMotion features a command-line interface and a modular architecture, allowing seamless integration into larger bioinformatic pipelines. The tool supports customizable filtering, temporal discretization definition, and mutation classification, making it adaptable to diverse research needs. While traditional phylogenetic methods may encounter computational challenges with large datasets, PyEvoMotion can process thousands to millions of sequences to compute statistical parameters associated with a stochastic differential equation model, thereby weighting the genetic variation within the population. Using viral genomic data, we demonstrate its capability to infer evolutionary rates and detect non-Brownian evolutionary motions with subdiffusive behavior. PyEvoMotion shows potential to provide overlooked insights into genome evolution in different contexts. AVAILABILITY AND IMPLEMENTATION: The open source software is available on GitHub at https://github.com/luksgrin/PyEvoMotion and on SourceForge at https://sourceforge.net/projects/pyevomotion.

Software↗

PubMed2000

Inverse planning incorporating organ motion.

Accurate targeting is important in intensity-modulated radiation therapy (IMRT). The positional uncertainties of structures with respect to the external beams arise in part from random organ motion and patient setup errors. While it is important to improve immobilization and reduce the influence of organ motion, the residual effects should be included in the IMRT plan design. Current inverse planning algorithms follow the conventional approach and include uncertainties by assuming population-based margins to the target and sensitive structures. Margin around a structure represents a "hard boundary" and the fact that a structure has a spatial probability distribution has been completely ignored. With increasing understanding of spatial uncertainties of structures and the technical capability of fine-tuning the dose distribution on an individual beamlet level in IMRT, it seems timely and important to fully utilize the information in the planning process. This will reduce the "effective" margins of the structures and facilitate dose escalation. Instead of specifying a "hard margin," we describe an inverse planning algorithm which takes into consideration positional uncertainty in terms of spatial probability distribution. The algorithm was demonstrated by assuming that the random organ motion can be represented by a three-dimensional Gaussian distribution function. Other probability distributions can be dealt with similarly. In particular, the commonly used "hard margin" is a special case of the current approach with a uniform probability distribution within a specified range. The algorithm was applied to plan treatment for a prostate case and a pancreatic case. The results were compared with those obtained by adding a margin to the clinical target volume. Better sparing of the sensitive structures were obtained in both cases using the proposed method for approximately the same target coverage.

Algorithms↗

PubMed2005

p-Value simulation for affected sib pair multiple testing.

A standard approach to calculation of critical values for affected sib pair multiple testing is based on: (a) fully informative markers, (b) Haldane map function assumptions leading to a Markov chain model for inheritance vectors, (c) central limit approximation to averages of sampled inheritance vectors leading to an Ornstein-Uhlenbeck process approximation, and (d) simple approximations to the maximum of such a process. Under these assumptions, assuming equispaced or close to equispaced markers, if the sample size is large, an approximation is available that is easy to calculate and performs well. However, for small sample sizes, a large number of markers, and for small p-values, there is good reason to be cautious about the use of the Gaussian approximation. We develop an algorithm for calculation of multiple testing p-values based on the standard Markov chain model, avoiding the use of Gaussian (large sample) approximation. We illustrate the use of this algorithm by demonstrating some inadequacies of the Gaussian approximation.

Algorithms↗

PubMed1999

A new way for the analysis of the exocytosis.

Exocytosis is the most common way for cells to secrete substances. This is a wide distributed phenomenon that involves all cell types and all animal species from yeast to human. Catecholamine (CA) release from adrenal chromaffin cells occurs by the exocytosis of secretory vesicles also called chromaffin granules. Individual secretory events can be easily monitored by the use of carbon fibers encased in glass microelectrodes. Catecholamines oxidized at the electrode tip produce a transient electrical current wave called secretory spike. The typical secretory spike consists in a sharp elevation of current followed by a rapid exponential decrease to the basal level. A 35-50% of the spikes showed a pre-spike wave called "foot" which represents the CA release through the fusion pore. The time course of secretory spikes observed is altered by extracellular phenomena's like diffusion. It has been suggested that amperometric spikes can be described by the convolution of a Gaussian with a decreasing exponential. The exponential function is partially governed by the diffusion of the secreted substances towards the electrode. In this article a method to deconvolve both functions is proposed. This mathematical approach allows the observation of the original secretory profile--the Gaussian--without the distortion caused by the diffusional broadening of catecholamines.

Adrenal Medulla↗