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PubMed2001

Phase shifting prior to spatial filtering enhances optical recordings of cardiac action potential propagation.

Optical imaging of cardiac electrical activity using a voltage-sensitive dye provides high spatial resolution maps of action potential propagation and repolarization. Charge-coupled-device (CCD) camera-based imaging systems, however, are limited by their low signal-to-noise ratio. We have developed an image processing method to enhance the quality of optical signals recorded using a CCD camera. The method is based on the observation that within a small neighborhood of adjacent pixels, the morphology of the optical action potential varies little except for a phase shift in time resulting from the propagation of the wavefront. The method uses a phase-correlation technique to first correct for this time shift before spatially filtering with a 5 x 5 Gaussian convolution kernel (sigma = 1.179). A length 5 median filter is then applied to further reduce noise by filtering in the temporal domain. The image-processing scheme allows for more accurate extraction of maps of electrical activation, repolarization, and action potential duration.

Action Potentials↗

PubMed2006

Optimal bulking agent particle size and usage for heat retention and disinfection in domestic wastewater sludge composting.

Composting of two types of sludge produced in wastewater treatment plants, raw sludge (RS) and anaerobically digested sludge (ADS), has been systematically studied by means of the experimental design technique. The results have been analyzed using a full factorial experimental design in order to determine the optimal conditions for composting such sludges in terms of bulking agent particle size and bulking agent:sludge volumetric ratio, two of the key parameters to ensure an optimal performance of the composting process. The objective function selected was a simulated death kinetics of Salmonella, which was chosen as a model pathogen microorganism to represent the disinfection of the material. For both types of sludge, optimal values were found at 5mm bulking agent particle size and 1:1 bulking agent:sludge volumetric ratio when a Gaussian function was fitted to the experimental data. Pilot scale experiments using optimal values obtained were successfully undertaken and confirmed a full disinfection of the sludge by means of the composting process. A mathematical model to simulate the disinfection performance of a composting material is presented. The model can be applied to simulate the disinfection performance of a given pathogen.

Disinfection↗

PubMed2005

Robust non-homomorphic approach for speckle reduction in medical ultrasound images.

Most existing wavelet-based image denoising techniques are developed for additive white Gaussian noise. In applications to speckle reduction in medical ultrasound (US) images, the traditional approach is first to perform the logarithmic transform (homomorphic processing) to convert the multiplicative speckle noise model to an additive one, and then the wavelet filtering is performed on the log-transformed image, followed by an exponential operation. However, this non-linear operation leads to biased estimation of the signal and increases the computational complexity of the filtering method. To overcome these drawbacks, an efficient, non-homomorphic technique for speckle reduction in medical US images is proposed. The method relies on the true characterisation of the marginal statistics of the signal and speckle wavelet coefficients. The speckle component was modelled using the generalised Nakagami distribution, which is versatile enough to model the speckle statistics under various scattering conditions of interest in medical US images. By combining this speckle model with the generalised Gaussian signal first, the Bayesian shrinkage functions were derived using the maximum a posteriori (MAP) criterion. The resulting Bayesian processor used the local image statistics to achieve soft-adaptation from homogeneous to highly heterogeneous areas. Finally, the results showed that the proposed method, named GNDShrink, yielded a signal-to-noise ratio (SNR) gain of 0.42dB over the best state-of-the-art despeckling method reported in the literature, 1.73dB over the Lee filter and 1.31dB over the Kaun filter at an input SNR of 12.0dB, when tested on a US image. Further, the visual comparison of despeckled US images indicated that the new method suppressed the speckle noise well, while preserving the texture and organ surfaces.

Algorithms↗

PubMed2002

Image processing and enhancement provided by commercial dental software programs.

