Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Deconvolution”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8Linked to original sources
PubMed1996

Dispersion, aberration and deconvolution in multi-wavelength fluorescence images.

The wavelength dependence of the incoherent point spread function in a wide-field microscope was investigated experimentally. Dispersion in the sample and optics can lead to significant changes in the point spread function as wavelength is varied over the range commonly used in fluorescence microscopy. For a given sample, optical conditions can generally be optimized to produce a point spread function largely free of spherical aberration at a given wavelength. Unfortunately, deviations in wavelength from this value will result in spherically aberrated point spread functions. Therefore, when multiple fluorophores are used to localize different components in the same sample, the image of the distribution of at least one of the fluorophores will be spherically aberrated. This aberration causes a loss of intensity and resolution, thereby complicating the localization and analysis of multiple components in a multi-wavelength image. We show that optimal resolution can be restored to a spherically aberrated image by constrained, iterative deconvolution, as long as the spherical aberration in the point spread function used for deconvolution matches the aberration in the image reasonably well. The success of this method is essentially independent of the initial degree of spherical aberration in the image. Deconvolution of many biological images can be achieved by collecting a small library of spherically aberrated and unaberrated point spread functions, and then choosing a point spread function appropriate for deconvolving each image. The co-localization and relative intensities of multiple components can then be accurately studied in a multi-wavelength image.

Algorithms↗
PubMed2002

Deconvolution improves colocalization analysis of multiple fluorochromes in 3D confocal data sets more than filtering techniques.

Background and noise impair image quality by affecting resolution and obscuring image detail in the low intensity range. Because background levels in unprocessed confocal images are frequently at about 30% maximum intensity, colocalization analysis, a typical segmentation process, is limited to high intensity signal and prone to noise-induced, false-positive events. This makes suppression or removal of background crucial for this kind of image analysis. This paper examines the effects of median filtering and deconvolution, two image-processing techniques enhancing the signal-to-noise ratio (SNR), on the results of colocalization analysis in confocal data sets of biological specimens. The data show that median filtering can improve the SNR by a factor of 2. The technique eliminates noise-induced colocalization events successfully. However, because filtering recovers voxel values from the local neighbourhood false-negative ('dissipation' of signal intensity below threshold value) as well as false-positive ('fusion' of noise with low intensity signal resulting in above threshold intensities), results can be generated. In addition, filtering involves the convolution of an image with a kernel, a procedure that inherently impairs resolution. Image restoration by deconvolution avoids both of these disadvantages. Such routines calculate a model of the object considering various parameters that impair image formation and are able to suppress background down to very low levels (< 10% maximum intensity, resulting in a SNR improved by a factor 3 as compared to raw images). This makes additional objects in the low intensity but high frequency range available to analysis. In addition, removal of noise and distortions induced by the optical system results in improved resolution, which is of critical importance in cases involving objects of near resolution size. The technique is, however, sensitive to overestimation of the background level. In conclusion, colocalization analysis will be improved by deconvolution more than by filtering. This applies especially to specimens characterized by small object size and/or low intensities.

Animals↗
PubMed2003

Expression deconvolution: a reinterpretation of DNA microarray data reveals dynamic changes in cell populations.

Cells grow in dynamically evolving populations, yet this aspect of experiments often goes unmeasured. A method is proposed for measuring the population dynamics of cells on the basis of their mRNA expression patterns. The population's expression pattern is modeled as the linear combination of mRNA expression from pure samples of cells, allowing reconstruction of the relative proportions of pure cell types in the population. Application of the method, termed expression deconvolution, to yeast grown under varying conditions reveals the population dynamics of the cells during the cell cycle, during the arrest of cells induced by DNA damage and the release of arrest in a cell cycle checkpoint mutant, during sporulation, and following environmental stress. Using expression deconvolution, cell cycle defects are detected and temporally ordered in 146 yeast deletion mutants; six of these defects are independently experimentally validated. Expression deconvolution allows a reinterpretation of the cell cycle dynamics underlying all previous microarray experiments and can be more generally applied to study most forms of cell population dynamics.

Cell Cycle↗
PubMed1994

Recursive deconvolution of combinatorial chemical libraries.

