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Results for “deconvolution”

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At least 379 records · Page 21Linked to original sources

PubMed2004

Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution.

Diffusion-weighted magnetic resonance imaging can provide information related to the arrangement of white matter fibers. The diffusion tensor is the model most commonly used to derive the orientation of the fibers within a voxel. However, this model has been shown to fail in regions containing several fiber populations with distinct orientations. A number of alternative models have been suggested, such as multiple tensor fitting, q-space, and Q-ball imaging. However, each of these has inherent limitations. In this study, we propose a novel method for estimating the fiber orientation distribution directly from high angular resolution diffusion-weighted MR data without the need for prior assumptions regarding the number of fiber populations present. We assume that all white matter fiber bundles in the brain share identical diffusion characteristics, thus implicitly assigning any differences in diffusion anisotropy to partial volume effects. The diffusion-weighted signal attenuation measured over the surface of a sphere can then be expressed as the convolution over the sphere of a response function (the diffusion-weighted attenuation profile for a typical fiber bundle) with the fiber orientation density function (ODF). The fiber ODF (the distribution of fiber orientations within the voxel) can therefore be obtained using spherical deconvolution. The properties of the technique are demonstrated using simulations and on data acquired from a volunteer using a standard 1.5-T clinical scanner. The technique can recover the fiber ODF in regions of multiple fiber crossing and holds promise for applications such as tractography.

Algorithms↗

PubMed2006

Cerebral perfusion mapping using a robust and efficient method for deconvolution analysis of dynamic contrast-enhanced images.

Dynamic contrast-enhanced (DCE) imaging using MRI or CT is emerging as a promising tool for diagnostic imaging of cerebral disorders and the monitoring of tumor response to treatment. In this study, we present a robust and efficient deconvolution method based on a linearized model of the impulse residue function, which allows for the mapping of functional cerebral parameters such as cerebral blood flow, volume, mean transit time, and permeability. Monte Carlo simulation studies were performed to study the accuracy and stability of the proposed method, before applying it to clinical study cases of patients with cerebral tumors imaged using DCE CT. Functional parameter maps generated using the proposed method revealed the locations of the cerebral tumors and were found to be of sufficiently good clarity for marked regional differences in tissue vascularity and permeability to be assessed. In particular, tumor visualization and delineation were found to be better on the parameter maps that were indicative of the breakdown of the blood-brain barrier.

Adenoma↗

PubMed2004

Determination of a misfit dislocation complex in SiGe/Si heterostructures by image deconvolution technique in HREM.

The core structure of a dislocation complex in SiGe/Si system composed of a perfect 60 degrees dislocation and an extended 60 degrees dislocation has been revealed at atomic level. This is attained by applying the image deconvolution technique in combination with dynamical diffraction effect correction to an image taken with a 200kV field-emission high-resolution electron microscope. The possible configuration of the dislocation complex is analyzed and their Burgers vectors are determined.

Journal Article↗

PubMed2004

A method of improving overall resolution in ultrasonic array imaging using spatio-temporal deconvolution.

In this paper a beamforming method for ultrasonic array imaging is presented that performs both spatial and temporal deconvolution based on a minimum mean square error (MMSE) criteria. The presented MMSE receive mode beamformer performs a regularized inversion of the propagation operator for the ultrasonic array system at hand. The MMSE beamformer accounts for the transmit and receive processes, defined in terms of finite array element sizes, transmit focusing laws and electrical transducer characteristics. The MMSE beamformer is compared to the traditional delay-and-sum (DAS) beamformer with respect to both resolution and signal-to-noise ratio. The two algorithms are compared using both simulated and measured data. The simulated data was obtained using ultrasonic field simulations and the measured data was acquired using a linear phased array imaging wire targets in water. The results show that the MMSE beamformer has superior temporal and lateral resolution compared to DAS. It is also shown that the MMSE beamformer can be expressed as a filter bank, which enables parallel processing at high frame rates.

Journal Article↗

PubMed2004

A new technique for the identification of ultrasonic flaw signals using deconvolution.

