Imaging samples in silica aerogel using an experimental point spread function.

PubMed

White, Amanda J; Ebel, Denton S

2015-02-01

Light microscopy is a powerful tool that allows for many types of samples to be examined in a rapid, easy, and nondestructive manner. Subsequent image analysis, however, is compromised by distortion of signal by instrument optics. Deconvolution of images prior to analysis allows for the recovery of lost information by procedures that utilize either a theoretically or experimentally calculated point spread function (PSF). Using a laser scanning confocal microscope (LSCM), we have imaged whole impact tracks of comet particles captured in silica aerogel, a low density, porous SiO2 solid, by the NASA Stardust mission. In order to understand the dynamical interactions between the particles and the aerogel, precise grain location and track volume measurement are required. We report a method for measuring an experimental PSF suitable for three-dimensional deconvolution of imaged particles in aerogel. Using fluorescent beads manufactured into Stardust flight-grade aerogel, we have applied a deconvolution technique standard in the biological sciences to confocal images of whole Stardust tracks. The incorporation of an experimentally measured PSF allows for better quantitative measurements of the size and location of single grains in aerogel and more accurate measurements of track morphology.

Bending the Rules: Widefield Microscopy and the Abbe Limit of Resolution

PubMed Central

Verdaasdonk, Jolien S.; Stephens, Andrew D.; Haase, Julian; Bloom, Kerry

2014-01-01

One of the most fundamental concepts of microscopy is that of resolution–the ability to clearly distinguish two objects as separate. Recent advances such as structured illumination microscopy (SIM) and point localization techniques including photoactivated localization microscopy (PALM), and stochastic optical reconstruction microscopy (STORM) strive to overcome the inherent limits of resolution of the modern light microscope. These techniques, however, are not always feasible or optimal for live cell imaging. Thus, in this review, we explore three techniques for extracting high resolution data from images acquired on a widefield microscope–deconvolution, model convolution, and Gaussian fitting. Deconvolution is a powerful tool for restoring a blurred image using knowledge of the point spread function (PSF) describing the blurring of light by the microscope, although care must be taken to ensure accuracy of subsequent quantitative analysis. The process of model convolution also requires knowledge of the PSF to blur a simulated image which can then be compared to the experimentally acquired data to reach conclusions regarding its geometry and fluorophore distribution. Gaussian fitting is the basis for point localization microscopy, and can also be applied to tracking spot motion over time or measuring spot shape and size. All together, these three methods serve as powerful tools for high-resolution imaging using widefield microscopy. PMID:23893718

Image processing tools dedicated to quantification in 3D fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dieterlen, A.; De Meyer, A.; Colicchio, B.; Le Calvez, S.; Haeberlé, O.; Jacquey, S.

2006-05-01

3-D optical fluorescent microscopy now becomes an efficient tool for the volume investigation of living biological samples. Developments in instrumentation have permitted to beat off the conventional Abbe limit. In any case the recorded image can be described by the convolution equation between the original object and the Point Spread Function (PSF) of the acquisition system. Due to the finite resolution of the instrument, the original object is recorded with distortions and blurring, and contaminated by noise. This induces that relevant biological information cannot be extracted directly from raw data stacks. If the goal is 3-D quantitative analysis, then to assess optimal performance of the instrument and to ensure the data acquisition reproducibility, the system characterization is mandatory. The PSF represents the properties of the image acquisition system; we have proposed the use of statistical tools and Zernike moments to describe a 3-D PSF system and to quantify the variation of the PSF. This first step toward standardization is helpful to define an acquisition protocol optimizing exploitation of the microscope depending on the studied biological sample. Before the extraction of geometrical information and/or intensities quantification, the data restoration is mandatory. Reduction of out-of-focus light is carried out computationally by deconvolution process. But other phenomena occur during acquisition, like fluorescence photo degradation named "bleaching", inducing an alteration of information needed for restoration. Therefore, we have developed a protocol to pre-process data before the application of deconvolution algorithms. A large number of deconvolution methods have been described and are now available in commercial package. One major difficulty to use this software is the introduction by the user of the "best" regularization parameters. We have pointed out that automating the choice of the regularization level; also greatly improves the reliability of the measurements although it facilitates the use. Furthermore, to increase the quality and the repeatability of quantitative measurements a pre-filtering of images improves the stability of deconvolution process. In the same way, the PSF prefiltering stabilizes the deconvolution process. We have shown that Zemike polynomials can be used to reconstruct experimental PSF, preserving system characteristics and removing the noise contained in the PSF.

XAP, a program for deconvolution and analysis of complex X-ray spectra

USGS Publications Warehouse

Quick, James E.; Haleby, Abdul Malik

1989-01-01

The X-ray analysis program (XAP) is a spectral-deconvolution program written in BASIC and specifically designed to analyze complex spectra produced by energy-dispersive X-ray analytical systems (EDS). XAP compensates for spectrometer drift, utilizes digital filtering to remove background from spectra, and solves for element abundances by least-squares, multiple-regression analysis. Rather than base analyses on only a few channels, broad spectral regions of a sample are reconstructed from standard reference spectra. The effects of this approach are (1) elimination of tedious spectrometer adjustments, (2) removal of background independent of sample composition, and (3) automatic correction for peak overlaps. Although the program was written specifically to operate a KEVEX 7000 X-ray fluorescence analytical system, it could be adapted (with minor modifications) to analyze spectra produced by scanning electron microscopes, electron microprobes, and probes, and X-ray defractometer patterns obtained from whole-rock powders.

Multi-kernel deconvolution for contrast improvement in a full field imaging system with engineered PSFs using conical diffraction

NASA Astrophysics Data System (ADS)

Enguita, Jose M.; Álvarez, Ignacio; González, Rafael C.; Cancelas, Jose A.

2018-01-01

The problem of restoration of a high-resolution image from several degraded versions of the same scene (deconvolution) has been receiving attention in the last years in fields such as optics and computer vision. Deconvolution methods are usually based on sets of images taken with small (sub-pixel) displacements or slightly different focus. Techniques based on sets of images obtained with different point-spread-functions (PSFs) engineered by an optical system are less popular and mostly restricted to microscopic systems, where a spot of light is projected onto the sample under investigation, which is then scanned point-by-point. In this paper, we use the effect of conical diffraction to shape the PSFs in a full-field macroscopic imaging system. We describe a series of simulations and real experiments that help to evaluate the possibilities of the system, showing the enhancement in image contrast even at frequencies that are strongly filtered by the lens transfer function or when sampling near the Nyquist frequency. Although results are preliminary and there is room to optimize the prototype, the idea shows promise to overcome the limitations of the image sensor technology in many fields, such as forensics, medical, satellite, or scientific imaging.

Joint de-blurring and nonuniformity correction method for infrared microscopy imaging

NASA Astrophysics Data System (ADS)

Jara, Anselmo; Torres, Sergio; Machuca, Guillermo; Ramírez, Wagner; Gutiérrez, Pablo A.; Viafora, Laura A.; Godoy, Sebastián E.; Vera, Esteban

2018-05-01

In this work, we present a new technique to simultaneously reduce two major degradation artifacts found in mid-wavelength infrared microscopy imagery, namely the inherent focal-plane array nonuniformity noise and the scene defocus presented due to the point spread function of the infrared microscope. We correct both nuisances using a novel, recursive method that combines the constant range nonuniformity correction algorithm with a frame-by-frame deconvolution approach. The ability of the method to jointly compensate for both nonuniformity noise and blur is demonstrated using two different real mid-wavelength infrared microscopic video sequences, which were captured from two microscopic living organisms using a Janos-Sofradir mid-wavelength infrared microscopy setup. The performance of the proposed method is assessed on real and simulated infrared data by computing the root mean-square error and the roughness-laplacian pattern index, which was specifically developed for the present work.

Deconvolution improves the accuracy and depth sensitivity of time-resolved measurements

NASA Astrophysics Data System (ADS)

Diop, Mamadou; St. Lawrence, Keith

2013-03-01

Time-resolved (TR) techniques have the potential to distinguish early- from late-arriving photons. Since light travelling through superficial tissue is detected earlier than photons that penetrate the deeper layers, time-windowing can in principle be used to improve the depth sensitivity of TR measurements. However, TR measurements also contain instrument contributions - referred to as the instrument-response-function (IRF) - which cause temporal broadening of the measured temporal-point-spread-function (TPSF). In this report, we investigate the influence of the IRF on pathlength-resolved absorption changes (Δμa) retrieved from TR measurements using the microscopic Beer-Lambert law (MBLL). TPSFs were acquired on homogeneous and two-layer tissue-mimicking phantoms with varying optical properties. The measured IRF and TPSFs were deconvolved to recover the distribution of time-of-flights (DTOFs) of the detected photons. The microscopic Beer-Lambert law was applied to early and late time-windows of the TPSFs and DTOFs to access the effects of the IRF on pathlength-resolved Δμa. The analysis showed that the late part of the TPSFs contains substantial contributions from early-arriving photons, due to the smearing effects of the IRF, which reduced its sensitivity to absorption changes occurring in deep layers. We also demonstrated that the effects of the IRF can be efficiently eliminated by applying a robust deconvolution technique, thereby improving the accuracy and sensitivity of TR measurements to deep-tissue absorption changes.

Application of an NLME-Stochastic Deconvolution Approach to Level A IVIVC Modeling.

PubMed

Kakhi, Maziar; Suarez-Sharp, Sandra; Shepard, Terry; Chittenden, Jason

2017-07-01

Stochastic deconvolution is a parameter estimation method that calculates drug absorption using a nonlinear mixed-effects model in which the random effects associated with absorption represent a Wiener process. The present work compares (1) stochastic deconvolution and (2) numerical deconvolution, using clinical pharmacokinetic (PK) data generated for an in vitro-in vivo correlation (IVIVC) study of extended release (ER) formulations of a Biopharmaceutics Classification System class III drug substance. The preliminary analysis found that numerical and stochastic deconvolution yielded superimposable fraction absorbed (F abs ) versus time profiles when supplied with exactly the same externally determined unit impulse response parameters. In a separate analysis, a full population-PK/stochastic deconvolution was applied to the clinical PK data. Scenarios were considered in which immediate release (IR) data were either retained or excluded to inform parameter estimation. The resulting F abs profiles were then used to model level A IVIVCs. All the considered stochastic deconvolution scenarios, and numerical deconvolution, yielded on average similar results with respect to the IVIVC validation. These results could be achieved with stochastic deconvolution without recourse to IR data. Unlike numerical deconvolution, this also implies that in crossover studies where certain individuals do not receive an IR treatment, their ER data alone can still be included as part of the IVIVC analysis. Published by Elsevier Inc.

Temporal and spatial binning of TCSPC data to improve signal-to-noise ratio and imaging speed

NASA Astrophysics Data System (ADS)

Walsh, Alex J.; Beier, Hope T.

2016-03-01

Time-correlated single photon counting (TCSPC) is the most robust method for fluorescence lifetime imaging using laser scanning microscopes. However, TCSPC is inherently slow making it ineffective to capture rapid events due to the single photon product per laser pulse causing extensive acquisition time limitations and the requirement of low fluorescence emission efficiency to avoid bias of measurement towards short lifetimes. Furthermore, thousands of photons per pixel are required for traditional instrument response deconvolution and fluorescence lifetime exponential decay estimation. Instrument response deconvolution and fluorescence exponential decay estimation can be performed in several ways including iterative least squares minimization and Laguerre deconvolution. This paper compares the limitations and accuracy of these fluorescence decay analysis techniques to accurately estimate double exponential decays across many data characteristics including various lifetime values, lifetime component weights, signal-to-noise ratios, and number of photons detected. Furthermore, techniques to improve data fitting, including binning data temporally and spatially, are evaluated as methods to improve decay fits and reduce image acquisition time. Simulation results demonstrate that binning temporally to 36 or 42 time bins, improves accuracy of fits for low photon count data. Such a technique reduces the required number of photons for accurate component estimation if lifetime values are known, such as for commercial fluorescent dyes and FRET experiments, and improve imaging speed 10-fold.

Blind deconvolution of 2-D and 3-D fluorescent micrographs

NASA Astrophysics Data System (ADS)

Krishnamurthi, Vijaykumar; Liu, Yi-Hwa; Holmes, Timothy J.; Roysam, Badrinath; Turner, James N.

1992-06-01

This paper presents recent results of our reconstructions of 3-D data from Drosophila chromosomes as well as our simulations with a refined version of the algorithm used in the former. It is well known that the calibration of the point spread function (PSF) of a fluorescence microscope is a tedious process and involves esoteric techniques in most cases. This problem is further compounded in the case of confocal microscopy where the measured intensities are usually low. A number of techniques have been developed to solve this problem, all of which are methods in blind deconvolution. These are so called because the measured PSF is not required in the deconvolution of degraded images from any optical system. Our own efforts in this area involved the maximum likelihood (ML) method, the numerical solution to which is obtained by the expectation maximization (EM) algorithm. Based on the reasonable early results obtained during our simulations with 2-D phantoms, we carried out experiments with real 3-D data. We found that the blind deconvolution method using the ML approach gave reasonable reconstructions. Next we tried to perform the reconstructions using some 2-D data, but we found that the results were not encouraging. We surmised that the poor reconstructions were primarily due to the large values of dark current in the input data. This, coupled with the fact that we are likely to have similar data with considerable dark current from a confocal microscope prompted us to look into ways of constraining the solution of the PSF. We observed that in the 2-D case, the reconstructed PSF has a tendency to retain values larger than those of the theoretical PSF in regions away from the center (outside of those we considered to be its region of support). This observation motivated us to apply an upper bound constraint on the PSF in these regions. Furthermore, we constrain the solution of the PSF to be a bandlimited function, as in the case in the true situation. We have derived two separate approaches for implementing the constraint. One approach involves the mathematical rigors of Lagrange multipliers. This approach is discussed in another paper. The second approach involves an adaptation of the Gershberg Saxton algorithm, which ensures bandlimitedness and non-negativity of the PSF. Although the latter approach is mathematically less rigorous than the former, we currently favor it because it has a simpler implementation on a computer and has smaller memory requirements. The next section describes briefly the theory and derivation of these constraint equations using Lagrange multipliers.