A recursive strategy that solves for the active members of a chemical library is presented. A pentapeptide library with an alphabet of Gly, Leu, Phe, and Tyr (1024 members) was constructed on a solid support by the method of split synthesis. One member of this library (NH2-Tyr-Gly-Gly-Phe-Leu) is a native binder to a beta-endorphin antibody. A variation of the split synthesis approach is used to build the combinatorial library. In four vials, a member of the library's alphabet is coupled to a solid support. After each coupling, a portion of the resin from each of the four reaction vials was set aside and catalogued. The solid support from each vial is then combined, mixed, and redivided. The steps of (i) coupling, (ii) saving and cataloging, and (iii) randomizing were repeated until a pentapeptide library was obtained. The four pentapeptide libraries where the N-terminal amino acid is defined were screened against the beta-endorphin antibody and quantitated via an ELISA. The amino acid of the four pools that demonstrated the most binding was then coupled to the four tetrapeptide partial libraries that had been set aside and catalogued during the split synthesis. This recursive deconvolution was repeated until the best binders were deduced. Besides the anticipated native binder, two other members of the library displayed significant binding. This recursive method of deconvolution does not use a molecular tag, requires only one split synthesis, and can be applied to the deconvolution of nonlinear small-molecule combinatorial libraries and linear oligomeric combinatorial libraries, since it is based only on the procedure of the synthesis.

Amino Acid Sequence↗
PubMed1989

Deconvolution in medical ultrasonics: practical considerations.

Deconvolution can, in principle, enhance the spatial resolution of specular reflectors in medical ultrasonic imaging but, in practice, the resolution improvement offered is offset by the introduction of undesirable artefacts. In this study, several problems related to deconvolution were identified and practical suggestions for minimising artefacts were made. These include: fitting a three-dimensional surface to experimentally measured beam profiles in order to take into account the depth-dependence of the point spread function (PSF); adaptive detail-preserving noise filtering as a preprocessing tool in order to improve the quality of the data and reduce the speckle enhancement artefact; a histogram modification procedure in order to overcome the problems of ringing, over- and undershooting. Processing of a large number of A-scan data obtained from tissue-mimicking phantoms and the abdomens of normal volunteers demonstrated the efficiency of these techniques in reducing artefacts. The performance of deconvolution in terms of resolution improvement was satisfactory when data from resolution test objects were processed but poor with abdominal scans. This difference in performance raises the question as to how similar the PSF in tissue is to the experimentally measured PSF in water or even a tissue-mimicking material.

Abdomen↗
PubMed1991

Ideal versus human observer for long-tailed point spread functions: does deconvolution help?

The ideal observer represents a Bayesian approach to performing detection tasks. Since such tasks are frequently used as a prototype tasks for radiological imaging systems, the detectability measured at the output of an ideal detector can be used as a figure of merit to characterize the imaging system. For the detectability achieved by the ideal observer to be a good figure of merit, it should predict the ability of the human observer to perform the same detection task. Of great general interest, especially to the medical community, are imaging devices with long-tailed point spread functions (PSFs). Such PSFs may occur due to septal penetration in collimators, veiling glare in image intensifiers or scattered radiation in the body. We have investigated the effect that this type of PSF has on human visual signal detection and whether any improvement in performance can be gained by deconvolving the tails of the PSF. For the ideal observer, it is straightforward to show that the performance is independent of any linear, invertible deconvolution filter. Our psychophysical studies show, however, that performance of the human observer is indeed improved by deconvolution. The ideal observer is, therefore, not a good predictor of human observer performance for detection of a signal imaged through a long-tailed PSF. We offer some explanations for this discrepancy by using some characteristics of the visual process and suggest a standard of comparison for the human observer that takes into account these characteristics. A look at the performance of the non-prewhitening (npw) ideal observer, before and after deconvolution, also brings some good insight into this study.

Bayes Theorem↗
PubMed2025

Enhancing and accelerating cell type deconvolution of large-scale spatial transcriptomics slices with dual network model.

MOTIVATION: Cell type deconvolution deciphers spatial distribution of mRNA transcripts at single cell level by integrating single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data to infer mixture of cell types of spots in slices. Current algorithms are criticized for neglecting connection between scRNA-seq and spatial transcriptomics data, as well as time-consuming, hampering their application to large-scale datasets. RESULTS: In this study, we propose a joint learning nonnegative matrix factorization algorithm for fast cell type deconvolution (aka jMF2D), which integrates scRNA-seq and spatial transcriptomics data with network models. To bridge scRNA-seq and spatial transcriptomics data, jMF2D jointly learns cell type similarity network to enhance quality of signatures of cell types, thereby promoting accuracy and efficiency of deconvolution. Experiments demonstrate that jMF2D outperforms state-of-the-art baselines in terms of accuracy by saving about 90% running time on various datasets generated by different platforms. Furthermore, it can also facilitates the identification of spatial domains and bio-marker genes, providing an efficient and effective model for analyzing spatial transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The software is coded using python, and is free available for academic https://github.com/xkmaxidian/jMF2D.