OBJECTIVES: To identify and analyse methods/algorithms for image processing provided by various commercial software programs used in direct digital dental imaging and to map them onto a standardized nomenclature. METHODS: Twelve programs presented at the 28th International Dental-Show, March, 2001, Cologne, Germany and the Emago advanced software were included in this study. An artificial test image, comprised of gray scale ramps, step wedges, fields with Gaussian-distributed noise, and salt and pepper noise, was synthesized and imported to all programs to classify algorithms for display; linear, non-linear and histogram-based point processing; pseudo-coloration; linear and non-linear spatial filtering; frequency domain filtering; measurements; image analysis; and annotations. RESULTS: The 13 programs were found to possess a great variety of image processing and enhancement facilities. All programs offer gray-scale image display with interactive brightness and contrast adjustment and gray-scale inversion as well as calibration and length measurements. While Emago enables arbitrary spatial filtering with user-defined masks up to 7x7 pixels in size, most programs sparsely include filters and tools for image analysis and comparison. Moreover, the naming and implementation of provided functions differ. Some functions inappropriately use standardized image processing terms to describe their operations. CONCLUSIONS: Image processing and enhancement functions are rarely incorporated in commercial software for direct digital imaging in dental radiology. Until now, comparison of software was limited by the arbitrary naming used in each system. Standardized terminology and increased functionality of image processing should be offered to the dental profession.

Algorithms↗

PubMed2003

Robust estimation of ultrasound pulses using outlier-resistant de-noising.

A different approach to the problem of estimation of the ultrasound pulse spectrum, which usually arises as a part of ultrasound image restoration algorithms, is presented. It is shown that this estimation problem can be reformulated in terms of a de-noising problem. In this formulation, the log-spectrum of a radio-frequency line (RF-line) is viewed as a noisy measurement of the signal that needs to be estimated, i.e., the ultrasound pulse log-spectrum. The log-spectrum of the tissue reflectivity function (i.e., tissue response) is considered as the noise to be rejected. The contribution of the paper is twofold. First, it provides statistical description of the reflectivity function log-spectrum for the case, when the samples of the reflectivity function are independent identically distributed (i.i.d.) Gaussian random variables. Moreover, it is shown that the problem of the pulse spectrum recovery is essentially a de-noising problem. Consequently, it is suggested to solve the problem within the framework of the de-noising by wavelet shrinkage. Second, a computationally efficient algorithm is proposed for the pulse-spectrum estimation, which can be viewed as a modified version of the classical Donoho's three-step de-noising procedure. This modification is necessary, because of specific properties of the noise to be rejected. It is shown, that whenever the samples of the reflectivity function can be assumed to be i.i.d. Gaussian random variables, the samples of its log-spectrum obey the Fisher-Tippet distribution. For this type of noise, straightforward implementation of the standard de-noising can cause serious estimation errors. In order to overcome this difficulty, an outlier-resistant de-noising is performed. The unique properties of this modified de-noising algorithm allow estimating the pulse spectrum adaptively to its properties, as they are continuously influenced by the frequency-dependent attenuation process. The performance of the proposed algorithm is examined in a series of computer-simulations. It is shown that this algorithm, developed on the assumption of the "Gaussian" reflectivity function, remains applicable for broader classes of distributions. The results obtained in a series of in vivo experiments reveal superior performance of the novel approach over some of alternative estimation techniques, e.g., cepstrum-based estimation.

Adult↗

PubMed2002

Non-Gaussian equilibrium distributions arising from the Langevin equation.

We study the Langevin equation of a point particle driven by random noise, modeled as a two-state Markov process. The corresponding master equation differs from the Fokker-Planck equation. In equilibrium, the velocity of the particle is distributed according to a binomial power law. We discuss transient (i.e., nonequilibrium) behavior, and the consequences of non-Markovian noise statistics.

Journal Article↗

PubMedDate not supplied

Identification and boundary extraction of blobs in complex imagery.

Automated identification and boundary extraction of blobs in "real world" imagery is a difficult task because the boundaries are so irregular that there is often insufficient a priori information describing these boundaries and traditional methods fail. This paper has proposed a progressive segmentation approach and a boundary estimation method to identify the blobs and to yield an accurate description of its boundary. The multiresolution image processing technique is incorporated into the whole work. This work has been applied to the problem of identifying and extracting the boundaries of major vessels (e.g., the aorta) in Magnetic Resonance (MR) imagery and the results are satisfactory. A Laplacian of Gaussian (LOG) operator is utilized as a spot detector to locate the approximate position of the blob of interest. A subimage centered on this approximate position is extracted to eliminate unwanted portions of the image and facilitate further processing. A histogram pyramid is created for the subimage histogram for automated determination of the threshold in the noisy histogram. A shrink-expand operation is then employed to reduced noise and undesired structures in the subimage. The rough and irregular boundary of the blob of interest obtained by thresholding is reparameterized into polar coordinates to create a Fourier descriptor representation of the boundary. Then, the discrete Fourier transform is applied to the reparameterized 1-D discrete curve to permit appropriate smoothing, as required, in frequency space. Finally, the boundary estimation is completed by taking the inverse Fourier transform to reconstruct the boundary of interest.