Volumetric Light-field Encryption at the Microscopic Scale

PubMed Central

Li, Haoyu; Guo, Changliang; Muniraj, Inbarasan; Schroeder, Bryce C.; Sheridan, John T.; Jia, Shu

2017-01-01

We report a light-field based method that allows the optical encryption of three-dimensional (3D) volumetric information at the microscopic scale in a single 2D light-field image. The system consists of a microlens array and an array of random phase/amplitude masks. The method utilizes a wave optics model to account for the dominant diffraction effect at this new scale, and the system point-spread function (PSF) serves as the key for encryption and decryption. We successfully developed and demonstrated a deconvolution algorithm to retrieve both spatially multiplexed discrete data and continuous volumetric data from 2D light-field images. Showing that the method is practical for data transmission and storage, we obtained a faithful reconstruction of the 3D volumetric information from a digital copy of the encrypted light-field image. The method represents a new level of optical encryption, paving the way for broad industrial and biomedical applications in processing and securing 3D data at the microscopic scale. PMID:28059149

Volumetric Light-field Encryption at the Microscopic Scale

NASA Astrophysics Data System (ADS)

Li, Haoyu; Guo, Changliang; Muniraj, Inbarasan; Schroeder, Bryce C.; Sheridan, John T.; Jia, Shu

2017-01-01

We report a light-field based method that allows the optical encryption of three-dimensional (3D) volumetric information at the microscopic scale in a single 2D light-field image. The system consists of a microlens array and an array of random phase/amplitude masks. The method utilizes a wave optics model to account for the dominant diffraction effect at this new scale, and the system point-spread function (PSF) serves as the key for encryption and decryption. We successfully developed and demonstrated a deconvolution algorithm to retrieve both spatially multiplexed discrete data and continuous volumetric data from 2D light-field images. Showing that the method is practical for data transmission and storage, we obtained a faithful reconstruction of the 3D volumetric information from a digital copy of the encrypted light-field image. The method represents a new level of optical encryption, paving the way for broad industrial and biomedical applications in processing and securing 3D data at the microscopic scale.

SU-F-T-478: Effect of Deconvolution in Analysis of Mega Voltage Photon Beam Profiles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muthukumaran, M; Manigandan, D; Murali, V

2016-06-15

Purpose: To study and compare the penumbra of 6 MV and 15 MV photon beam profiles after deconvoluting different volume ionization chambers. Methods: 0.125cc Semi-Flex chamber, Markus Chamber and PTW Farmer chamber were used to measure the in-plane and cross-plane profiles at 5 cm depth for 6 MV and 15 MV photons. The profiles were measured for various field sizes starting from 2×2 cm till 30×30 cm. PTW TBA scan software was used for the measurements and the “deconvolution” functionality in the software was used to remove the volume averaging effect due to finite volume of the chamber along lateralmore » and longitudinal directions for all the ionization chambers. The predicted true profile was compared and the change in penumbra before and after deconvolution was studied. Results: After deconvoluting the penumbra decreased by 1 mm for field sizes ranging from 2 × 2 cm till 20 x20 cm. This is observed for along both lateral and longitudinal directions. However for field sizes from 20 × 20 till 30 ×30 cm the difference in penumbra was around 1.2 till 1.8 mm. This was observed for both 6 MV and 15 MV photon beams. The penumbra was always lesser in the deconvoluted profiles for all the ionization chambers involved in the study. The variation in difference in penumbral values were in the order of 0.1 till 0.3 mm between the deconvoluted profile along lateral and longitudinal directions for all the chambers under study. Deconvolution of the profiles along longitudinal direction for Farmer chamber was not good and is not comparable with other deconvoluted profiles. Conclusion: The results of the deconvoluted profiles for 0.125cc and Markus chamber was comparable and the deconvolution functionality can be used to overcome the volume averaging effect.« less

Application of an improved minimum entropy deconvolution method for railway rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Yao; Zhou, Ning; Zhang, Weihua; Wang, Zhiwei

2018-07-01

Minimum entropy deconvolution is a widely-used tool in machinery fault diagnosis, because it enhances the impulse component of the signal. The filter coefficients that greatly influence the performance of the minimum entropy deconvolution are calculated by an iterative procedure. This paper proposes an improved deconvolution method for the fault detection of rolling element bearings. The proposed method solves the filter coefficients by the standard particle swarm optimization algorithm, assisted by a generalized spherical coordinate transformation. When optimizing the filters performance for enhancing the impulses in fault diagnosis (namely, faulty rolling element bearings), the proposed method outperformed the classical minimum entropy deconvolution method. The proposed method was validated in simulation and experimental signals from railway bearings. In both simulation and experimental studies, the proposed method delivered better deconvolution performance than the classical minimum entropy deconvolution method, especially in the case of low signal-to-noise ratio.

Fast analytical spectral filtering methods for magnetic resonance perfusion quantification.

PubMed

Reddy, Kasireddy V; Mitra, Abhishek; Yalavarthy, Phaneendra K

2016-08-01

The deconvolution in the perfusion weighted imaging (PWI) plays an important role in quantifying the MR perfusion parameters. The PWI application to stroke and brain tumor studies has become a standard clinical practice. The standard approach for this deconvolution is oscillatory-limited singular value decomposition (oSVD) and frequency domain deconvolution (FDD). The FDD is widely recognized as the fastest approach currently available for deconvolution of MR perfusion data. In this work, two fast deconvolution methods (namely analytical fourier filtering and analytical showalter spectral filtering) are proposed. Through systematic evaluation, the proposed methods are shown to be computationally efficient and quantitatively accurate compared to FDD and oSVD.

Scalar flux modeling in turbulent flames using iterative deconvolution

NASA Astrophysics Data System (ADS)

Nikolaou, Z. M.; Cant, R. S.; Vervisch, L.

2018-04-01

In the context of large eddy simulations, deconvolution is an attractive alternative for modeling the unclosed terms appearing in the filtered governing equations. Such methods have been used in a number of studies for non-reacting and incompressible flows; however, their application in reacting flows is limited in comparison. Deconvolution methods originate from clearly defined operations, and in theory they can be used in order to model any unclosed term in the filtered equations including the scalar flux. In this study, an iterative deconvolution algorithm is used in order to provide a closure for the scalar flux term in a turbulent premixed flame by explicitly filtering the deconvoluted fields. The assessment of the method is conducted a priori using a three-dimensional direct numerical simulation database of a turbulent freely propagating premixed flame in a canonical configuration. In contrast to most classical a priori studies, the assessment is more stringent as it is performed on a much coarser mesh which is constructed using the filtered fields as obtained from the direct simulations. For the conditions tested in this study, deconvolution is found to provide good estimates both of the scalar flux and of its divergence.

Enhancing the performance of the light field microscope using wavefront coding.

PubMed

Cohen, Noy; Yang, Samuel; Andalman, Aaron; Broxton, Michael; Grosenick, Logan; Deisseroth, Karl; Horowitz, Mark; Levoy, Marc

2014-10-06

Light field microscopy has been proposed as a new high-speed volumetric computational imaging method that enables reconstruction of 3-D volumes from captured projections of the 4-D light field. Recently, a detailed physical optics model of the light field microscope has been derived, which led to the development of a deconvolution algorithm that reconstructs 3-D volumes with high spatial resolution. However, the spatial resolution of the reconstructions has been shown to be non-uniform across depth, with some z planes showing high resolution and others, particularly at the center of the imaged volume, showing very low resolution. In this paper, we enhance the performance of the light field microscope using wavefront coding techniques. By including phase masks in the optical path of the microscope we are able to address this non-uniform resolution limitation. We have also found that superior control over the performance of the light field microscope can be achieved by using two phase masks rather than one, placed at the objective's back focal plane and at the microscope's native image plane. We present an extended optical model for our wavefront coded light field microscope and develop a performance metric based on Fisher information, which we use to choose adequate phase masks parameters. We validate our approach using both simulated data and experimental resolution measurements of a USAF 1951 resolution target; and demonstrate the utility for biological applications with in vivo volumetric calcium imaging of larval zebrafish brain.

Deconvolution of continuous paleomagnetic data from pass-through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization

NASA Astrophysics Data System (ADS)

Oda, Hirokuni; Xuan, Chuang

2014-10-01

development of pass-through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long-core samples. The output of pass-through measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor response. Although several studies could restore high-resolution paleomagnetic signal through deconvolution of pass-through measurement, difficulties in accurately measuring the magnetometer sensor response have hindered the application of deconvolution. We acquired reliable sensor response of an SRM at the Oregon State University based on repeated measurements of a precisely fabricated magnetic point source. In addition, we present an improved deconvolution algorithm based on Akaike's Bayesian Information Criterion (ABIC) minimization, incorporating new parameters to account for errors in sample measurement position and length. The new algorithm was tested using synthetic data constructed by convolving "true" paleomagnetic signal containing an "excursion" with the sensor response. Realistic noise was added to the synthetic measurement using Monte Carlo method based on measurement noise distribution acquired from 200 repeated measurements of a u-channel sample. Deconvolution of 1000 synthetic measurements with realistic noise closely resembles the "true" magnetization, and successfully restored fine-scale magnetization variations including the "excursion." Our analyses show that inaccuracy in sample measurement position and length significantly affects deconvolution estimation, and can be resolved using the new deconvolution algorithm. Optimized deconvolution of 20 repeated measurements of a u-channel sample yielded highly consistent deconvolution results and estimates of error in sample measurement position and length, demonstrating the reliability of the new deconvolution algorithm for real pass-through measurements.

Optimized Deconvolution for Maximum Axial Resolution in Three-Dimensional Aberration-Corrected Scanning Transmission Electron Microscopy

PubMed Central

Ramachandra, Ranjan; de Jonge, Niels

2012-01-01

Three-dimensional (3D) data sets were recorded of gold nanoparticles placed on both sides of silicon nitride membranes using focal series aberration-corrected scanning transmission electron microscopy (STEM). The deconvolution of the 3D datasets was optimized to obtain the highest possible axial resolution. The deconvolution involved two different point spread function (PSF)s, each calculated iteratively via blind deconvolution.. Supporting membranes of different thicknesses were tested to study the effect of beam broadening on the deconvolution. It was found that several iterations of deconvolution was efficient in reducing the imaging noise. With an increasing number of iterations, the axial resolution was increased, and most of the structural information was preserved. Additional iterations improved the axial resolution by maximal a factor of 4 to 6, depending on the particular dataset, and up to 8 nm maximal, but at the cost of a reduction of the lateral size of the nanoparticles in the image. Thus, the deconvolution procedure optimized for highest axial resolution is best suited for applications where one is interested in the 3D locations of nanoparticles only. PMID:22152090

Enhancing the performance of the light field microscope using wavefront coding

PubMed Central

Cohen, Noy; Yang, Samuel; Andalman, Aaron; Broxton, Michael; Grosenick, Logan; Deisseroth, Karl; Horowitz, Mark; Levoy, Marc

2014-01-01

Light field microscopy has been proposed as a new high-speed volumetric computational imaging method that enables reconstruction of 3-D volumes from captured projections of the 4-D light field. Recently, a detailed physical optics model of the light field microscope has been derived, which led to the development of a deconvolution algorithm that reconstructs 3-D volumes with high spatial resolution. However, the spatial resolution of the reconstructions has been shown to be non-uniform across depth, with some z planes showing high resolution and others, particularly at the center of the imaged volume, showing very low resolution. In this paper, we enhance the performance of the light field microscope using wavefront coding techniques. By including phase masks in the optical path of the microscope we are able to address this non-uniform resolution limitation. We have also found that superior control over the performance of the light field microscope can be achieved by using two phase masks rather than one, placed at the objective’s back focal plane and at the microscope’s native image plane. We present an extended optical model for our wavefront coded light field microscope and develop a performance metric based on Fisher information, which we use to choose adequate phase masks parameters. We validate our approach using both simulated data and experimental resolution measurements of a USAF 1951 resolution target; and demonstrate the utility for biological applications with in vivo volumetric calcium imaging of larval zebrafish brain. PMID:25322056

A novel partial volume effects correction technique integrating deconvolution associated with denoising within an iterative PET image reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merlin, Thibaut, E-mail: thibaut.merlin@telecom-bretagne.eu; Visvikis, Dimitris; Fernandez, Philippe

2015-02-15

Purpose: Partial volume effect (PVE) plays an important role in both qualitative and quantitative PET image accuracy, especially for small structures. A previously proposed voxelwise PVE correction method applied on PET reconstructed images involves the use of Lucy–Richardson deconvolution incorporating wavelet-based denoising to limit the associated propagation of noise. The aim of this study is to incorporate the deconvolution, coupled with the denoising step, directly inside the iterative reconstruction process to further improve PVE correction. Methods: The list-mode ordered subset expectation maximization (OSEM) algorithm has been modified accordingly with the application of the Lucy–Richardson deconvolution algorithm to the current estimationmore » of the image, at each reconstruction iteration. Acquisitions of the NEMA NU2-2001 IQ phantom were performed on a GE DRX PET/CT system to study the impact of incorporating the deconvolution inside the reconstruction [with and without the point spread function (PSF) model] in comparison to its application postreconstruction and to standard iterative reconstruction incorporating the PSF model. The impact of the denoising step was also evaluated. Images were semiquantitatively assessed by studying the trade-off between the intensity recovery and the noise level in the background estimated as relative standard deviation. Qualitative assessments of the developed methods were additionally performed on clinical cases. Results: Incorporating the deconvolution without denoising within the reconstruction achieved superior intensity recovery in comparison to both standard OSEM reconstruction integrating a PSF model and application of the deconvolution algorithm in a postreconstruction process. The addition of the denoising step permitted to limit the SNR degradation while preserving the intensity recovery. Conclusions: This study demonstrates the feasibility of incorporating the Lucy–Richardson deconvolution associated with a wavelet-based denoising in the reconstruction process to better correct for PVE. Future work includes further evaluations of the proposed method on clinical datasets and the use of improved PSF models.« less

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

NASA Astrophysics Data System (ADS)

Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Improving ground-penetrating radar data in sedimentary rocks using deterministic deconvolution

USGS Publications Warehouse

Xia, J.; Franseen, E.K.; Miller, R.D.; Weis, T.V.; Byrnes, A.P.

2003-01-01

Resolution is key to confidently identifying unique geologic features using ground-penetrating radar (GPR) data. Source wavelet "ringing" (related to bandwidth) in a GPR section limits resolution because of wavelet interference, and can smear reflections in time and/or space. The resultant potential for misinterpretation limits the usefulness of GPR. Deconvolution offers the ability to compress the source wavelet and improve temporal resolution. Unlike statistical deconvolution, deterministic deconvolution is mathematically simple and stable while providing the highest possible resolution because it uses the source wavelet unique to the specific radar equipment. Source wavelets generated in, transmitted through and acquired from air allow successful application of deterministic approaches to wavelet suppression. We demonstrate the validity of using a source wavelet acquired in air as the operator for deterministic deconvolution in a field application using "400-MHz" antennas at a quarry site characterized by interbedded carbonates with shale partings. We collected GPR data on a bench adjacent to cleanly exposed quarry faces in which we placed conductive rods to provide conclusive groundtruth for this approach to deconvolution. The best deconvolution results, which are confirmed by the conductive rods for the 400-MHz antenna tests, were observed for wavelets acquired when the transmitter and receiver were separated by 0.3 m. Applying deterministic deconvolution to GPR data collected in sedimentary strata at our study site resulted in an improvement in resolution (50%) and improved spatial location (0.10-0.15 m) of geologic features compared to the same data processed without deterministic deconvolution. The effectiveness of deterministic deconvolution for increased resolution and spatial accuracy of specific geologic features is further demonstrated by comparing results of deconvolved data with nondeconvolved data acquired along a 30-m transect immediately adjacent to a fresh quarry face. The results at this site support using deterministic deconvolution, which incorporates the GPR instrument's unique source wavelet, as a standard part of routine GPR data processing. ?? 2003 Elsevier B.V. All rights reserved.