Algorithms↗
PubMed2000

Amplitude correction in image deconvolution for determining crystal defects at atomic level

A method is proposed to improve the image deconvolution technique based on the weak-phase object approximation for determining the crystal defects at atomic level. Originally, both the amplitude and phase modulation caused by the contrast transfer function (CTF) was removed for all reflections in the diffractogram of the image and then the deconvoluted image was obtained by carrying out the inverse FT. In this paper after removing the CTF modulation the amplitudes of reflections are further corrected by constraining the integral amplitudes to be equal to the corresponding structure factor amplitudes of perfect crystals. [110] high-resolution electron microscope images were simulated for a structure model of Si crystal containing the 60 degrees dislocation with different thickness. A comparison between deconvoluted images with the amplitudes corrected by the present method and those uncorrected is given to show the effectiveness of the method. The amplitude-crystal thickness dependence for images simulated close to the Scherzer defocus condition has been analysed and the result serves as an empirical basis of the method. The validity and limitation of the method are discussed.

Journal Article↗
PubMed2000

Zero loss peak deconvolution for bandgap EEL spectra.

This paper shows how bandgap EEL spectra are commonly processed either by deconvolution or subtraction methods in an attempt to remove effects arising from the finite width and long tail of the zero loss peak. This paper will compare the two main methods, and show that the deconvolution method is significantly more reliable and free of user-interpretation or artefacts. We first consider how the zero loss peak is produced and what effects experimental conditions have upon it, and then show that only by the deconvolution method can accurate bandgap energies and bandgap densities of states be determined.

Journal Article↗
PubMed1999

Tc-99m DTPA renal scintigraphy using deconvolution analysis with six functional images of the mean time to evaluate acute pyelonephritis.

In 38 children with proved P-fimbriated Escherichia coli acute pyelonephritis, Tc-99m DTPA dynamic renal scintigraphy in the zoom mode using deconvolution analysis was performed, and the results were compared with those of Tc-99m DMSA scans. From the dynamic study, six functional images of the mean time were generated. Each functional image was analyzed separately to search for focal areas of increased mean time within the kidney contour, especially over the kidney parenchyma. Time-activity curves from these areas were generated and analyzed. Tc-99m DMSA scintigraphy showed generalized or focal decreased uptake in 32 (41.8%) kidneys, and deconvolution analysis of Tc-99m DTPA scintigraphy revealed pathologic renographic curves in 58 (77.6%) kidneys. Prolonged whole-kidney and normal renal parenchymal transit times (dilatation without obstruction) were found in 38 (50%) kidneys, whereas prolonged whole-kidney and renal parenchymal transit times (dilatation with obstruction) were observed in 20 (27.6%) kidneys. Separate analysis of each of the six functional images of the mean time showed focal areas of increased mean time in the kidney parenchyma of 11 kidneys. In five cases, time-activity curves from these areas showed a sharp increase of activity on the descending part of the curve, which might reflect the return of urine from the collecting system into kidney cortex (i.e., intrarenal reflux). These results showed that in a urinary tract with acute pyelonephritis, urodynamic changes may lead to obstructive nephropathy and intrarenal reflux. Tc-99m DTPA renal scintigraphy in the zoom mode using deconvolution analysis with six functional images of the mean time has proved to be a valuable method to evaluate acute pyelonephritis, thus allowing dynamic and morphologic analysis of the urinary tract at the same time.

Child↗
PubMed2001

EPR tooth enamel dosimetry: optimization of the automated spectra deconvolution routine.

A computer routine was developed for automatic deconvolution of electron paramagnetic resonance spectra of tooth enamel samples for individual radiation dose reconstruction in the low dose region. The deconvolution routine uses the non-linear least square fit of a model simulating a tooth enamel spectrum by superposition of derivative Gaussian functions to obtain the amplitude of the dosimetric radiation induced signal. The parameters of the model and of the routine were optimized on a dose response level using a criterion of the least standard deviation of the derived radiation induced signal amplitude from the regression line vs. the nominal doses for the series of spectra of samples irradiated in known doses in the range 0-500 mGy. It was found that for the series of spectra of the heterogeneous samples (every sample is prepared from different teeth of different persons), it is essential to vary in the least square fit the parameters describing the shape of the native background signal in order to obtain the best accuracy. In the case of the series of spectra of the homogeneous (pooled) samples, almost the same accuracy of the results was obtained using the procedures with varied and fixed background signal parameters. The standard error of the dose reconstruction by the optimized deconvolution procedure was estimated as about 30 mGy for heterogeneous samples and 20 mGy for homogeneous samples.