Aorta↗

PubMed2006

A general approach for two-stage analysis of multilevel clustered non-Gaussian data.

In this article, we propose a two-stage approach to modeling multilevel clustered non-Gaussian data with sufficiently large numbers of continuous measures per cluster. Such data are common in biological and medical studies utilizing monitoring or image-processing equipment. We consider a general class of hierarchical models that generalizes the model in the global two-stage (GTS) method for nonlinear mixed effects models by using any square-root-n-consistent and asymptotically normal estimators from stage 1 as pseudodata in the stage 2 model, and by extending the stage 2 model to accommodate random effects from multiple levels of clustering. The second-stage model is a standard linear mixed effects model with normal random effects, but the cluster-specific distributions, conditional on random effects, can be non-Gaussian. This methodology provides a flexible framework for modeling not only a location parameter but also other characteristics of conditional distributions that may be of specific interest. For estimation of the population parameters, we propose a conditional restricted maximum likelihood (CREML) approach and establish the asymptotic properties of the CREML estimators. The proposed general approach is illustrated using quartiles as cluster-specific parameters estimated in the first stage, and applied to the data example from a collagen fibril development study. We demonstrate using simulations that in samples with small numbers of independent clusters, the CREML estimators may perform better than conditional maximum likelihood estimators, which are a direct extension of the estimators from the GTS method.

Animals↗

PubMed1990

Automated estimation of epithelial volume in breast cancer sections. A comparison with the image processing steps applied to gynecologic tumors.

The paper describes an image analysis technique for automated estimation of the epithelial percentage in standard paraffin tissue sections of invasive ductal breast cancers. Two staining procedures are evaluated: Feulgen (pararosanilin) and CAM 5.2-demonstrating the presence of cytokeratin 8 and 18-, both counterstained with naphthol yellow. In the technique, one image is recorded with a filter to visualize where the epithelium lies. This filter is chosen corresponding to the type of staining: it is yellow for Feulgen and blue for anti-cytokeratin CAM 5.2. To visualize where the stroma lies, the same image can be used for anti-cytokeratin CAM 5.2, whereas for Feulgen, a second image has to be recorded from the same microscope field with a blue filter. The image processing steps to determine the total tissue area comprise correction for shading, segmentation of the tissue area, and restoration of the segmented image by removal of small artefacts and closure of small tears in the tissue. The method for determination of the epithelial area consists of the following steps: correction for shading, gaussian blurring, segmentation of nuclei or epithelial cells, and editing of the segmented image by removal of small objects and closure of small spaces between the epithelial nuclei or cells. These image processing steps are compared to those for quantification of the epithelial percentage in gynecologic tumors of epithelial origin. For the Feulgen stain, the method is evaluated on 30 breast cancers of the ductal type (4 grade I, 12 grade II, and 14 grade III).(ABSTRACT TRUNCATED AT 250 WORDS)

Antibodies, Monoclonal↗

PubMed2003

Forward masking of faces by spatially quantized random and structured masks: on the roles of wholistic configuration, local features, and spatial-frequency spectra in perceptual identification.

The forward masking of faces by spatially quantized masking images was studied. Masks were used in order to exert different types of degrading effects on the early representations in facial information processing. Three types of source images for masks were used: Same-face images (with regard to targets), different-face images, and random Gaussian noise that was spectrally similar to facial images. They were all spatially quantized over the same range of quantization values. Same-face masks had virtually no masking effect at any of the quantization values. Different-face masks had strong masking effects only with fine-scale quantization, but led to the same efficiency of recognition as in the same-face mask condition with the coarsest quantization. Moreover, compared with the noise-mask condition, coarsely quantized different-face masks led to a relatively facilitated level of recognition efficiency. The masking effect of the noise mask did not vary significantly with the coarseness of quantization. The results supported neither a local feature processing account, nor a generalized spatial-frequency processing account, but were consistent with the microgenetic configuration-processing theory of face recognition. Also, the suitability of a spatial quantization technique for image configuration processing research has been demonstrated.