Toward optimal spatial and spectral quality in widefield infrared spectromicroscopy of IR labelled single cells.

PubMed

Mattson, Eric C; Unger, Miriam; Clède, Sylvain; Lambert, François; Policar, Clotilde; Imtiaz, Asher; D'Souza, Roshan; Hirschmugl, Carol J

2013-10-07

Advancements in widefield infrared spectromicroscopy have recently been demonstrated following the commissioning of IRENI (InfraRed ENvironmental Imaging), a Fourier Transform infrared (FTIR) chemical imaging beamline at the Synchrotron Radiation Center. The present study demonstrates the effects of magnification, spatial oversampling, spectral pre-processing and deconvolution, focusing on the intracellular detection and distribution of an exogenous metal tris-carbonyl derivative 1 in a single MDA-MB-231 breast cancer cell. We demonstrate here that spatial oversampling for synchrotron-based infrared imaging is critical to obtain accurate diffraction-limited images at all wavelengths simultaneously. Resolution criteria and results from raw and deconvoluted images for two Schwarzschild objectives (36×, NA 0.5 and 74×, NA 0.65) are compared to each other and to prior reports for raster-scanned, confocal microscopes. The resolution of the imaging data can be improved by deconvolving the instrumental broadening that is determined with the measured PSFs, which is implemented with GPU programming architecture for fast hyperspectral processing. High definition, rapidly acquired, FTIR chemical images of respective spectral signatures of the cell 1 and shows that 1 is localized next to the phosphate- and Amide-rich regions, in agreement with previous infrared and luminescence studies. The infrared image contrast, localization and definition are improved after applying proven spectral pre-processing (principal component analysis based noise reduction and RMie scattering correction algorithms) to individual pixel spectra in the hyperspectral cube.

Hybrid sparse blind deconvolution: an implementation of SOOT algorithm to real data

NASA Astrophysics Data System (ADS)

Pakmanesh, Parvaneh; Goudarzi, Alireza; Kourki, Meisam

2018-06-01

Getting information of seismic data depends on deconvolution as an important processing step; it provides the reflectivity series by signal compression. This compression can be obtained by removing the wavelet effects on the traces. The recently blind deconvolution has provided reliable performance for sparse signal recovery. In this study, two deconvolution methods have been implemented to the seismic data; the convolution of these methods provides a robust spiking deconvolution approach. This hybrid deconvolution is applied using the sparse deconvolution (MM algorithm) and the Smoothed-One-Over-Two algorithm (SOOT) in a chain. The MM algorithm is based on the minimization of the cost function defined by standards l1 and l2. After applying the two algorithms to the seismic data, the SOOT algorithm provided well-compressed data with a higher resolution than the MM algorithm. The SOOT algorithm requires initial values to be applied for real data, such as the wavelet coefficients and reflectivity series that can be achieved through the MM algorithm. The computational cost of the hybrid method is high, and it is necessary to be implemented on post-stack or pre-stack seismic data of complex structure regions.

Light field creating and imaging with different order intensity derivatives

NASA Astrophysics Data System (ADS)

Wang, Yu; Jiang, Huan

2014-10-01

Microscopic image restoration and reconstruction is a challenging topic in the image processing and computer vision, which can be widely applied to life science, biology and medicine etc. A microscopic light field creating and three dimensional (3D) reconstruction method is proposed for transparent or partially transparent microscopic samples, which is based on the Taylor expansion theorem and polynomial fitting. Firstly the image stack of the specimen is divided into several groups in an overlapping or non-overlapping way along the optical axis, and the first image of every group is regarded as reference image. Then different order intensity derivatives are calculated using all the images of every group and polynomial fitting method based on the assumption that the structure of the specimen contained by the image stack in a small range along the optical axis are possessed of smooth and linear property. Subsequently, new images located any position from which to reference image the distance is Δz along the optical axis can be generated by means of Taylor expansion theorem and the calculated different order intensity derivatives. Finally, the microscopic specimen can be reconstructed in 3D form using deconvolution technology and all the images including both the observed images and the generated images. The experimental results show the effectiveness and feasibility of our method.

Using deconvolution to improve the metrological performance of the grid method

NASA Astrophysics Data System (ADS)

Grédiac, Michel; Sur, Frédéric; Badulescu, Claudiu; Mathias, Jean-Denis

2013-06-01

The use of various deconvolution techniques to enhance strain maps obtained with the grid method is addressed in this study. Since phase derivative maps obtained with the grid method can be approximated by their actual counterparts convolved by the envelope of the kernel used to extract phases and phase derivatives, non-blind restoration techniques can be used to perform deconvolution. Six deconvolution techniques are presented and employed to restore a synthetic phase derivative map, namely direct deconvolution, regularized deconvolution, the Richardson-Lucy algorithm and Wiener filtering, the last two with two variants concerning their practical implementations. Obtained results show that the noise that corrupts the grid images must be thoroughly taken into account to limit its effect on the deconvolved strain maps. The difficulty here is that the noise on the grid image yields a spatially correlated noise on the strain maps. In particular, numerical experiments on synthetic data show that direct and regularized deconvolutions are unstable when noisy data are processed. The same remark holds when Wiener filtering is employed without taking into account noise autocorrelation. On the other hand, the Richardson-Lucy algorithm and Wiener filtering with noise autocorrelation provide deconvolved maps where the impact of noise remains controlled within a certain limit. It is also observed that the last technique outperforms the Richardson-Lucy algorithm. Two short examples of actual strain fields restoration are finally shown. They deal with asphalt and shape memory alloy specimens. The benefits and limitations of deconvolution are presented and discussed in these two cases. The main conclusion is that strain maps are correctly deconvolved when the signal-to-noise ratio is high and that actual noise in the actual strain maps must be more specifically characterized than in the current study to address higher noise levels with Wiener filtering.

Least-squares (LS) deconvolution of a series of overlapping cortical auditory evoked potentials: a simulation and experimental study

NASA Astrophysics Data System (ADS)

Bardy, Fabrice; Van Dun, Bram; Dillon, Harvey; Cowan, Robert

2014-08-01

Objective. To evaluate the viability of disentangling a series of overlapping ‘cortical auditory evoked potentials’ (CAEPs) elicited by different stimuli using least-squares (LS) deconvolution, and to assess the adaptation of CAEPs for different stimulus onset-asynchronies (SOAs). Approach. Optimal aperiodic stimulus sequences were designed by controlling the condition number of matrices associated with the LS deconvolution technique. First, theoretical considerations of LS deconvolution were assessed in simulations in which multiple artificial overlapping responses were recovered. Second, biological CAEPs were recorded in response to continuously repeated stimulus trains containing six different tone-bursts with frequencies 8, 4, 2, 1, 0.5, 0.25 kHz separated by SOAs jittered around 150 (120-185), 250 (220-285) and 650 (620-685) ms. The control condition had a fixed SOA of 1175 ms. In a second condition, using the same SOAs, trains of six stimuli were separated by a silence gap of 1600 ms. Twenty-four adults with normal hearing (<20 dB HL) were assessed. Main results. Results showed disentangling of a series of overlapping responses using LS deconvolution on simulated waveforms as well as on real EEG data. The use of rapid presentation and LS deconvolution did not however, allow the recovered CAEPs to have a higher signal-to-noise ratio than for slowly presented stimuli. The LS deconvolution technique enables the analysis of a series of overlapping responses in EEG. Significance. LS deconvolution is a useful technique for the study of adaptation mechanisms of CAEPs for closely spaced stimuli whose characteristics change from stimulus to stimulus. High-rate presentation is necessary to develop an understanding of how the auditory system encodes natural speech or other intrinsically high-rate stimuli.

Iterative and function-continuation Fourier deconvolution methods for enhancing mass spectrometer resolution

NASA Technical Reports Server (NTRS)

Ioup, J. W.; Ioup, G. E.; Rayborn, G. H., Jr.; Wood, G. M., Jr.; Upchurch, B. T.

1984-01-01

Mass spectrometer data in the form of ion current versus mass-to-charge ratio often include overlapping mass peaks, especially in low- and medium-resolution instruments. Numerical deconvolution of such data effectively enhances the resolution by decreasing the overlap of mass peaks. In this paper two approaches to deconvolution are presented: a function-domain iterative technique and a Fourier transform method which uses transform-domain function-continuation. Both techniques include data smoothing to reduce the sensitivity of the deconvolution to noise. The efficacy of these methods is demonstrated through application to representative mass spectrometer data and the deconvolved results are discussed and compared to data obtained from a spectrometer with sufficient resolution to achieve separation of the mass peaks studied. A case for which the deconvolution is seriously affected by Gibbs oscillations is analyzed.

Micron-scale roughness of volcanic surfaces from thermal infrared spectroscopy and scanning electron microscopy

NASA Astrophysics Data System (ADS)

Carter, Adam J.; Ramsey, Michael S.; Durant, Adam J.; Skilling, Ian P.; Wolfe, Amy

2009-02-01

Textural characteristics of recently emplaced volcanic materials provide information on the degassing history, volatile content, and future explosive activity of volcanoes. Thermal infrared (TIR) remote sensing has been used to derive the micron-scale roughness (i.e., surface vesicularity) of lavas using a two-component (glass plus blackbody) spectral deconvolution model. We apply and test this approach on TIR data of pyroclastic flow (PF) deposits for the first time. Samples from two PF deposits (January 2005: block-rich and March 2000: ash-rich) were collected at Bezymianny Volcano (Russia) and analyzed using (1) TIR emission spectroscopy, (2) scanning electron microscope (SEM)-derived roughness (profiling), (3) SEM-derived surface vesicularity (imaging), and (4) thin section observations. Results from SEM roughness (0.9-2.8 μm) and SEM vesicularity (18-26%) showed a positive correlation. These were compared to the deconvolution results from the laboratory and spaceborne spectra, as well as to field-derived percentages of the block and ash. The spaceborne results were within 5% of the laboratory results and showed a positive correlation. However, a negative correlation between the SEM and spectral results was observed and was likely due to a combination of factors; an incorrect glass end-member, particle size effects, and subsequent weathering/reworking of the PF deposits. Despite these differences, this work shows that microscopic textural heterogeneities on PF deposits can be detected with TIR remote sensing using a technique similar to that used for lavas, but the results must be carefully interpreted. If applied correctly, it could be an important tool to map recent PF deposits and infer the causative eruption style/mechanism.

Three-dimensional scanning transmission electron microscopy of biological specimens.

PubMed

de Jonge, Niels; Sougrat, Rachid; Northan, Brian M; Pennycook, Stephen J

2010-02-01

A three-dimensional (3D) reconstruction of the cytoskeleton and a clathrin-coated pit in mammalian cells has been achieved from a focal-series of images recorded in an aberration-corrected scanning transmission electron microscope (STEM). The specimen was a metallic replica of the biological structure comprising Pt nanoparticles 2-3 nm in diameter, with a high stability under electron beam radiation. The 3D dataset was processed by an automated deconvolution procedure. The lateral resolution was 1.1 nm, set by pixel size. Particles differing by only 10 nm in vertical position were identified as separate objects with greater than 20% dip in contrast between them. We refer to this value as the axial resolution of the deconvolution or reconstruction, the ability to recognize two objects, which were unresolved in the original dataset. The resolution of the reconstruction is comparable to that achieved by tilt-series transmission electron microscopy. However, the focal-series method does not require mechanical tilting and is therefore much faster. 3D STEM images were also recorded of the Golgi ribbon in conventional thin sections containing 3T3 cells with a comparable axial resolution in the deconvolved dataset.

Three-Dimensional Scanning Transmission Electron Microscopy of Biological Specimens

PubMed Central

de Jonge, Niels; Sougrat, Rachid; Northan, Brian M.; Pennycook, Stephen J.

2010-01-01

A three-dimensional (3D) reconstruction of the cytoskeleton and a clathrin-coated pit in mammalian cells has been achieved from a focal-series of images recorded in an aberration-corrected scanning transmission electron microscope (STEM). The specimen was a metallic replica of the biological structure comprising Pt nanoparticles 2–3 nm in diameter, with a high stability under electron beam radiation. The 3D dataset was processed by an automated deconvolution procedure. The lateral resolution was 1.1 nm, set by pixel size. Particles differing by only 10 nm in vertical position were identified as separate objects with greater than 20% dip in contrast between them. We refer to this value as the axial resolution of the deconvolution or reconstruction, the ability to recognize two objects, which were unresolved in the original dataset. The resolution of the reconstruction is comparable to that achieved by tilt-series transmission electron microscopy. However, the focal-series method does not require mechanical tilting and is therefore much faster. 3D STEM images were also recorded of the Golgi ribbon in conventional thin sections containing 3T3 cells with a comparable axial resolution in the deconvolved dataset. PMID:20082729

Blind source deconvolution for deep Earth seismology

NASA Astrophysics Data System (ADS)

Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.

2007-12-01

We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.

Gamma-Ray Simulated Spectrum Deconvolution of a LaBr₃ 1-in. x 1-in. Scintillator for Nondestructive ATR Fuel Burnup On-Site Predictions

DOE PAGES

Navarro, Jorge; Ring, Terry A.; Nigg, David W.