Algorithms↗
PubMed2003

Comment on "Atomic spectral line-free parameter deconvolution procedure".

Recently Milosavljević and Poparić [Phys. Rev. E 63, 036404 (2001)] proposed a method for the deconvolution of isolated asymmetric plasma broadened atomic (neutral) spectral lines. The authors claim that their method enables a complete plasma diagnostics by applying this deconvolution on a single experimental line profile. In the present Comment the proposed deconvolution procedure and its application are reexamined.

Comment↗
PubMed2002

Blind deconvolution of ultrasound sequences using nonparametric local polynomial estimates of the pulse.

The problem of reconstructing the reflectivity of a biological tissue is examined by means of blind deconvolution of the echo ultrasound signals. It is shown that the quality of the reconstruction procedure can be significantly improved when initially the ultrasonic pulse is accurately estimated. A new approach to the estimation of the ultrasound pulse echo sequences is proposed, using local polynomial approximation, which is closely related to the wavelet transform theory. This approach can be viewed as a modification of homomorphic deconvolution, by using bases different from the Fourier basis of the space of square-integrable functions L2. The bases used here are the orthogonal compactly supported wavelet bases. It is shown that the locality of the estimate can be extremely useful in number of cases of practical interest, resulting in estimates with smaller root-mean squared (rms) errors, as compared with estimates employing the Fourier basis. This approach is applied to ultrasound signals, for estimation of the ultrasound pulse log-spectrum from the log-spectrum of radio-frequency (RF) sequences. It is shown, conceptually and experimentally, that the proposed approach can provide robust and rapidly computed estimates of the ultrasound pulses from the RF-sequences, as obtained in the process of tissue scanning. The pulse phase was recovered using the minimum-phase assumption, which was found to hold for the transducers in use. The obtained pulse estimates are used for the deconvolution of the RF-sequences, which result in stable estimates of the tissue reflectivity function, fairly independent of the properties of the imaging system. Simulated data, data obtained from several phantoms and from in vitro experiments have been processed and the results seem to be quite promising.

Animals↗
PubMed2005

Blind deconvolution of images using optimal sparse representations.

The relative Newton algorithm, previously proposed for quasi-maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of images. Smooth approximation of the absolute value is used as the nonlinear term for sparse sources. In addition, we propose a method of sparsification, which allows blind deconvolution of arbitrary sources, and show how to find optimal sparsifying transformations by supervised learning.

Algorithms↗
PubMed2004

Assessment of perfusion by dynamic contrast-enhanced imaging using a deconvolution approach based on regression and singular value decomposition.

The assessment of tissue perfusion by dynamic contrast-enhanced (DCE) imaging involves a deconvolution process. For analysis of DCE imaging data, we implemented a regression approach to select appropriate regularization parameters for deconvolution using the standard and generalized singular value decomposition methods. Monte Carlo simulation experiments were carried out to study the performance and to compare with other existing methods used for deconvolution analysis of DCE imaging data. The present approach is found to be robust and reliable at the levels of noise commonly encountered in DCE imaging, and for different models of the underlying tissue vasculature. The advantages of the present method, as compared with previous methods, include its efficiency of computation, ability to achieve adequate regularization to reproduce less noisy solutions, and that it does not require prior knowledge of the noise condition. The proposed method is applied on actual patient study cases with brain tumors and ischemic stroke, to illustrate its applicability as a clinical tool for diagnosis and assessment of treatment response.

Algorithms↗
PubMed1985

In vitro and in vivo deconvolution assessment of drug release kinetics from oxprenolol Oros preparations.

The relationship between in vitro and in vivo drug release from Oros systems has been examined by analysing plasma concentration data from two pharmacokinetic studies, using a numerical deconvolution technique. This method generates an input profile by comparing the response with that achieved following an instantaneous reference unit dose. The approach is conceptually simple and does not require compartmental pharmacokinetic modelling or curve fitting. In the analysis of the first study, the plasma profile following intravenous dosing was used as the reference function, allowing the combined release/absorption process to be calculated; for the second, an oral bolus was used, the result of the deconvolution therefore indicating the in vivo dissolution rate of the Oros systems. The in vivo release from Oros in most volunteers followed the same pattern as that measured in vitro; only after 6-8 h was the decline in the in vivo release rate somewhat greater than expected. In a few individuals the cumulative absorption profile reached an early plateau level which coincided, on some but not all occasions, with the premature excretion of the Oros system from the body. The amount of drug in recovered systems agreed reasonably with the prediction of the deconvolution analysis.