Adult↗

PubMed1996

A novel extravascular input function for the assessment of drug absorption in bioavailability studies.

PURPOSE: Flexible parametric models describing the input process after extravascular drug administration are needed for the assessment of absorption rate and the use of population methods in bioavailability and bioequivalence studies. METHODS: The oral concentration-time curve modeled as the product of the input and disposition function in the Laplace domain was obtained by numerical inversion methods for parameter estimation. The utility of the inverse Gaussian input density was examined using bioavailability data of an extended-release dosage form. Measures of rate of absorption and the cumulative absorbed amount profile were defined in terms of the estimated model parameters. RESULTS: Accurate estimation of absorption parameters was achieved by simultaneous fitting of the extravascular and intravascular data (describing the latter by a triexponential function). The new input function allowed a direct estimation of both extent of absorption and mean absorption time. CONCLUSIONS: The findings suggest that the inverse Gaussian density is a useful input function. Its flexibility may reduce the effect of model misspecification in parameter estimation. All parameters can be readily interpreted in terms of the absorption process.

Absorption↗

PubMed1988

Examination of the uncertainty in air concentration predictions using Hanford field data.

The accuracy of an environmental transport model is best determined by comparing model predictions with environmental measurements made under conditions similar to those assumed by the model, a process commonly referred to as model validation. Over the past several years, we have done a variety of validation studies with the popular Gaussian plume atmospheric dispersion model using data from tests conducted on the Hanford site. Data for short-term releases of small particles for a range of release heights from surface level to 111 m have been used. Downwind distances examined have ranged from a few hundred meters to 12.8 km, depending on the particular data used. Measured and predicted ground-level centerline, crosswind-integrated, and 22.5 degrees sector-averaged air concentrations have been compared. Up to six different sets of atmospheric dispersion parameters and three different atmospheric stability class specification schemes have been examined. Overall, dispersion parameters based on measurements made near Jülich, Federal Republic of Germany, give the best comparisons between observed and predicted air concentrations. The commonly used vertical temperature gradient method for determining atmospheric stability class consistently gives poor results. The accuracy of air concentration predictions improves when dry deposition processes are included in the model. Further validation studies using various Hanford data sets are planned.

Air Pollutants↗

PubMed2006

A proof of Jarzynski's nonequilibrium work theorem for dynamical systems that conserve the canonical distribution.

We present a derivation of the Jarzynski [Phys. Rev. Lett. 78, 2690 (1997)] identity and the Crooks [J. Stat. Phys. 90, 1481 (1998)] fluctuation theorem for systems governed by deterministic dynamics that conserves the canonical distribution such as Hamiltonian dynamics, Nose-Hoover dynamics, Nose-Hoover chains, and Gaussian isokinetic dynamics. The proof is based on a relation between the heat absorbed by the system during the nonequilibrium process and the Jacobian of the phase flow generated by the dynamics.

Journal Article↗

PubMed2003

Reaction-controlled diffusion: Monte Carlo simulations.

We study the coupled two-species nonequilibrium reaction-controlled diffusion model introduced by Trimper et al. [Phys. Rev. E 62, 6071 (2000)] by means of detailed Monte Carlo simulations in one and two dimensions. Particles of type A may independently hop to an adjacent lattice site, provided it is occupied by at least one B particle. The B particle species undergoes diffusion-limited reactions. In an active state with nonzero, essentially homogeneous B particle saturation density, the A species displays normal diffusion. In an inactive, absorbing phase with exponentially decaying B density, the A particles become localized. In situations with algebraic decay rho(B)(t) approximately t(-alpha(B)), as occurring either at a nonequilibrium continuous phase transition separating active and absorbing states, or in a power-law inactive phase, the A particles propagate subdiffusively with mean-square displacement (t)(2)(A)> approximately t(1-alpha(A)). We find that within the accuracy of our simulation data, alpha(A) approximately alpha(B) as predicted by a simple mean-field approach. This remains true even in the presence of strong spatiotemporal fluctuations of the B density. However, in contrast with the mean-field results, our data yield a distinctly non-Gaussian A particle displacement distribution n(A)(x-->,t) that obeys dynamic scaling and looks remarkably similar for the different processes investigated here. Fluctuations of effective diffusion rates cause a marked enhancement of n(A)(x-->,t) at low displacements /x-->/, indicating a considerable fraction of practically localized A particles, as well as at large traversed distances.