2015-03-01

A deconvolution method for a LaBr₃ 1"x1" detector for nondestructive Advanced Test Reactor (ATR) fuel burnup applications was developed. The method consisted of obtaining the detector response function, applying a deconvolution algorithm to 1”x1” LaBr₃ simulated, data along with evaluating the effects that deconvolution have on nondestructively determining ATR fuel burnup. The simulated response function of the detector was obtained using MCNPX as well with experimental data. The Maximum-Likelihood Expectation Maximization (MLEM) deconvolution algorithm was selected to enhance one-isotope source-simulated and fuel- simulated spectra. The final evaluation of the study consisted of measuring the performance of the fuel burnup calibrationmore » curve for the convoluted and deconvoluted cases. The methodology was developed in order to help design a reliable, high resolution, rugged and robust detection system for the ATR fuel canal capable of collecting high performance data for model validation, along with a system that can calculate burnup and using experimental scintillator detector data.« less

Volumetric bioimaging based on light field microscopy with temporal focusing illumination

NASA Astrophysics Data System (ADS)

Hsu, Feng-Chun; Sie, Yong Da; Lai, Feng-Jie; Chen, Shean-Jen

2018-02-01

Light field technique at a single shot can get the whole volume image of observed sample. Therefore, the original frame rate of the optical system can be taken as the volumetric image rate. For dynamically imaging whole micron-scale biosample, a light field microscope with temporal focusing illumination has been developed. In the light field microscope, the f-number of the microlens array (MLA) is adopted to match that of the objective; hence, the subimages via adjacent lenslets do not overlay each other. A three-dimensional (3D) deconvolution algorithm is utilized to deblur the out-of-focusing part. Conventional light field microscopy (LFM) illuminates whole volume sample even noninteresting parts; nevertheless, whole volume excitation causes even more damage on bio-sample and also increase the background noise from the out of range. Therefore, temporal focusing is integrated into the light field microscope for selecting the illumination volume. Herein, a slit on the back focal plane of the objective is utilized to control the axial excitation confinement for selecting the illumination volume. As a result, the developed light field microscope with the temporal focusing multiphoton illumination (TFMPI) can reconstruct 3D images within the selected volume, and the lateral resolution approaches to the theoretical value. Furthermore, the 3D Brownian motion of two-micron fluorescent beads is observed as the criterion of dynamic sample. With superior signal-to-noise ratio and less damage to tissue, the microscope is potential to provide volumetric imaging for vivo sample.

Application of deterministic deconvolution of ground-penetrating radar data in a study of carbonate strata

USGS Publications Warehouse

Xia, J.; Franseen, E.K.; Miller, R.D.; Weis, T.V.

2004-01-01

We successfully applied deterministic deconvolution to real ground-penetrating radar (GPR) data by using the source wavelet that was generated in and transmitted through air as the operator. The GPR data were collected with 400-MHz antennas on a bench adjacent to a cleanly exposed quarry face. The quarry site is characterized by horizontally bedded carbonate strata with shale partings. In order to provide groundtruth for this deconvolution approach, 23 conductive rods were drilled into the quarry face at key locations. The steel rods provided critical information for: (1) correlation between reflections on GPR data and geologic features exposed in the quarry face, (2) GPR resolution limits, (3) accuracy of velocities calculated from common midpoint data and (4) identifying any multiples. Comparing the results of deconvolved data with non-deconvolved data demonstrates the effectiveness of deterministic deconvolution in low dielectric-loss media for increased accuracy of velocity models (improved at least 10-15% in our study after deterministic deconvolution), increased vertical and horizontal resolution of specific geologic features and more accurate representation of geologic features as confirmed from detailed study of the adjacent quarry wall. ?? 2004 Elsevier B.V. All rights reserved.

Hybrid Imaging for Extended Depth of Field Microscopy

NASA Astrophysics Data System (ADS)

Zahreddine, Ramzi Nicholas

An inverse relationship exists in optical systems between the depth of field (DOF) and the minimum resolvable feature size. This trade-off is especially detrimental in high numerical aperture microscopy systems where resolution is pushed to the diffraction limit resulting in a DOF on the order of 500 nm. Many biological structures and processes of interest span over micron scales resulting in significant blurring during imaging. This thesis explores a two-step computational imaging technique known as hybrid imaging to create extended DOF (EDF) microscopy systems with minimal sacrifice in resolution. In the first step a mask is inserted at the pupil plane of the microscope to create a focus invariant system over 10 times the traditional DOF, albeit with reduced contrast. In the second step the contrast is restored via deconvolution. Several EDF pupil masks from the literature are quantitatively compared in the context of biological microscopy. From this analysis a new mask is proposed, the incoherently partitioned pupil with binary phase modulation (IPP-BPM), that combines the most advantageous properties from the literature. Total variation regularized deconvolution models are derived for the various noise conditions and detectors commonly used in biological microscopy. State of the art algorithms for efficiently solving the deconvolution problem are analyzed for speed, accuracy, and ease of use. The IPP-BPM mask is compared with the literature and shown to have the highest signal-to-noise ratio and lowest mean square error post-processing. A prototype of the IPP-BPM mask is fabricated using a combination of 3D femtosecond glass etching and standard lithography techniques. The mask is compared against theory and demonstrated in biological imaging applications.

Studing Regional Wave Source Time Functions Using A Massive Automated EGF Deconvolution Procedure

NASA Astrophysics Data System (ADS)

Xie, J. "; Schaff, D. P.

2010-12-01

Reliably estimated source time functions (STF) from high-frequency regional waveforms, such as Lg, Pn and Pg, provide important input for seismic source studies, explosion detection, and minimization of parameter trade-off in attenuation studies. The empirical Green’s function (EGF) method can be used for estimating STF, but it requires a strict recording condition. Waveforms from pairs of events that are similar in focal mechanism, but different in magnitude must be on-scale recorded on the same stations for the method to work. Searching for such waveforms can be very time consuming, particularly for regional waves that contain complex path effects and have reduced S/N ratios due to attenuation. We have developed a massive, automated procedure to conduct inter-event waveform deconvolution calculations from many candidate event pairs. The procedure automatically evaluates the “spikiness” of the deconvolutions by calculating their “sdc”, which is defined as the peak divided by the background value. The background value is calculated as the mean absolute value of the deconvolution, excluding 10 s around the source time function. When the sdc values are about 10 or higher, the deconvolutions are found to be sufficiently spiky (pulse-like), indicating similar path Green’s functions and good estimates of the STF. We have applied this automated procedure to Lg waves and full regional wavetrains from 989 M ≥ 5 events in and around China, calculating about a million deconvolutions. Of these we found about 2700 deconvolutions with sdc greater than 9, which, if having a sufficiently broad frequency band, can be used to estimate the STF of the larger events. We are currently refining our procedure, as well as the estimated STFs. We will infer the source scaling using the STFs. We will also explore the possibility that the deconvolution procedure could complement cross-correlation in a real time event-screening process.

Rapid perfusion quantification using Welch-Satterthwaite approximation and analytical spectral filtering

NASA Astrophysics Data System (ADS)

Krishnan, Karthik; Reddy, Kasireddy V.; Ajani, Bhavya; Yalavarthy, Phaneendra K.

2017-02-01

CT and MR perfusion weighted imaging (PWI) enable quantification of perfusion parameters in stroke studies. These parameters are calculated from the residual impulse response function (IRF) based on a physiological model for tissue perfusion. The standard approach for estimating the IRF is deconvolution using oscillatory-limited singular value decomposition (oSVD) or Frequency Domain Deconvolution (FDD). FDD is widely recognized as the fastest approach currently available for deconvolution of CT Perfusion/MR PWI. In this work, three faster methods are proposed. The first is a direct (model based) crude approximation to the final perfusion quantities (Blood flow, Blood volume, Mean Transit Time and Delay) using the Welch-Satterthwaite approximation for gamma fitted concentration time curves (CTC). The second method is a fast accurate deconvolution method, we call Analytical Fourier Filtering (AFF). The third is another fast accurate deconvolution technique using Showalter's method, we call Analytical Showalter's Spectral Filtering (ASSF). Through systematic evaluation on phantom and clinical data, the proposed methods are shown to be computationally more than twice as fast as FDD. The two deconvolution based methods, AFF and ASSF, are also shown to be quantitatively accurate compared to FDD and oSVD.

Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?

PubMed

Horger, Marius; Fallier-Becker, Petra; Thaiss, Wolfgang M; Sauter, Alexander; Bösmüller, Hans; Martella, Manuela; Preibsch, Heike; Fritz, Jan; Nikolaou, Konstantin; Kloth, Christopher

2018-05-03

This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics. Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28-74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m 2 ), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness. Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BF deconvolution (P = .047, r = 0.418) and additionally was significantly associated with higher mean BV deconvolution (P < .005). Mean k-trans Patlak correlated strongly with mean k-trans deconvolution (r = 0.939, P = .001), and both correlated with mean BF deconvolution (P = .001, r = 0.748), max BF deconvolution (P = .028, r = 0.564), mean BV deconvolution (P = .001, r = 0.752), and max BV deconvolution (P = .001, r = 0.771). Microvessel density correlated with max k-trans deconvolution (r = 0.564, P = .023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-trans Patlak (P = .041, r = 0.686) and mean BF deconvolution (P = .038, r = 0.695). k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Improving space debris detection in GEO ring using image deconvolution

NASA Astrophysics Data System (ADS)

Núñez, Jorge; Núñez, Anna; Montojo, Francisco Javier; Condominas, Marta

2015-07-01

In this paper we present a method based on image deconvolution to improve the detection of space debris, mainly in the geostationary ring. Among the deconvolution methods we chose the iterative Richardson-Lucy (R-L), as the method that achieves better goals with a reasonable amount of computation. For this work, we used two sets of real 4096 × 4096 pixel test images obtained with the Telescope Fabra-ROA at Montsec (TFRM). Using the first set of data, we establish the optimal number of iterations in 7, and applying the R-L method with 7 iterations to the images, we show that the astrometric accuracy does not vary significantly while the limiting magnitude of the deconvolved images increases significantly compared to the original ones. The increase is in average about 1.0 magnitude, which means that objects up to 2.5 times fainter can be detected after deconvolution. The application of the method to the second set of test images, which includes several faint objects, shows that, after deconvolution, up to four previously undetected faint objects are detected in a single frame. Finally, we carried out a study of some economic aspects of applying the deconvolution method, showing that an important economic impact can be envisaged.

Study of one- and two-dimensional filtering and deconvolution algorithms for a streaming array computer

NASA Technical Reports Server (NTRS)

Ioup, G. E.

1985-01-01

Appendix 5 of the Study of One- and Two-Dimensional Filtering and Deconvolution Algorithms for a Streaming Array Computer includes a resume of the professional background of the Principal Investigator on the project, lists of this publications and research papers, graduate thesis supervised, and grants received.

Thermoluminescence dosimetry properties of new Cu doped CaF(2) nanoparticles.

PubMed

Zahedifar, M; Sadeghi, E

2013-12-01

Nanoparticles of Cu-doped calcium fluoride were synthesised by using the hydrothermal method. The structure of the prepared nanomaterial was characterised by the X-ray diffraction (XRD) pattern and energy dispersive spectrometer. The particle size of 36 nm was calculated from the XRD data. Its shape and size were also observed by scanning electron microscope. Thermoluminescence (TL) and photoluminescence of the produced phosphor were also considered. The computerised glow curve deconvolution procedure was used to identify the number of glow peaks included in the TL glow curve of the CaF2:Cu nanoparticles. The TL glow curve contains two overlapping glow peaks at ∼413 and 451 K. The TL response of this phosphor was studied for different Cu concentrations and the maximum sensitivity was found at 1 mol% of Cu impurity. Other dosimetric characteristics of the synthesised nanophosphor are also presented and discussed.

Partial Deconvolution with Inaccurate Blur Kernel.

PubMed

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.

Intrinsic fluorescence spectroscopy of glutamate dehydrogenase: Integrated behavior and deconvolution analysis

NASA Astrophysics Data System (ADS)

Pompa, P. P.; Cingolani, R.; Rinaldi, R.

2003-07-01

In this paper, we present a deconvolution method aimed at spectrally resolving the broad fluorescence spectra of proteins, namely, of the enzyme bovine liver glutamate dehydrogenase (GDH). The analytical procedure is based on the deconvolution of the emission spectra into three distinct Gaussian fluorescing bands Gj. The relative changes of the Gj parameters are directly related to the conformational changes of the enzyme, and provide interesting information about the fluorescence dynamics of the individual emitting contributions. Our deconvolution method results in an excellent fitting of all the spectra obtained with GDH in a number of experimental conditions (various conformational states of the protein) and describes very well the dynamics of a variety of phenomena, such as the dependence of hexamers association on protein concentration, the dynamics of thermal denaturation, and the interaction process between the enzyme and external quenchers. The investigation was carried out by means of different optical experiments, i.e., native enzyme fluorescence, thermal-induced unfolding, and fluorescence quenching studies, utilizing both the analysis of the “average” behavior of the enzyme and the proposed deconvolution approach.

Real-time restoration of white-light confocal microscope optical sections

PubMed Central

Balasubramanian, Madhusudhanan; Iyengar, S. Sitharama; Beuerman, Roger W.; Reynaud, Juan; Wolenski, Peter

2009-01-01

Confocal microscopes (CM) are routinely used for building 3-D images of microscopic structures. Nonideal imaging conditions in a white-light CM introduce additive noise and blur. The optical section images need to be restored prior to quantitative analysis. We present an adaptive noise filtering technique using Karhunen–Loéve expansion (KLE) by the method of snapshots and a ringing metric to quantify the ringing artifacts introduced in the images restored at various iterations of iterative Lucy–Richardson deconvolution algorithm. The KLE provides a set of basis functions that comprise the optimal linear basis for an ensemble of empirical observations. We show that most of the noise in the scene can be removed by reconstructing the images using the KLE basis vector with the largest eigenvalue. The prefiltering scheme presented is faster and does not require prior knowledge about image noise. Optical sections processed using the KLE prefilter can be restored using a simple inverse restoration algorithm; thus, the methodology is suitable for real-time image restoration applications. The KLE image prefilter outperforms the temporal-average prefilter in restoring CM optical sections. The ringing metric developed uses simple binary morphological operations to quantify the ringing artifacts and confirms with the visual observation of ringing artifacts in the restored images. PMID:20186290

Deconvolution method for accurate determination of overlapping peak areas in chromatograms.

PubMed

Nelson, T J

1991-12-20

A method is described for deconvoluting chromatograms which contain overlapping peaks. Parameters can be selected to ensure that attenuation of peak areas is uniform over any desired range of peak widths. A simple extension of the method greatly reduces the negative overshoot frequently encountered with deconvolutions. The deconvoluted chromatograms are suitable for integration by conventional methods.

Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image

NASA Astrophysics Data System (ADS)

He, Xingwu; You, Junchen

2018-03-01

Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.

UDECON: deconvolution optimization software for restoring high-resolution records from pass-through paleomagnetic measurements

NASA Astrophysics Data System (ADS)

Xuan, Chuang; Oda, Hirokuni

2015-11-01

The rapid accumulation of continuous paleomagnetic and rock magnetic records acquired from pass-through measurements on superconducting rock magnetometers (SRM) has greatly contributed to our understanding of the paleomagnetic field and paleo-environment. Pass-through measurements are inevitably smoothed and altered by the convolution effect of SRM sensor response, and deconvolution is needed to restore high-resolution paleomagnetic and environmental signals. Although various deconvolution algorithms have been developed, the lack of easy-to-use software has hindered the practical application of deconvolution. Here, we present standalone graphical software UDECON as a convenient tool to perform optimized deconvolution for pass-through paleomagnetic measurements using the algorithm recently developed by Oda and Xuan (Geochem Geophys Geosyst 15:3907-3924, 2014). With the preparation of a format file, UDECON can directly read pass-through paleomagnetic measurement files collected at different laboratories. After the SRM sensor response is determined and loaded to the software, optimized deconvolution can be conducted using two different approaches (i.e., "Grid search" and "Simplex method") with adjustable initial values or ranges for smoothness, corrections of sample length, and shifts in measurement position. UDECON provides a suite of tools to view conveniently and check various types of original measurement and deconvolution data. Multiple steps of measurement and/or deconvolution data can be compared simultaneously to check the consistency and to guide further deconvolution optimization. Deconvolved data together with the loaded original measurement and SRM sensor response data can be saved and reloaded for further treatment in UDECON. Users can also export the optimized deconvolution data to a text file for analysis in other software.