Biological Availability↗
PubMed1993

The frequency and amplitude of growth hormone secretory episodes as determined by deconvolution analysis are increased in adolescents with insulin dependent diabetes mellitus and are unaffected by short-term euglycaemia.

OBJECTIVE: High overnight plasma growth hormone (GH) levels in insulin-dependent diabetes mellitus (IDDM) are reflected in both an increase in the GH pulse amplitude and elevated baseline GH concentrations. To determine whether these are a result of an increase in GH secretory episodes, we undertook deconvolution analysis of overnight GH profiles using previously determined half-life data. DESIGN: Deconvolution of overnight GH profiles (2000-0800 h) was undertaken from normal and diabetic adolescents (either on their usual insulin regime (n = 15), during overnight euglycaemic clamp using a variable rate insulin infusion (n = 29), or during clamp plus 100 mg pirenzepine to suppress endogenous GH (n = 7)). PATIENTS: Thirty-five normal and 29 diabetic adolescents of both sexes at all stages of puberty. MEASUREMENTS: GH secretory rates were calculated from deconvolution analysis, and Fourier transformation was increased mean overnight GH secretion when analysed by sex and by puberty stage compared to normal subjects; overnight GH secretion median (range) of diabetic group 1.88 (0.56-3.81) mU/min; control group 0.62 (0.32-1.92) mU/min (P < 0.001). Fourier transform analysis of these secretory episodes showed greater pulse frequency in the diabetics with dominant pulse periodicity of 90 minutes compared with 135 minutes in normal subjects. During overnight euglycaemia, mean +/- SEM overnight GH secretory rates were comparable to subjects' usual regime night (1.82 +/- 0.33 vs 1.91 +/- 0.37 mU/min) and there was no change in the dominant pulse periodicity of 90 minutes. Pirenzepine administration in diabetic subjects significantly reduced overnight GH secretion from 1.57 +/- 0.19 to 0.71 +/- 0.80 mU/min (P < 0.001) showing a median (range) reduction of 63 (9.3-82.8)% when compared to the subjects' clamp night. However, dominant pulse periodicity was not altered by pirenzepine administration, and remained at 90 minutes. CONCLUSION: In patients with insulin-dependent diabetes mellitus there is an increase in both the amplitude and frequency of pulsatile GH secretion compared to normal subjects, which is not affected by maintenance of overnight normoglycaemia. The anticholinergic drug pirenzepine appears to suppress the amplitude of GH pulse secretion but has no effect on frequency.

Adolescent↗
PubMedDate not supplied

Validation of deconvolutional analysis for the measurement of hepatic function in dogs with toxic-induced liver disease.

The extraction of the hepatobiliary radiopharmaceutical 99mTc-mebrofenin (Choletec) by the liver can be used to evaluate the severity of hepatocellular disease. The hepatic parenchymal cells extract mebrofenin from the blood by the same active transport mechanism as bilirubin. The ability of the liver to extract 99mTc-mebrofenin is a measure of hepatic parenchymal cell function. In this study, we induced hepatocellular disease by administration of a hepatotoxic drug and compared a direct method of determining the hepatic extraction of 99mTc-mebrofenin to hepatic extraction fraction derived from deconvolutional analysis. We also compared both methods of calculating the hepatic extraction of 99mTc-mebrofenin to liver histopathology. Hepatic extraction fraction derived from deconvolutional analysis correlated very well to the direct measurement technique (R=0.922, p < 0.001). Both methods of determining hepatic extraction correlated well to quantitative histopathology, having the same correlation coefficient and p values. (R=-0.833, p=0.003). As the hepatic extraction 99mTc-mebrofenin decreased, the severity of the histopathologic lesions of the liver increased in a linear fashion. There was a significant correlation of the hepatic excretion T1/2 to quantitative histopathology (R=0.949, p < 0.001). The hepatic excretion T1/2 increased as the severity of the histopathologic lesions of the liver increased. Hepatic extraction (HEF) and excretion of 99mTc-mebrofenin are good predictors of the severity of hepatocellular damage in toxic induced liver disease. This study helps validate the premise that HEF derived from deconvolutional analysis is a good predictor of the actual first pass hepatic extraction of 99mTc-mebrofenin.

Aniline Compounds↗