The identification of ultrasonic flaw signals is a difficult task in the angle beam ultrasonic testing of welded joints due to the presence of non-relevant signals from the geometric reflectors such as weld-roots and counter-bores. This paper describes a new approach to identify ultrasonic flaw signals in such a problematic situation. A similarity function is defined as the deconvolution of a target signal by a reference signal. The similarity functions for the same type of flaws/references are symmetric bandlimited impulse-like patterns with larger amplitudes while those for different types of flaws/references are asymmetrical broad patterns with relatively smaller amplitudes. Therefore, ultrasonic signals could be identified by the pattern of the similarity function. In the initial experiments, the proposed technique showed great potential for identifying ultrasonic flaw signals in the inspection of weld joints.

Journal Article↗

PubMed2003

Multicolor deconvolution microscopy of thick biological specimens.

One limitation in understanding disease at the cellular level has been the inability to efficiently analyze DNA on a cell-to-cell basis within the natural tissue context. However, DNA analyses at a single-cell resolution should be instrumental for the understanding of cancer cell biology, cancer evolution, for chromosomal mosaic analysis and rare cell events, and should provide otherwise inaccessible information on essential biological processes. Here we present a fluorescence in situ hybridization-based multicolor deconvolution technique for three-dimensional microscopy. We use up to seven different color channels for probe detection, which allows the simultaneous high-resolution localization of multiple point-like sources within a biological specimen with a thickness of up to 30 micro m. In addition, a DNA counterstain is used for volume labeling of the nuclei offering the opportunity for a simultaneous segmentation of nuclei. Furthermore, as the instrumentation consists of a standard fluorescence microscope it represents a low-cost method as compared to confocal microscopy.

Centromere↗

PubMed2002

Measurement of thin filament lengths by distributed deconvolution analysis of fluorescence images.

The lengths of the actin (thin) filaments in sarcomeres directly influence the physiological properties of striated muscle. Although electron microscopy techniques provide the highest precision and accuracy for measuring thin filament lengths, significant obstacles limit their widespread use. Here, we describe distributed deconvolution, a fluorescence-based method that determines the location of specific thin filament components such as tropomodulin (Tmod) or probes such as phallacidin (a phalloidin derivative). Using Tmod and phallacidin fluorescence, we were able to determine the thin filament lengths of isolated chicken pectoralis major myofibrils with an accuracy and precision comparable to electron microscopy. Additionally, phallacidin fluorescence intensity at the Z line provided information about the width of Z lines. Furthermore, we detected significant variations in thin filaments lengths among individual myofibrils from chicken posterior latissimus dorsai and embryonic chick cardiac myocytes, suggesting that a ruler molecule (e.g., nebulin) does not strictly determine thin filament lengths in these muscles. This versatile method is applicable to myofibrils in living cells that exhibit significant variation in sarcomere lengths, and only requires a fluorescence microscope and a CCD camera.

Actins↗

PubMed2000

Comparison of gas chromatography-pulsed flame photometric detection-mass spectrometry, automated mass spectral deconvolution and identification system and gas chromatography-tandem mass spectrometry as tools for trace level detection and identification.

The complexity of a matrix is in many cases the major limiting factor in the detection and identification of trace level analytes. In this work, the ability to detect and identify trace level of pesticides in complex matrices was studied and compared in three, relatively new methods: (a) GC-PFPD-MS where simultaneous PFPD (pulsed flame photometric detection) and MS analysis is performed. The PFPD indicates the exact chromatographic time of suspected peaks for their MS identification and provides elemental information; (b) automatic GC-MS data analysis using the AMDIS ("Automated Mass Spectral Deconvolution and Identification System") software by the National Institute of Standards and Technology; (c) GC-MS-MS analysis. A pesticide mixture (MX-5), containing diazinon, methyl parathion, ethyl parathion, methyl trithion and ethion was spiked, in descending levels from 1 ppm to 10 ppb, into soil and sage (spice) extracts and the detection level and identification quality were evaluated in each experiment. PFPD-MS and AMDIS exhibited similar performance, both superior to standard GC-MS, revealing and identifying compounds that did not exhibit an observable GC peak (either buried under the chromatographic background baseline or co-eluting with other interfering GC peaks). GC-MS-MS featured improved detection limits (lower by a factor of 6-8) compared to AMDIS and PFPD-MS. The GC-PFPD-MS-MS combination was found useful in several cases, where no reconstructed ion chromatogram MS-MS peaks existed, but an MS-MS spectrum could still be extracted at the elution time indicated by PFPD. The level of identification and confirmation with MS-MS was inferior to that of the other two techniques. In comparison with the soil matrix, detection limits obtained with the loaded sage matrix were poorer by similar factors for all the techniques studied (factors of 5.8, >6.5 and 4.0 for AMDIS, PFPD-MS and MS-MS, respectively). Based on the above results, the paper discusses the trade-offs between detectivity and identification level with the compared three techniques as well as other more traditional techniques and approaches.