Evaluation of deconvolution modelling applied to numerical combustion

NASA Astrophysics Data System (ADS)

Mehl, Cédric; Idier, Jérôme; Fiorina, Benoît

2018-01-01

A possible modelling approach in the large eddy simulation (LES) of reactive flows is to deconvolve resolved scalars. Indeed, by inverting the LES filter, scalars such as mass fractions are reconstructed. This information can be used to close budget terms of filtered species balance equations, such as the filtered reaction rate. Being ill-posed in the mathematical sense, the problem is very sensitive to any numerical perturbation. The objective of the present study is to assess the ability of this kind of methodology to capture the chemical structure of premixed flames. For that purpose, three deconvolution methods are tested on a one-dimensional filtered laminar premixed flame configuration: the approximate deconvolution method based on Van Cittert iterative deconvolution, a Taylor decomposition-based method, and the regularised deconvolution method based on the minimisation of a quadratic criterion. These methods are then extended to the reconstruction of subgrid scale profiles. Two methodologies are proposed: the first one relies on subgrid scale interpolation of deconvolved profiles and the second uses parametric functions to describe small scales. Conducted tests analyse the ability of the method to capture the chemical filtered flame structure and front propagation speed. Results show that the deconvolution model should include information about small scales in order to regularise the filter inversion. a priori and a posteriori tests showed that the filtered flame propagation speed and structure cannot be captured if the filter size is too large.

Confocal Raman spectroscopic analysis of cross-linked ultra-high molecular weight polyethylene for application in artificial hip joints.

PubMed

Pezzotti, Giuseppe; Kumakura, Tsuyoshi; Yamada, Kiyotaka; Tateiwa, Toshiyuki; Puppulin, Leonardo; Zhu, Wenliang; Yamamoto, Kengo

2007-01-01

Confocal spectroscopic techniques are applied to selected Raman bands to study the microscopic features of acetabular cups made of ultra-high molecular weight polyethylene (UHMWPE) before and after implantation in vivo. The micrometric lateral resolution of a laser beam focused on the polymeric surface (or subsurface) enables a highly resolved visualization of 2-D conformational population patterns, including crystalline, amorphous, orthorhombic phase fractions, and oxidation index. An optimized confocal probe configuration, aided by a computational deconvolution of the optical probe, allows minimization of the probe size along the in-depth direction and a nondestructive evaluation of microstructural properties along the material subsurface. Computational deconvolution is also attempted, based on an experimental assessment of the probe response function of the polyethylene Raman spectrum, according to a defocusing technique. A statistical set of high-resolution microstructural data are collected on a fully 3-D level on gamma-ray irradiated UHMWPE acetabular cups both as-received from the maker and after retrieval from a human body. Microstructural properties reveal significant gradients along the immediate material subsurface and distinct differences are found due to the loading history in vivo, which cannot be revealed by conventional optical spectroscopy. The applicability of the confocal spectroscopic technique is valid beyond the particular retrieval cases examined in this study, and can be easily extended to evaluate in-vitro tested components or to quality control of new polyethylene brands. Confocal Raman spectroscopy may also contribute to rationalize the complex effects of gamma-ray irradiation on the surface of medical grade UHMWPE for total joint replacement and, ultimately, to predict their actual lifetime in vivo.

A neural network approach for the blind deconvolution of turbulent flows

NASA Astrophysics Data System (ADS)

Maulik, R.; San, O.

2017-11-01

We present a single-layer feedforward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse grained computations such as those encountered in large eddy simulations. We stress that the deconvolution procedure proposed in this investigation is blind, i.e. the deconvolved field is computed without any pre-existing information about the filtering procedure or kernel. This may be conceptually contrasted to the celebrated approximate deconvolution approaches where a filter shape is predefined for an iterative deconvolution process. We demonstrate that the proposed blind deconvolution network performs exceptionally well in the a-priori testing of both two-dimensional Kraichnan and three-dimensional Kolmogorov turbulence and shows promise in forming the backbone of a physics-augmented data-driven closure for the Navier-Stokes equations.

Waveform LiDAR processing: comparison of classic approaches and optimized Gold deconvolution to characterize vegetation structure and terrain elevation

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.

2016-12-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: 1) direct decomposition, 2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from discrete LiDAR data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, < 0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, < 1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (< 1.01m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE.

Crowded field photometry with deconvolved images.

NASA Astrophysics Data System (ADS)

Linde, P.; Spännare, S.

A local implementation of the Lucy-Richardson algorithm has been used to deconvolve a set of crowded stellar field images. The effects of deconvolution on detection limits as well as on photometric and astrometric properties have been investigated as a function of the number of deconvolution iterations. Results show that deconvolution improves detection of faint stars, although artifacts are also found. Deconvolution provides more stars measurable without significant degradation of positional accuracy. The photometric precision is affected by deconvolution in several ways. Errors due to unresolved images are notably reduced, while flux redistribution between stars and background increases the errors.

Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection

NASA Astrophysics Data System (ADS)

McDonald, Geoff L.; Zhao, Qing

2017-01-01

Minimum Entropy Deconvolution (MED) has been applied successfully to rotating machine fault detection from vibration data, however this method has limitations. A convolution adjustment to the MED definition and solution is proposed in this paper to address the discontinuity at the start of the signal - in some cases causing spurious impulses to be erroneously deconvolved. A problem with the MED solution is that it is an iterative selection process, and will not necessarily design an optimal filter for the posed problem. Additionally, the problem goal in MED prefers to deconvolve a single-impulse, while in rotating machine faults we expect one impulse-like vibration source per rotational period of the faulty element. Maximum Correlated Kurtosis Deconvolution was proposed to address some of these problems, and although it solves the target goal of multiple periodic impulses, it is still an iterative non-optimal solution to the posed problem and only solves for a limited set of impulses in a row. Ideally, the problem goal should target an impulse train as the output goal, and should directly solve for the optimal filter in a non-iterative manner. To meet these goals, we propose a non-iterative deconvolution approach called Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA). MOMEDA proposes a deconvolution problem with an infinite impulse train as the goal and the optimal filter solution can be solved for directly. From experimental data on a gearbox with and without a gear tooth chip, we show that MOMEDA and its deconvolution spectrums according to the period between the impulses can be used to detect faults and study the health of rotating machine elements effectively.

Automatic layer segmentation of H&E microscopic images of mice skin

NASA Astrophysics Data System (ADS)

Hussein, Saif; Selway, Joanne; Jassim, Sabah; Al-Assam, Hisham

2016-05-01

Mammalian skin is a complex organ composed of a variety of cells and tissue types. The automatic detection and quantification of changes in skin structures has a wide range of applications for biological research. To accurately segment and quantify nuclei, sebaceous gland, hair follicles, and other skin structures, there is a need for a reliable segmentation of different skin layers. This paper presents an efficient segmentation algorithm to segment the three main layers of mice skin, namely epidermis, dermis, and subcutaneous layers. It also segments the epidermis layer into two sub layers, basal and cornified layers. The proposed algorithm uses adaptive colour deconvolution technique on H&E stain images to separate different tissue structures, inter-modes and Otsu thresholding techniques were effectively combined to segment the layers. It then uses a set of morphological and logical operations on each layer to removing unwanted objects. A dataset of 7000 H&E microscopic images of mutant and wild type mice were used to evaluate the effectiveness of the algorithm. Experimental results examined by domain experts have confirmed the viability of the proposed algorithms.

Two-Photon Excitation STED Microscopy with Time-Gated Detection

PubMed Central

Coto Hernández, Iván; Castello, Marco; Lanzanò, Luca; d’Amora, Marta; Bianchini, Paolo; Diaspro, Alberto; Vicidomini, Giuseppe

2016-01-01

We report on a novel two-photon excitation stimulated emission depletion (2PE-STED) microscope based on time-gated detection. The time-gated detection allows for the effective silencing of the fluorophores using moderate stimulated emission beam intensity. This opens the possibility of implementing an efficient 2PE-STED microscope with a stimulated emission beam running in a continuous-wave. The continuous-wave stimulated emission beam tempers the laser architecture’s complexity and cost, but the time-gated detection degrades the signal-to-noise ratio (SNR) and signal-to-background ratio (SBR) of the image. We recover the SNR and the SBR through a multi-image deconvolution algorithm. Indeed, the algorithm simultaneously reassigns early-photons (normally discarded by the time-gated detection) to their original positions and removes the background induced by the stimulated emission beam. We exemplify the benefits of this implementation by imaging sub-cellular structures. Finally, we discuss of the extension of this algorithm to future all-pulsed 2PE-STED implementationd based on time-gated detection and a nanosecond laser source. PMID:26757892

Correction for frequency-dependent hydrophone response to nonlinear pressure waves using complex deconvolution and rarefactional filtering: application with fiber optic hydrophones.

PubMed

Wear, Keith; Liu, Yunbo; Gammell, Paul M; Maruvada, Subha; Harris, Gerald R

2015-01-01

Nonlinear acoustic signals contain significant energy at many harmonic frequencies. For many applications, the sensitivity (frequency response) of a hydrophone will not be uniform over such a broad spectrum. In a continuation of a previous investigation involving deconvolution methodology, deconvolution (implemented in the frequency domain as an inverse filter computed from frequency-dependent hydrophone sensitivity) was investigated for improvement of accuracy and precision of nonlinear acoustic output measurements. Timedelay spectrometry was used to measure complex sensitivities for 6 fiber-optic hydrophones. The hydrophones were then used to measure a pressure wave with rich harmonic content. Spectral asymmetry between compressional and rarefactional segments was exploited to design filters used in conjunction with deconvolution. Complex deconvolution reduced mean bias (for 6 fiber-optic hydrophones) from 163% to 24% for peak compressional pressure (p+), from 113% to 15% for peak rarefactional pressure (p-), and from 126% to 29% for pulse intensity integral (PII). Complex deconvolution reduced mean coefficient of variation (COV) (for 6 fiber optic hydrophones) from 18% to 11% (p+), 53% to 11% (p-), and 20% to 16% (PII). Deconvolution based on sensitivity magnitude or the minimum phase model also resulted in significant reductions in mean bias and COV of acoustic output parameters but was less effective than direct complex deconvolution for p+ and p-. Therefore, deconvolution with appropriate filtering facilitates reliable nonlinear acoustic output measurements using hydrophones with frequency-dependent sensitivity.

The Small-scale Structure of Photospheric Convection Retrieved by a Deconvolution Technique Applied to Hinode/SP Data

NASA Astrophysics Data System (ADS)

Oba, T.; Riethmüller, T. L.; Solanki, S. K.; Iida, Y.; Quintero Noda, C.; Shimizu, T.

2017-11-01

Solar granules are bright patterns surrounded by dark channels, called intergranular lanes, in the solar photosphere and are a manifestation of overshooting convection. Observational studies generally find stronger upflows in granules and weaker downflows in intergranular lanes. This trend is, however, inconsistent with the results of numerical simulations in which downflows are stronger than upflows through the joint action of gravitational acceleration/deceleration and pressure gradients. One cause of this discrepancy is the image degradation caused by optical distortion and light diffraction and scattering that takes place in an imaging instrument. We apply a deconvolution technique to Hinode/SP data in an attempt to recover the original solar scene. Our results show a significant enhancement in both the convective upflows and downflows but particularly for the latter. After deconvolution, the up- and downflows reach maximum amplitudes of -3.0 km s-1 and +3.0 km s-1 at an average geometrical height of roughly 50 km, respectively. We found that the velocity distributions after deconvolution match those derived from numerical simulations. After deconvolution, the net LOS velocity averaged over the whole field of view lies close to zero as expected in a rough sense from mass balance.

Sub-diffraction Limit Localization of Proteins in Volumetric Space Using Bayesian Restoration of Fluorescence Images from Ultrathin Specimens

PubMed Central

Wang, Gordon; Smith, Stephen J.

2012-01-01

Photon diffraction limits the resolution of conventional light microscopy at the lateral focal plane to 0.61λ/NA (λ = wavelength of light, NA = numerical aperture of the objective) and at the axial plane to 1.4nλ/NA2 (n = refractive index of the imaging medium, 1.51 for oil immersion), which with visible wavelengths and a 1.4NA oil immersion objective is ∼220 nm and ∼600 nm in the lateral plane and axial plane respectively. This volumetric resolution is too large for the proper localization of protein clustering in subcellular structures. Here we combine the newly developed proteomic imaging technique, Array Tomography (AT), with its native 50–100 nm axial resolution achieved by physical sectioning of resin embedded tissue, and a 2D maximum likelihood deconvolution method, based on Bayes' rule, which significantly improves the resolution of protein puncta in the lateral plane to allow accurate and fast computational segmentation and analysis of labeled proteins. The physical sectioning of AT allows tissue specimens to be imaged at the physical optimum of modern high NA plan-apochormatic objectives. This translates to images that have little out of focus light, minimal aberrations and wave-front distortions. Thus, AT is able to provide images with truly invariant point spread functions (PSF), a property critical for accurate deconvolution. We show that AT with deconvolution increases the volumetric analytical fidelity of protein localization by significantly improving the modulation of high spatial frequencies up to and potentially beyond the spatial frequency cut-off of the objective. Moreover, we are able to achieve this improvement with no noticeable introduction of noise or artifacts and arrive at object segmentation and localization accuracies on par with image volumes captured using commercial implementations of super-resolution microscopes. PMID:22956902

Sub-diffraction limit localization of proteins in volumetric space using Bayesian restoration of fluorescence images from ultrathin specimens.