Journal Article↗

PubMed2001

Audio-visual enhancement of speech in noise.

A key problem for telecommunication or human-machine communication systems concerns speech enhancement in noise. In this domain, a certain number of techniques exist, all of them based on an acoustic-only approach--that is, the processing of the audio corrupted signal using audio information (from the corrupted signal only or additive audio information). In this paper, an audio-visual approach to the problem is considered, since it has been demonstrated in several studies that viewing the speaker's face improves message intelligibility, especially in noisy environments. A speech enhancement prototype system that takes advantage of visual inputs is developed. A filtering process approach is proposed that uses enhancement filters estimated with the help of lip shape information. The estimation process is based on linear regression or simple neural networks using a training corpus. A set of experiments assessed by Gaussian classification and perceptual tests demonstrates that it is indeed possible to enhance simple stimuli (vowel-plosive-vowel sequences) embedded in white Gaussian noise.

Adult↗

PubMed2000

Surfaces in E3 invariant under a one parameter group of isometries of E3.

We develop a convenient surface theory in E3 in order to apply it to the class of the surfaces invariant under a one-parameter group of isometries of E3. In this way we derive intrinsic characterizations along with several results of subclasses of this class of surfaces that satisfy certain preassigned properties. In the process all results are also effortlessly derived. Among these subclasses are those with surfaces; of constant mean curvature, of constant Gaussian curvature, isothermic, with constant difference or ratio of the principal curvatures.

Journal Article↗

PubMed1998

Using Gaussian-like input rate function in the two-compartment model. Formulation and application to analysis of didanosine plasma concentration in two Japanese hemophiliacs.

We used a time-dependent input rate function in the two-compartment model to simulate drug plasma concentrations after an oral administration. The input rate term has a Gaussian-like structure with two parameters, time to maximum absorption rate (tm) and measure of the duration of the absorption process (s). This structure corresponds to the scenario in which the absorption rate of the drug into the central compartment changes unimodally with respect to time after administration with a single peak at time tm. We demonstrate the applicability of this formulation in the simulation of plasma concentration of didanosine after oral administration in two Japanese hemophiliacs. We found that we were able to simulate the time courses of the didanosine plasma concentrations in both patients using the theoretical equation with the input term included, and that we were able to determine the six parameters in the equation by the least squares estimation. Pharmacokinetic values derived from the best-fit curve were almost comparable to those reported in other literature except that the Cmax and AUC0-infinity seemed to be slightly higher than those reported elsewhere. Although we are unable to verify the accuracy of this formulation because of the lack of sufficient Japanese data, we are able to demonstrate its efficacy and convenience in the application presented here.

AIDS-Related Complex↗

PubMed2003

Numerical studies of the transport behavior of a passive solute in a two-dimensional incompressible random flow field.

We study the transport behavior of a passive scalar in a two-dimensional (2D) time-independent Gaussian random velocity field by efficient and highly accurate numerical simulations. The model under consideration has been used in order to gain basic understanding of transport processes in incompressible flow through heterogeneous porous media. The velocity field is derived from the linearized solution of the Darcy equation with a Gauss-distributed log-hydraulic conductivity. The transport of a passive scalar is studied by a high precision random-walk method, which allows for a systematic nonperturbative study of the ensemble and effective dispersion coefficients. The conclusive numerical results validate the range of applicability of the perturbation theory and the consistency of nonperturbative approaches to the transport problem in a random medium. Furthermore, we observe closed streamlines in incompressible 2D Gaussian random fields, which restricts the direct applicability of the simulation method for transport in heterogeneous porous media, and questions the results of similar studies that do not observe this phenomenon.

Journal Article↗