Automation↗

PubMed2002

An expectation-maximisation algorithm for the deconvolution of the intrinsic distribution of single molecule's parameters.

Values obtained from single molecule techniques exhibit distinct distributions comprising an uncertainty due to random noise convoluted with the intrinsic distribution of the molecule's properties. In the fields of single molecule light microscopy and spectroscopy, force microscopy and spectroscopy as well as other techniques like electrophysiology, sophisticated data analysis algorithms are available which extract the interesting parameters and their uncertainties from the noisy data set. The intrinsic distributions of these parameters contain valuable information about the molecules' physical and chemical properties, that need to be deconvoluted from the data. Here, we present an expectation-maximisation (EM-) algorithm that estimates the intrinsic distribution in single molecule experiments. The performance is tested by using computer simulations and the application of the method is demonstrated for data from single molecule force spectroscopy.

Algorithms↗

PubMed1997

Noise deconvolution based on the L1-metric and decomposition of discrete distributions of postsynaptic responses.

A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.

Animals↗

PubMed1988

Quantitation of collagen fragments and gelatin by deconvolution of polarimetry denaturation curves.

A method for quantitating nicked or shortened molecules (fragments) in pepsinized bovine type I collagen preparations using polarimetry thermal denaturation curves is described. The shortened molecules denature about 4 degrees C lower than intact collagen molecules. The analog output of a polarimeter was digitized and stored on a microcomputer disk. A BASIC program was written which retrieves the specific rotation data from the disk, smooths the data with a boxcar average, and plots the derivative of the denaturation curve. The derivative curve was deconvoluted by fitting three Gaussian curves to the derivative curve using published algorithms. The area of the Gaussian centered at 37 degrees C was proportional to the amount of collagen fragments. A good correlation between the amount of fragments determined by polarimetry and by a trypsin sensitivity assay was observed. The overall precision of the method was about 10% RSD, and the method was repeatable by multiple analysts. Application of the method to reconstituted fibrillar collagen samples showed that more fragments are generated when pepsin digestion time is lengthened. By fitting a fourth Gaussian component to the derivative curve, the method can also be used to determine relative amounts of denatured collagen (helix partially unwound but alpha chains not nicked). The detection limit for denatured collagen is about 20%.

Algorithms↗

PubMed2001

Spectral deconvolution and operational use of stripping ratios in airborne radiometrics.

Spectral deconvolution using stripping ratios for a set of pre-defined energy windows is the simplest means of reducing the most important part of gamma-ray spectral information. In this way, the effective interferences between the measured peaks are removed, leading, through a calibration, to clear estimates of radionuclide inventory. While laboratory measurements of stripping ratios are relatively easy to acquire, with detectors placed above small-scale calibration pads of known radionuclide concentrations, the extrapolation to measurements at altitudes where airborne survey detectors are used bring difficulties such as air-path attenuation and greater uncertainties in knowing ground level inventories. Stripping ratios are altitude dependent, and laboratory measurements using various absorbers to simulate the air-path have been used with some success. Full-scale measurements from an aircraft require a suitable location where radionuclide concentrations vary little over the field of view of the detector (which may be hundreds of metres). Monte Carlo simulations offer the potential of full-scale reproduction of gamma-ray transport and detection mechanisms. Investigations have been made to evaluate stripping ratios using experimental and Monte Carlo methods.

Air Pollution, Radioactive↗

PubMed2000

Image deconvolution for protein crystals.

The image deconvolution technique developed for non-biological samples, which is based on the weak-phase-object approximation and principle of maximum entropy, was applied to simulated images of the biotin-binding protein streptavidin. A slight modification of the technique was introduced to solve the problem caused by the special image formation condition for biological samples. It has been shown that the modified technique is effective.

Crystallography↗

PubMed1996

Quantitative analysis of multivariate data using artificial neural networks: a tutorial review and applications to the deconvolution of pyrolysis mass spectra.