PubMed

Wang, Gordon; Smith, Stephen J

2012-01-01

Photon diffraction limits the resolution of conventional light microscopy at the lateral focal plane to 0.61λ/NA (λ = wavelength of light, NA = numerical aperture of the objective) and at the axial plane to 1.4nλ/NA(2) (n = refractive index of the imaging medium, 1.51 for oil immersion), which with visible wavelengths and a 1.4NA oil immersion objective is -220 nm and -600 nm in the lateral plane and axial plane respectively. This volumetric resolution is too large for the proper localization of protein clustering in subcellular structures. Here we combine the newly developed proteomic imaging technique, Array Tomography (AT), with its native 50-100 nm axial resolution achieved by physical sectioning of resin embedded tissue, and a 2D maximum likelihood deconvolution method, based on Bayes' rule, which significantly improves the resolution of protein puncta in the lateral plane to allow accurate and fast computational segmentation and analysis of labeled proteins. The physical sectioning of AT allows tissue specimens to be imaged at the physical optimum of modern high NA plan-apochormatic objectives. This translates to images that have little out of focus light, minimal aberrations and wave-front distortions. Thus, AT is able to provide images with truly invariant point spread functions (PSF), a property critical for accurate deconvolution. We show that AT with deconvolution increases the volumetric analytical fidelity of protein localization by significantly improving the modulation of high spatial frequencies up to and potentially beyond the spatial frequency cut-off of the objective. Moreover, we are able to achieve this improvement with no noticeable introduction of noise or artifacts and arrive at object segmentation and localization accuracies on par with image volumes captured using commercial implementations of super-resolution microscopes.

Gold - A novel deconvolution algorithm with optimization for waveform LiDAR processing

NASA Astrophysics Data System (ADS)

Zhou, Tan; Popescu, Sorin C.; Krause, Keith; Sheridan, Ryan D.; Putman, Eric

2017-07-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: (1) direct decomposition, (2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson-Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from the corresponding reference data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, <0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, <1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (<1.01 m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE. Additionally, the high level of uncertainty occurs more on areas with high slope and high vegetation. This study provides an alternative and innovative approach for waveform processing that will benefit high fidelity processing of waveform LiDAR data to characterize vegetation structures.

A feasibility and optimization study to determine cooling time and burnup of advanced test reactor fuels using a nondestructive technique

NASA Astrophysics Data System (ADS)

Navarro, Jorge

The goal of this study presented is to determine the best available nondestructive technique necessary to collect validation data as well as to determine burnup and cooling time of the fuel elements on-site at the Advanced Test Reactor (ATR) canal. This study makes a recommendation of the viability of implementing a permanent fuel scanning system at the ATR canal and leads to the full design of a permanent fuel scan system. The study consisted at first in determining if it was possible and which equipment was necessary to collect useful spectra from ATR fuel elements at the canal adjacent to the reactor. Once it was establish that useful spectra can be obtained at the ATR canal, the next step was to determine which detector and which configuration was better suited to predict burnup and cooling time of fuel elements nondestructively. Three different detectors of High Purity Germanium (HPGe), Lanthanum Bromide (LaBr3), and High Pressure Xenon (HPXe) in two system configurations of above and below the water pool were used during the study. The data collected and analyzed were used to create burnup and cooling time calibration prediction curves for ATR fuel. The next stage of the study was to determine which of the three detectors tested was better suited for the permanent system. From spectra taken and the calibration curves obtained, it was determined that although the HPGe detector yielded better results, a detector that could better withstand the harsh environment of the ATR canal was needed. The in-situ nature of the measurements required a rugged fuel scanning system, low in maintenance and easy to control system. Based on the ATR canal feasibility measurements and calibration results, it was determined that the LaBr3 detector was the best alternative for canal in-situ measurements; however, in order to enhance the quality of the spectra collected using this scintillator, a deconvolution method was developed. Following the development of the deconvolution method for ATR applications, the technique was tested using one-isotope, multi-isotope, and fuel simulated sources. Burnup calibrations were perfomed using convoluted and deconvoluted data. The calibrations results showed burnup prediction by this method improves using deconvolution. The final stage of the deconvolution method development was to perform an irradiation experiment in order to create a surrogate fuel source to test the deconvolution method using experimental data. A conceptual design of the fuel scan system is path forward using the rugged LaBr 3 detector in an above the water configuration and deconvolution algorithms.

Light-sheet microscopy for everyone? Experience of building an OpenSPIM to study flatworm development.

PubMed

Girstmair, Johannes; Zakrzewski, Anne; Lapraz, François; Handberg-Thorsager, Mette; Tomancak, Pavel; Pitrone, Peter Gabriel; Simpson, Fraser; Telford, Maximilian J

2016-06-30

Selective plane illumination microscopy (SPIM a type of light-sheet microscopy) involves focusing a thin sheet of laser light through a specimen at right angles to the objective lens. As only the thin section of the specimen at the focal plane of the lens is illuminated, out of focus light is naturally absent and toxicity due to light (phototoxicity) is greatly reduced enabling longer term live imaging. OpenSPIM is an open access platform (Pitrone et al. 2013 and OpenSPIM.org) created to give new users step-by-step instructions on building a basic configuration of a SPIM microscope, which can in principle be adapted and upgraded to each laboratory's own requirements and budget. Here we describe our own experience with the process of designing, building, configuring and using an OpenSPIM for our research into the early development of the polyclad flatworm Maritigrella crozieri - a non-model animal. Our OpenSPIM builds on the standard design with the addition of two colour laser illumination for simultaneous detection of two probes/molecules and dual sided illumination, which provides more even signal intensity across a specimen. Our OpenSPIM provides high resolution 3d images and time lapse recordings, and we demonstrate the use of two colour lasers and the benefits of two color dual-sided imaging. We used our microscope to study the development of the embryo of the polyclad flatworm M. crozieri. The capabilities of our microscope are demonstrated by our ability to record the stereotypical spiral cleavage pattern of M. crozieri with high-speed multi-view time lapse imaging. 3D and 4D (3D + time) reconstruction of early development from these data is possible using image registration and deconvolution tools provided as part of the open source Fiji platform. We discuss our findings on the pros and cons of a self built microscope. We conclude that home-built microscopes, such as an OpenSPIM, together with the available open source software, such as MicroManager and Fiji, make SPIM accessible to anyone interested in having continuous access to their own light-sheet microscope. However, building an OpenSPIM is not without challenges and an open access microscope is a worthwhile, if significant, investment of time and money. Multi-view 4D microscopy is more challenging than we had expected. We hope that our experience gained during this project will help future OpenSPIM users with similar ambitions.

An adaptive sparse deconvolution method for distinguishing the overlapping echoes of ultrasonic guided waves for pipeline crack inspection

NASA Astrophysics Data System (ADS)

Chang, Yong; Zi, Yanyang; Zhao, Jiyuan; Yang, Zhe; He, Wangpeng; Sun, Hailiang

2017-03-01

In guided wave pipeline inspection, echoes reflected from closely spaced reflectors generally overlap, meaning useful information is lost. To solve the overlapping problem, sparse deconvolution methods have been developed in the past decade. However, conventional sparse deconvolution methods have limitations in handling guided wave signals, because the input signal is directly used as the prototype of the convolution matrix, without considering the waveform change caused by the dispersion properties of the guided wave. In this paper, an adaptive sparse deconvolution (ASD) method is proposed to overcome these limitations. First, the Gaussian echo model is employed to adaptively estimate the column prototype of the convolution matrix instead of directly using the input signal as the prototype. Then, the convolution matrix is constructed upon the estimated results. Third, the split augmented Lagrangian shrinkage (SALSA) algorithm is introduced to solve the deconvolution problem with high computational efficiency. To verify the effectiveness of the proposed method, guided wave signals obtained from pipeline inspection are investigated numerically and experimentally. Compared to conventional sparse deconvolution methods, e.g. the {{l}1} -norm deconvolution method, the proposed method shows better performance in handling the echo overlap problem in the guided wave signal.

Application of Fourier-wavelet regularized deconvolution for improving image quality of free space propagation x-ray phase contrast imaging.

PubMed

Zhou, Zhongxing; Gao, Feng; Zhao, Huijuan; Zhang, Lixin

2012-11-21

New x-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the negative effects of finite source size and limited spatial resolution. These negative effects swamp the fine phase contrast fringes and make them almost undetectable. In order to alleviate this problem, deconvolution procedures should be applied to the blurred x-ray phase contrast images. In this study, three different deconvolution techniques, including Wiener filtering, Tikhonov regularization and Fourier-wavelet regularized deconvolution (ForWaRD), were applied to the simulated and experimental free space propagation x-ray phase contrast images of simple geometric phantoms. These algorithms were evaluated in terms of phase contrast improvement and signal-to-noise ratio. The results demonstrate that the ForWaRD algorithm is most appropriate for phase contrast image restoration among above-mentioned methods; it can effectively restore the lost information of phase contrast fringes while reduce the amplified noise during Fourier regularization.

The Small-scale Structure of Photospheric Convection Retrieved by a Deconvolution Technique Applied to Hinode /SP Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oba, T.; Riethmüller, T. L.; Solanki, S. K.

Solar granules are bright patterns surrounded by dark channels, called intergranular lanes, in the solar photosphere and are a manifestation of overshooting convection. Observational studies generally find stronger upflows in granules and weaker downflows in intergranular lanes. This trend is, however, inconsistent with the results of numerical simulations in which downflows are stronger than upflows through the joint action of gravitational acceleration/deceleration and pressure gradients. One cause of this discrepancy is the image degradation caused by optical distortion and light diffraction and scattering that takes place in an imaging instrument. We apply a deconvolution technique to Hinode /SP data inmore » an attempt to recover the original solar scene. Our results show a significant enhancement in both the convective upflows and downflows but particularly for the latter. After deconvolution, the up- and downflows reach maximum amplitudes of −3.0 km s{sup −1} and +3.0 km s{sup −1} at an average geometrical height of roughly 50 km, respectively. We found that the velocity distributions after deconvolution match those derived from numerical simulations. After deconvolution, the net LOS velocity averaged over the whole field of view lies close to zero as expected in a rough sense from mass balance.« less

Processing strategy for water-gun seismic data from the Gulf of Mexico

USGS Publications Warehouse

Lee, Myung W.; Hart, Patrick E.; Agena, Warren F.

2000-01-01

In order to study the regional distribution of gas hydrates and their potential relationship to a large-scale sea-fl oor failures, more than 1,300 km of near-vertical-incidence seismic profi les were acquired using a 15-in3 water gun across the upper- and middle-continental slope in the Garden Banks and Green Canyon regions of the Gulf of Mexico. Because of the highly mixed phase water-gun signature, caused mainly by a precursor of the source arriving about 18 ms ahead of the main pulse, a conventional processing scheme based on the minimum phase assumption is not suitable for this data set. A conventional processing scheme suppresses the reverberations and compresses the main pulse, but the failure to suppress precursors results in complex interference between the precursors and primary refl ections, thus obscuring true refl ections. To clearly image the subsurface without interference from the precursors, a wavelet deconvolution based on the mixedphase assumption using variable norm is attempted. This nonminimum- phase wavelet deconvolution compresses a longwave- train water-gun signature into a simple zero-phase wavelet. A second-zero-crossing predictive deconvolution followed by a wavelet deconvolution suppressed variable ghost arrivals attributed to the variable depths of receivers. The processing strategy of using wavelet deconvolution followed by a secondzero- crossing deconvolution resulted in a sharp and simple wavelet and a better defi nition of the polarity of refl ections. Also, the application of dip moveout correction enhanced lateral resolution of refl ections and substantially suppressed coherent noise.

What do you gain from deconvolution? - Observing faint galaxies with the Hubble Space Telescope Wide Field Camera

NASA Technical Reports Server (NTRS)

Schade, David J.; Elson, Rebecca A. W.

1993-01-01

We describe experiments with deconvolutions of simulations of deep HST Wide Field Camera images containing faint, compact galaxies to determine under what circumstances there is a quantitative advantage to image deconvolution, and explore whether it is (1) helpful for distinguishing between stars and compact galaxies, or between spiral and elliptical galaxies, and whether it (2) improves the accuracy with which characteristic radii and integrated magnitudes may be determined. The Maximum Entropy and Richardson-Lucy deconvolution algorithms give the same results. For medium and low S/N images, deconvolution does not significantly improve our ability to distinguish between faint stars and compact galaxies, nor between spiral and elliptical galaxies. Measurements from both raw and deconvolved images are biased and must be corrected; it is easier to quantify and remove the biases for cases that have not been deconvolved. We find no benefit from deconvolution for measuring luminosity profiles, but these results are limited to low S/N images of very compact (often undersampled) galaxies.

Post-processing of adaptive optics images based on frame selection and multi-frame blind deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Changhui; Wei, Kai

2008-07-01

The adaptive optics can only partially compensate the image blurred by atmospheric turbulence due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frames blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are suitable for blind deconvolution from the recorded AO close-loop frames series are selected by the frame selection technique and then do the multi-frame blind deconvolution. There is no priori knowledge except for the positive constraint in blind deconvolution. It is benefit for the use of multi-frame images to improve the stability and convergence of the blind deconvolution algorithm. The method had been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system at Yunnan Observatory. The results show that the method can effectively improve the images partially corrected by adaptive optics.

Single-Ion Deconvolution of Mass Peak Overlaps for Atom Probe Microscopy.

PubMed

London, Andrew J; Haley, Daniel; Moody, Michael P

2017-04-01

Due to the intrinsic evaporation properties of the material studied, insufficient mass-resolving power and lack of knowledge of the kinetic energy of incident ions, peaks in the atom probe mass-to-charge spectrum can overlap and result in incorrect composition measurements. Contributions to these peak overlaps can be deconvoluted globally, by simply examining adjacent peaks combined with knowledge of natural isotopic abundances. However, this strategy does not account for the fact that the relative contributions to this convoluted signal can often vary significantly in different regions of the analysis volume; e.g., across interfaces and within clusters. Some progress has been made with spatially localized deconvolution in cases where the discrete microstructural regions can be easily identified within the reconstruction, but this means no further point cloud analyses are possible. Hence, we present an ion-by-ion methodology where the identity of each ion, normally obscured by peak overlap, is resolved by examining the isotopic abundance of their immediate surroundings. The resulting peak-deconvoluted data are a point cloud and can be analyzed with any existing tools. We present two detailed case studies and discussion of the limitations of this new technique.

Evaluation of uncertainty for regularized deconvolution: A case study in hydrophone measurements.

PubMed

Eichstädt, S; Wilkens, V

2017-06-01

An estimation of the measurand in dynamic metrology usually requires a deconvolution based on a dynamic calibration of the measuring system. Since deconvolution is, mathematically speaking, an ill-posed inverse problem, some kind of regularization is required to render the problem stable and obtain usable results. Many approaches to regularized deconvolution exist in the literature, but the corresponding evaluation of measurement uncertainties is, in general, an unsolved issue. In particular, the uncertainty contribution of the regularization itself is a topic of great importance, because it has a significant impact on the estimation result. Here, a versatile approach is proposed to express prior knowledge about the measurand based on a flexible, low-dimensional modeling of an upper bound on the magnitude spectrum of the measurand. This upper bound allows the derivation of an uncertainty associated with the regularization method in line with the guidelines in metrology. As a case study for the proposed method, hydrophone measurements in medical ultrasound with an acoustic working frequency of up to 7.5 MHz are considered, but the approach is applicable for all kinds of estimation methods in dynamic metrology, where regularization is required and which can be expressed as a multiplication in the frequency domain.

Deconvolution of the role of metal and pH in metal coordinating polymers

NASA Astrophysics Data System (ADS)

Cazzell, Seth; Holten-Andersen, Niels

Nature uses metal binding amino acids to engineer both mechanical properties and structural functionality. Some examples of this metal binding behavior can be found in both mussel foot protein and DNA binding protein. The mussel byssal thread contains reversible intermolecular protein-metal bonds, allowing it to withstand harsh intertidal environments. Zinc fingers form intramolecular protein-metal bonds to stabilize the tertiary structure of DNA binding proteins, allowing specific structural functionality. Inspired by both these metal-binding materials, we present mechanical and spectroscopic characterization of a model polymer system, designed to mimic this bonding. Through these studies, we are able to answer fundamental polymer physics questions, such as the role of pH and metal to ligand ratio, illuminating both the macroscopic and microscopic material behavior. These understandings further bio-inspired engineering techniques that are used to design viscoelastic soft materials. I was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Liquid chromatography with diode array detection combined with spectral deconvolution for the analysis of some diterpene esters in Arabica coffee brew.

PubMed

Erny, Guillaume L; Moeenfard, Marzieh; Alves, Arminda

2015-02-01

In this manuscript, the separation of kahweol and cafestol esters from Arabica coffee brews was investigated using liquid chromatography with a diode array detector. When detected in conjunction, cafestol, and kahweol esters were eluted together, but, after optimization, the kahweol esters could be selectively detected by setting the wavelength at 290 nm to allow their quantification. Such an approach was not possible for the cafestol esters, and spectral deconvolution was used to obtain deconvoluted chromatograms. In each of those chromatograms, the four esters were baseline separated allowing for the quantification of the eight targeted compounds. Because kahweol esters could be quantified either using the chromatogram obtained by setting the wavelength at 290 nm or using the deconvoluted chromatogram, those compounds were used to compare the analytical performances. Slightly better limits of detection were obtained using the deconvoluted chromatogram. Identical concentrations were found in a real sample with both approaches. The peak areas in the deconvoluted chromatograms were repeatable (intraday repeatability of 0.8%, interday repeatability of 1.0%). This work demonstrates the accuracy of spectral deconvolution when using liquid chromatography to mathematically separate coeluting compounds using the full spectra recorded by a diode array detector. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computerized glow curve deconvolution of thermoluminescent emission from polyminerals of Jamaica Mexican flower

NASA Astrophysics Data System (ADS)

Favalli, A.; Furetta, C.; Zaragoza, E. Cruz; Reyes, A.

The aim of this work is to study the main thermoluminescence (TL) characteristics of the inorganic polyminerals extracted from dehydrated Jamaica flower or roselle (Hibiscus sabdariffa L.) belonging to Malvaceae family of Mexican origin. TL emission properties of the polymineral fraction in powder were studied using the initial rise (IR) method. The complex structure and kinetic parameters of the glow curves have been analysed accurately using the computerized glow curve deconvolution (CGCD) assuming an exponential distribution of trapping levels. The extension of the IR method to the case of a continuous and exponential distribution of traps is reported, such as the derivation of the TL glow curve deconvolution functions for continuous trap distribution. CGCD is performed both in the case of frequency factor, s, temperature independent, and in the case with the s function of temperature.

Thermoluminescent response of LiF:Mg,Ti to 20 keV electrons.

PubMed

Mercado-Uribe, H; Brandan, M E

2002-01-01

The thermoluminescence response of LiF:Mg,Ti (TLD-100) to 20 keV electrons from a scanning electron microscope has been measured. Radiochromic dye films previously calibrated were used to determine the fluence incident on TLD-100 chips. The procedure for irradiation and glow curve deconvolution was adhered to the protocols previously determined in our laboratory for gamma rays and heavy charged particles. The response at electron fluences higher than 4 x 10(10) cm(-2) is supralinear, due to the increasingly relevant contribution of the high temperature peaks. The relative contribution of the high temperature peaks to the TL signal is abnormally small, about half that observed in gamma irradiation and four times smaller than what has been measured in low-energy X ray exposure.

A feasibility and optimization study to determine cooling time and burnup of advanced test reactor fuels using a nondestructive technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Navarro, Jorge

2013-12-01

The goal of this study presented is to determine the best available non-destructive technique necessary to collect validation data as well as to determine burn-up and cooling time of the fuel elements onsite at the Advanced Test Reactor (ATR) canal. This study makes a recommendation of the viability of implementing a permanent fuel scanning system at the ATR canal and leads3 to the full design of a permanent fuel scan system. The study consisted at first in determining if it was possible and which equipment was necessary to collect useful spectra from ATR fuel elements at the canal adjacent tomore » the reactor. Once it was establish that useful spectra can be obtained at the ATR canal the next step was to determine which detector and which configuration was better suited to predict burnup and cooling time of fuel elements non-destructively. Three different detectors of High Purity Germanium (HPGe), Lanthanum Bromide (LaBr3), and High Pressure Xenon (HPXe) in two system configurations of above and below the water pool were used during the study. The data collected and analyzed was used to create burnup and cooling time calibration prediction curves for ATR fuel. The next stage of the study was to determine which of the three detectors tested was better suited for the permanent system. From spectra taken and the calibration curves obtained, it was determined that although the HPGe detector yielded better results, a detector that could better withstand the harsh environment of the ATR canal was needed. The in-situ nature of the measurements required a rugged fuel scanning system, low in maintenance and easy to control system. Based on the ATR canal feasibility measurements and calibration results it was determined that the LaBr3 detector was the best alternative for canal in-situ measurements; however in order to enhance the quality of the spectra collected using this scintillator a deconvolution method was developed. Following the development of the deconvolution method for ATR applications the technique was tested using one-isotope, multi-isotope and fuel simulated sources. Burnup calibrations were perfomed using convoluted and deconvoluted data. The calibrations results showed burnup prediction by this method improves using deconvolution. The final stage of the deconvolution method development was to perform an irradiation experiment in order to create a surrogate fuel source to test the deconvolution method using experimental data. A conceptual design of the fuel scan system is path forward using the rugged LaBr3 detector in an above the water configuration and deconvolution algorithms.« less

Seismic interferometry by multidimensional deconvolution as a means to compensate for anisotropic illumination

NASA Astrophysics Data System (ADS)

Wapenaar, K.; van der Neut, J.; Ruigrok, E.; Draganov, D.; Hunziker, J.; Slob, E.; Thorbecke, J.; Snieder, R.

2008-12-01

It is well-known that under specific conditions the crosscorrelation of wavefields observed at two receivers yields the impulse response between these receivers. This principle is known as 'Green's function retrieval' or 'seismic interferometry'. Recently it has been recognized that in many situations it can be advantageous to replace the correlation process by deconvolution. One of the advantages is that deconvolution compensates for the waveform emitted by the source; another advantage is that it is not necessary to assume that the medium is lossless. The approaches that have been developed to date employ a 1D deconvolution process. We propose a method for seismic interferometry by multidimensional deconvolution and show that under specific circumstances the method compensates for irregularities in the source distribution. This is an important difference with crosscorrelation methods, which rely on the condition that waves are equipartitioned. This condition is for example fulfilled when the sources are regularly distributed along a closed surface and the power spectra of the sources are identical. The proposed multidimensional deconvolution method compensates for anisotropic illumination, without requiring knowledge about the positions and the spectra of the sources.

SOURCE PULSE ENHANCEMENT BY DECONVOLUTION OF AN EMPIRICAL GREEN'S FUNCTION.

USGS Publications Warehouse

Mueller, Charles S.

1985-01-01

Observations of the earthquake source-time function are enhanced if path, recording-site, and instrument complexities can be removed from seismograms. Assuming that a small earthquake has a simple source, its seismogram can be treated as an empirical Green's function and deconvolved from the seismogram of a larger and/or more complex earthquake by spectral division. When the deconvolution is well posed, the quotient spectrum represents the apparent source-time function of the larger event. This study shows that with high-quality locally recorded earthquake data it is feasible to Fourier transform the quotient and obtain a useful result in the time domain. In practice, the deconvolution can be stabilized by one of several simple techniques. Application of the method is given. Refs.

Deconvolution of time series in the laboratory

NASA Astrophysics Data System (ADS)

John, Thomas; Pietschmann, Dirk; Becker, Volker; Wagner, Christian

2016-10-01

In this study, we present two practical applications of the deconvolution of time series in Fourier space. First, we reconstruct a filtered input signal of sound cards that has been heavily distorted by a built-in high-pass filter using a software approach. Using deconvolution, we can partially bypass the filter and extend the dynamic frequency range by two orders of magnitude. Second, we construct required input signals for a mechanical shaker in order to obtain arbitrary acceleration waveforms, referred to as feedforward control. For both situations, experimental and theoretical approaches are discussed to determine the system-dependent frequency response. Moreover, for the shaker, we propose a simple feedback loop as an extension to the feedforward control in order to handle nonlinearities of the system.

Chloroform induces outstanding crystallization of poly(hydroxybutyrate) (PHB) vesicles within bacteria.

PubMed

Rebois, Rolando; Onidas, Delphine; Marcott, Curtis; Noda, Isao; Dazzi, Alexandre

2017-03-01

Poly[(R)-3-hydroxyalkanoate]s or PHAs are aliphatic polyesters produced by numerous microorganisms. They are accumulated as energy and carbon reserve in the form of small intracellular vesicles. Poly[(R)-3-hydroxybutyrate] (PHB) is the most ubiquitous and simplest PHA. An atomic force microscope coupled with a tunable infrared laser (AFM-IR) was used to record highly spatially resolved infrared spectra of commercial purified PHB and native PHB within bacteria. For the first time, the crystallinity degree of native PHB within vesicle has been directly evaluated in situ without alteration due to the measure or extraction and purification steps of the polymer: native PHB is in crystalline state at 15% whereas crystallinity degree reaches 57% in commercial PHB. Chloroform addition on native PHB induces crystallization of the polymer within bacteria up to 60%. This possibility of probing and changing the physical state of polymer in situ could open alternative ways of production for PHB and others biopolymers. Graphical abstract An atomic force microscope coupled with a tunable infrared laser (AFM-IR) has been used to record local infrared spectra of biopolymer PHB within bacteria. Deconvolution of those spectra has allowed to determine in situ the crystallinity degree of native PHB.

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL).

PubMed

Koestler, Devin C; Jones, Meaghan J; Usset, Joseph; Christensen, Brock C; Butler, Rondi A; Kobor, Michael S; Wiencke, John K; Kelsey, Karl T

2016-03-08

Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogenous biospecimens offer a promising solution, however the performance of such methods depends entirely on the library of methylation markers being used for deconvolution. Here, we introduce a novel algorithm for Identifying Optimal Libraries (IDOL) that dynamically scans a candidate set of cell-specific methylation markers to find libraries that optimize the accuracy of cell fraction estimates obtained from cell mixture deconvolution. Application of IDOL to training set consisting of samples with both whole-blood DNA methylation data (Illumina HumanMethylation450 BeadArray (HM450)) and flow cytometry measurements of cell composition revealed an optimized library comprised of 300 CpG sites. When compared existing libraries, the library identified by IDOL demonstrated significantly better overall discrimination of the entire immune cell landscape (p = 0.038), and resulted in improved discrimination of 14 out of the 15 pairs of leukocyte subtypes. Estimates of cell composition across the samples in the training set using the IDOL library were highly correlated with their respective flow cytometry measurements, with all cell-specific R (2)>0.99 and root mean square errors (RMSEs) ranging from [0.97 % to 1.33 %] across leukocyte subtypes. Independent validation of the optimized IDOL library using two additional HM450 data sets showed similarly strong prediction performance, with all cell-specific R (2)>0.90 and R M S E<4.00 %. In simulation studies, adjustments for cell composition using the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, while also demonstrating an improved capacity to explain epigenome-wide variation in DNA methylation within two large publicly available HM450 data sets. Despite consisting of half as many CpGs compared to existing libraries for whole blood mixture deconvolution, the optimized IDOL library identified herein resulted in outstanding prediction performance across all considered data sets and demonstrated potential to improve the operating characteristics of EWAS involving adjustments for cell distribution. In addition to providing the EWAS community with an optimized library for whole blood mixture deconvolution, our work establishes a systematic and generalizable framework for the assembly of libraries that improve the accuracy of cell mixture deconvolution.

Parsimonious Charge Deconvolution for Native Mass Spectrometry

PubMed Central

2018-01-01

Charge deconvolution infers the mass from mass over charge (m/z) measurements in electrospray ionization mass spectra. When applied over a wide input m/z or broad target mass range, charge-deconvolution algorithms can produce artifacts, such as false masses at one-half or one-third of the correct mass. Indeed, a maximum entropy term in the objective function of MaxEnt, the most commonly used charge deconvolution algorithm, favors a deconvolved spectrum with many peaks over one with fewer peaks. Here we describe a new “parsimonious” charge deconvolution algorithm that produces fewer artifacts. The algorithm is especially well-suited to high-resolution native mass spectrometry of intact glycoproteins and protein complexes. Deconvolution of native mass spectra poses special challenges due to salt and small molecule adducts, multimers, wide mass ranges, and fewer and lower charge states. We demonstrate the performance of the new deconvolution algorithm on a range of samples. On the heavily glycosylated plasma properdin glycoprotein, the new algorithm could deconvolve monomer and dimer simultaneously and, when focused on the m/z range of the monomer, gave accurate and interpretable masses for glycoforms that had previously been analyzed manually using m/z peaks rather than deconvolved masses. On therapeutic antibodies, the new algorithm facilitated the analysis of extensions, truncations, and Fab glycosylation. The algorithm facilitates the use of native mass spectrometry for the qualitative and quantitative analysis of protein and protein assemblies. PMID:29376659

Broadband ion mobility deconvolution for rapid analysis of complex mixtures.

PubMed

Pettit, Michael E; Brantley, Matthew R; Donnarumma, Fabrizio; Murray, Kermit K; Solouki, Touradj

2018-05-04

High resolving power ion mobility (IM) allows for accurate characterization of complex mixtures in high-throughput IM mass spectrometry (IM-MS) experiments. We previously demonstrated that pure component IM-MS data can be extracted from IM unresolved post-IM/collision-induced dissociation (CID) MS data using automated ion mobility deconvolution (AIMD) software [Matthew Brantley, Behrooz Zekavat, Brett Harper, Rachel Mason, and Touradj Solouki, J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. In our previous reports, we utilized a quadrupole ion filter for m/z-isolation of IM unresolved monoisotopic species prior to post-IM/CID MS. Here, we utilize a broadband IM-MS deconvolution strategy to remove the m/z-isolation requirement for successful deconvolution of IM unresolved peaks. Broadband data collection has throughput and multiplexing advantages; hence, elimination of the ion isolation step reduces experimental run times and thus expands the applicability of AIMD to high-throughput bottom-up proteomics. We demonstrate broadband IM-MS deconvolution of two separate and unrelated pairs of IM unresolved isomers (viz., a pair of isomeric hexapeptides and a pair of isomeric trisaccharides) in a simulated complex mixture. Moreover, we show that broadband IM-MS deconvolution improves high-throughput bottom-up characterization of a proteolytic digest of rat brain tissue. To our knowledge, this manuscript is the first to report successful deconvolution of pure component IM and MS data from an IM-assisted data-independent analysis (DIA) or HDMSE dataset.