The implementation of artificial neural networks (ANNs) to the analysis of multivariate data is reviewed, with particular reference to the analysis of pyrolysis mass spectra. The need for and benefits of multivariate data analysis are explained followed by a discussion of ANNs and their optimisation. Finally, an example of the use of ANNs for the quantitative deconvolution of the pyrolysis mass spectra of Staphylococcus aureus mixed with Escherichia coli is demonstrated.

Escherichia coli↗

PubMed1998

Bimodal granulocyte transit time through the human lung demonstrated by deconvolution analysis.

The lungs are an important site of granulocyte pooling. The aim of the study is to quantify pulmonary vascular granulocyte transit time using deconvolution analysis, as has previously been performed to measure pulmonary red cell transit time. Granulocyte and red cell studies were performed in separate groups of patients. Both cell types were labelled with Tc-99m, which for granulocyte labelling was complexed with hexamethylpropyleneamine oxime (HMPAO). The red cell impulse response function (IRF) was monoexponential with a median transit time of 4.3 s. The granulocyte IRF was biexponential in 19 of 22 subjects, 18 of whom had systemic inflammation (inflammatory bowel disease, systemic vasculitis or graft-vs-host disease) and four were controls without inflammatory disease. The median transit time of the fast component ranged from 20 to 25 s and of the slow component 120-138 s in the four patient groups. The fraction of cells undergoing slow transit correlated significantly with (a) mean granulocyte transit time and (b) the fraction showing shape change in vitro. We conclude that granulocyte transit time through the pulmonary circulation is bimodal and that shape-changed (activated) cells transit more slowly that non-activated cells. The size of the fraction undergoing slow transit is closely related to mean granulocyte transit time and is an important determinant of the size of the pulmonary vascular granulocyte pool.

Cell Movement↗

PubMed1999

Synthesis and deconvolution of the first combinatorial library of glycosidase inhibitors.

A combinatorial library of 125 compounds with a structure consisting of 1-azafagomine linked at N-1 via an acetic acid linker to a variable tripeptide was synthesised. The library was synthesised by Merrifield split and mix synthesis of the peptide, followed by capping with chloroacetate, regioselective nucleophilic substitution with 1-azafagomine and cleavage from the polymeric support. The library was screened for inhibition of beta-glucosidase, alpha-glucosidase and glycogen phosphorylase and found to display beta-glucosidase inhibition. Deconvolution of the library revealed that some inhibition was caused by all library members but the strongest inhibitor was clearly a compound having three hydroxyproline residues in the peptide fragment. This compound was a weaker but more selective inhibitor than 1-azafagomine itself.

Carbohydrate Sequence↗

PubMed2000

EPR spectrum deconvolution and dose assessment of fossil tooth enamel using maximum likelihood common factor analysis.

In order to determine the components which give rise to the EPR spectrum around g = 2 we have applied Maximum Likelihood Common Factor Analysis (MLCFA) on the EPR spectra of enamel sample 1126 which has previously been analysed by continuous wave and pulsed EPR as well as EPR microscopy. MLCFA yielded agreeing results on three sets of X-band spectra and the following components were identified: an orthorhombic component attributed to CO2-, an axial component (CO3(3-)), as well as four isotropic components, three of which could be attributed to SO2-, a tumbling CO2- and a central line of a dimethyl radical. The X-band results were confirmed by analysis of Q-band spectra where three additional isotropic lines were found, however, these three components could not be attributed to known radicals. The orthorhombic component was used to establish dose response curves for the assessment of the past radiation dose, D(E). The results appear to be more reliable than those based on conventional peak-to-peak EPR intensity measurements or simple Gaussian deconvolution methods.

Animals↗

PubMed2000

A multiple window deconvolution technique for measuring low-energy beta activity in samples contaminated with high-energy beta impurities using liquid scintillation spectrometry

An optimised multiple window counting technique, using liquid scintillation counting combined with internal standardisation and spectrum unfolding has been developed for the assessment of low-level, low-energy beta activity in multilabeled samples containing high-energy beta impurities. Distinct spectral contributions are reconstructed for every individual radionuclide and impurity using software deconvolution techniques. The most important advantages of this method are that it does not require setting up quench correction curves and that the exact knowledge of reference activity is not required, thus eliminating two important sources of uncertainty in the final results. The technique has been successfully used on mixtures of 3H, 14C, 63Ni, 99Tc and 60Co over a wide range of quenching and activity ratios.

Journal Article↗