Calculation of the static in-flight telescope-detector response by deconvolution applied to point-spread function for the geostationary earth radiation budget experiment.

PubMed

Matthews, Grant

2004-12-01

The Geostationary Earth Radiation Budget (GERB) experiment is a broadband satellite radiometer instrument program intended to resolve remaining uncertainties surrounding the effect of cloud radiative feedback on future climate change. By use of a custom-designed diffraction-aberration telescope model, the GERB detector spatial response is recovered by deconvolution applied to the ground calibration point-spread function (PSF) measurements. An ensemble of randomly generated white-noise test scenes, combined with the measured telescope transfer function results in the effect of noise on the deconvolution being significantly reduced. With the recovered detector response as a base, the same model is applied in construction of the predicted in-flight field-of-view response of each GERB pixel to both short- and long-wave Earth radiance. The results of this study can now be used to simulate and investigate the instantaneous sampling errors incurred by GERB. Also, the developed deconvolution method may be highly applicable in enhancing images or PSF data for any telescope system for which a wave-front error measurement is available.

Nimbus 7 earth radiation budget wide field of view climate data set improvement. I - The earth albedo from deconvolution of shortwave measurements

NASA Technical Reports Server (NTRS)

Hucek, Richard R.; Ardanuy, Philip E.; Kyle, H. Lee

1987-01-01

A deconvolution method for extracting the top of the atmosphere (TOA) mean, daily albedo field from a set of wide-FOV (WFOV) shortwave radiometer measurements is proposed. The method is based on constructing a synthetic measurement for each satellite observation. The albedo field is represented as a truncated series of spherical harmonic functions, and these linear equations are presented. Simulation studies were conducted to determine the sensitivity of the method. It is observed that a maximum of about 289 pieces of data can be extracted from a set of Nimbus 7 WFOV satellite measurements. The albedos derived using the deconvolution method are compared with albedos derived using the WFOV archival method; the developed albedo field achieved a 20 percent reduction in the global rms regional reflected flux density errors. The deconvolution method is applied to estimate the mean, daily average TOA albedo field for January 1983. A strong and extensive albedo maximum (0.42), which corresponds to the El Nino/Southern Oscillation event of 1982-1983, is detected over the south central Pacific Ocean.

Wave optics theory and 3-D deconvolution for the light field microscope

PubMed Central

Broxton, Michael; Grosenick, Logan; Yang, Samuel; Cohen, Noy; Andalman, Aaron; Deisseroth, Karl; Levoy, Marc

2013-01-01

Light field microscopy is a new technique for high-speed volumetric imaging of weakly scattering or fluorescent specimens. It employs an array of microlenses to trade off spatial resolution against angular resolution, thereby allowing a 4-D light field to be captured using a single photographic exposure without the need for scanning. The recorded light field can then be used to computationally reconstruct a full volume. In this paper, we present an optical model for light field microscopy based on wave optics, instead of previously reported ray optics models. We also present a 3-D deconvolution method for light field microscopy that is able to reconstruct volumes at higher spatial resolution, and with better optical sectioning, than previously reported. To accomplish this, we take advantage of the dense spatio-angular sampling provided by a microlens array at axial positions away from the native object plane. This dense sampling permits us to decode aliasing present in the light field to reconstruct high-frequency information. We formulate our method as an inverse problem for reconstructing the 3-D volume, which we solve using a GPU-accelerated iterative algorithm. Theoretical limits on the depth-dependent lateral resolution of the reconstructed volumes are derived. We show that these limits are in good agreement with experimental results on a standard USAF 1951 resolution target. Finally, we present 3-D reconstructions of pollen grains that demonstrate the improvements in fidelity made possible by our method. PMID:24150383

Cryo X-ray microscope with flat sample geometry for correlative fluorescence and nanoscale tomographic imaging.

PubMed

Schneider, Gerd; Guttmann, Peter; Rehbein, Stefan; Werner, Stephan; Follath, Rolf

2012-02-01

X-ray imaging offers a new 3-D view into cells. With its ability to penetrate whole hydrated cells it is ideally suited for pairing fluorescence light microscopy and nanoscale X-ray tomography. In this paper, we describe the X-ray optical set-up and the design of the cryo full-field transmission X-ray microscope (TXM) at the electron storage ring BESSY II. Compared to previous TXM set-ups with zone plate condenser monochromator, the new X-ray optical layout employs an undulator source, a spherical grating monochromator and an elliptically shaped glass capillary mirror as condenser. This set-up improves the spectral resolution by an order of magnitude. Furthermore, the partially coherent object illumination improves the contrast transfer of the microscope compared to incoherent conditions. With the new TXM, cells grown on flat support grids can be tilted perpendicular to the optical axis without any geometrical restrictions by the previously required pinhole for the zone plate monochromator close to the sample plane. We also developed an incorporated fluorescence light microscope which permits to record fluorescence, bright field and DIC images of cryogenic cells inside the TXM. For TXM tomography, imaging with multi-keV X-rays is a straightforward approach to increase the depth of focus. Under these conditions phase contrast imaging is necessary. For soft X-rays with shrinking depth of focus towards 10nm spatial resolution, thin optical sections through a thick specimen might be obtained by deconvolution X-ray microscopy. As alternative 3-D X-ray imaging techniques, the confocal cryo-STXM and the dual beam cryo-FIB/STXM with photoelectron detection are proposed. Copyright © 2012 Elsevier Inc. All rights reserved.

Two-Dimensional Signal Processing and Storage and Theory and Applications of Electromagnetic Measurements.

DTIC Science & Technology

1983-06-01

system, provides a convenient, low- noise , fully parallel method of improving contrast and enhancing structural detail in an image prior to input to a...directed towards problems in deconvolution, reconstruction from projections, bandlimited extrapolation, and shift varying deblurring of images...deconvolution algorithm has been studied with promising 5 results [I] for simulated motion blurs. Future work will focus on noise effects and the extension

Minimum entropy deconvolution and blind equalisation

NASA Technical Reports Server (NTRS)

Satorius, E. H.; Mulligan, J. J.

1992-01-01

Relationships between minimum entropy deconvolution, developed primarily for geophysics applications, and blind equalization are pointed out. It is seen that a large class of existing blind equalization algorithms are directly related to the scale-invariant cost functions used in minimum entropy deconvolution. Thus the extensive analyses of these cost functions can be directly applied to blind equalization, including the important asymptotic results of Donoho.

Interpretation of high resolution airborne magnetic data (HRAMD) of Ilesha and its environs, Southwest Nigeria, using Euler deconvolution method

NASA Astrophysics Data System (ADS)

Olurin, Oluwaseun Tolutope

2017-12-01

Interpretation of high resolution aeromagnetic data of Ilesha and its environs within the basement complex of the geological setting of Southwestern Nigeria was carried out in the study. The study area is delimited by geographic latitudes 7°30'-8°00'N and longitudes 4°30'-5°00'E. This investigation was carried out using Euler deconvolution on filtered digitised total magnetic data (Sheet Number 243) to delineate geological structures within the area under consideration. The digitised airborne magnetic data acquired in 2009 were obtained from the archives of the Nigeria Geological Survey Agency (NGSA). The airborne magnetic data were filtered, processed and enhanced; the resultant data were subjected to qualitative and quantitative magnetic interpretation, geometry and depth weighting analyses across the study area using Euler deconvolution filter control file in Oasis Montag software. Total magnetic intensity distribution in the field ranged from -77.7 to 139.7 nT. Total magnetic field intensities reveal high-magnitude magnetic intensity values (high-amplitude anomaly) and magnetic low intensities (low-amplitude magnetic anomaly) in the area under consideration. The study area is characterised with high intensity correlated with lithological variation in the basement. The sharp contrast is enhanced due to the sharp contrast in magnetic intensity between the magnetic susceptibilities of the crystalline and sedimentary rocks. The reduced-to-equator (RTE) map is characterised by high frequencies, short wavelengths, small size, weak intensity, sharp low amplitude and nearly irregular shaped anomalies, which may due to near-surface sources, such as shallow geologic units and cultural features. Euler deconvolution solution indicates a generally undulating basement, with a depth ranging from -500 to 1000 m. The Euler deconvolution results show that the basement relief is generally gentle and flat, lying within the basement terrain.

Sparse Solution of Fiber Orientation Distribution Function by Diffusion Decomposition

PubMed Central

Yeh, Fang-Cheng; Tseng, Wen-Yih Isaac

2013-01-01

Fiber orientation is the key information in diffusion tractography. Several deconvolution methods have been proposed to obtain fiber orientations by estimating a fiber orientation distribution function (ODF). However, the L 2 regularization used in deconvolution often leads to false fibers that compromise the specificity of the results. To address this problem, we propose a method called diffusion decomposition, which obtains a sparse solution of fiber ODF by decomposing the diffusion ODF obtained from q-ball imaging (QBI), diffusion spectrum imaging (DSI), or generalized q-sampling imaging (GQI). A simulation study, a phantom study, and an in-vivo study were conducted to examine the performance of diffusion decomposition. The simulation study showed that diffusion decomposition was more accurate than both constrained spherical deconvolution and ball-and-sticks model. The phantom study showed that the angular error of diffusion decomposition was significantly lower than those of constrained spherical deconvolution at 30° crossing and ball-and-sticks model at 60° crossing. The in-vivo study showed that diffusion decomposition can be applied to QBI, DSI, or GQI, and the resolved fiber orientations were consistent regardless of the diffusion sampling schemes and diffusion reconstruction methods. The performance of diffusion decomposition was further demonstrated by resolving crossing fibers on a 30-direction QBI dataset and a 40-direction DSI dataset. In conclusion, diffusion decomposition can improve angular resolution and resolve crossing fibers in datasets with low SNR and substantially reduced number of diffusion encoding directions. These advantages may be valuable for human connectome studies and clinical research. PMID:24146772

Gaussian and linear deconvolution of LC-MS/MS chromatograms of the eight aminobutyric acid isomers

PubMed Central

Vemula, Harika; Kitase, Yukiko; Ayon, Navid J.; Bonewald, Lynda; Gutheil, William G.

2016-01-01

Isomeric molecules present a challenge for analytical resolution and quantification, even with MS-based detection. The eight-aminobutyric acid (ABA) isomers are of interest for their various biological activities, particularly γ-aminobutyric acid (GABA) and the d- and l-isomers of β-aminoisobutyric acid (β-AIBA; BAIBA). This study aimed to investigate LC-MS/MS-based resolution of these ABA isomers as their Marfey's (Mar) reagent derivatives. HPLC was able to separate three Mar-ABA isomers l-β-ABA (l-BABA), and l- and d-α-ABA (AABA) completely, with three isomers (GABA, and d/l-BAIBA) in one chromatographic cluster, and two isomers (α-AIBA (AAIBA) and d-BABA) in a second cluster. Partially separated cluster components were deconvoluted using Gaussian peak fitting except for GABA and d-BAIBA. MS/MS detection of Marfey's derivatized ABA isomers provided six MS/MS fragments, with substantially different intensity profiles between structural isomers. This allowed linear deconvolution of ABA isomer peaks. Combining HPLC separation with linear and Gaussian deconvolution allowed resolution of all eight ABA isomers. Application to human serum found a substantial level of l-AABA (13 μM), an intermediate level of l-BAIBA (0.8 μM), and low but detectable levels (<0.2 μM) of GABA, l-BABA, AAIBA, d-BAIBA, and d-AABA. This approach should be useful for LC-MS/MS deconvolution of other challenging groups of isomeric molecules. PMID:27771391

Seismic interferometry by crosscorrelation and by multidimensional deconvolution: a systematic comparison

NASA Astrophysics Data System (ADS)

Wapenaar, Kees; van der Neut, Joost; Ruigrok, Elmer; Draganov, Deyan; Hunziker, Juerg; Slob, Evert; Thorbecke, Jan; Snieder, Roel

2010-05-01

In recent years, seismic interferometry (or Green's function retrieval) has led to many applications in seismology (exploration, regional and global), underwater acoustics and ultrasonics. One of the explanations for this broad interest lies in the simplicity of the methodology. In passive data applications a simple crosscorrelation of responses at two receivers gives the impulse response (Green's function) at one receiver as if there were a source at the position of the other. In controlled-source applications the procedure is similar, except that it involves in addition a summation along the sources. It has also been recognized that the simple crosscorrelation approach has its limitations. From the various theoretical models it follows that there are a number of underlying assumptions for retrieving the Green's function by crosscorrelation. The most important assumptions are that the medium is lossless and that the waves are equipartitioned. In heuristic terms the latter condition means that the receivers are illuminated isotropically from all directions, which is for example achieved when the sources are regularly distributed along a closed surface, the sources are mutually uncorrelated and their power spectra are identical. Despite the fact that in practical situations these conditions are at most only partly fulfilled, the results of seismic interferometry are generally quite robust, but the retrieved amplitudes are unreliable and the results are often blurred by artifacts. Several researchers have proposed to address some of the shortcomings by replacing the correlation process by deconvolution. In most cases the employed deconvolution procedure is essentially 1-D (i.e., trace-by-trace deconvolution). This compensates the anelastic losses, but it does not account for the anisotropic illumination of the receivers. To obtain more accurate results, seismic interferometry by deconvolution should acknowledge the 3-D nature of the seismic wave field. Hence, from a theoretical point of view, the trace-by-trace process should be replaced by a full 3-D wave field deconvolution process. Interferometry by multidimensional deconvolution is more accurate than the trace-by-trace correlation and deconvolution approaches but the processing is more involved. In the presentation we will give a systematic analysis of seismic interferometry by crosscorrelation versus multi-dimensional deconvolution and discuss applications of both approaches.

Deconvolution for three-dimensional acoustic source identification based on spherical harmonics beamforming

NASA Astrophysics Data System (ADS)

Chu, Zhigang; Yang, Yang; He, Yansong

2015-05-01

Spherical Harmonics Beamforming (SHB) with solid spherical arrays has become a particularly attractive tool for doing acoustic sources identification in cabin environments. However, it presents some intrinsic limitations, specifically poor spatial resolution and severe sidelobe contaminations. This paper focuses on overcoming these limitations effectively by deconvolution. First and foremost, a new formulation is proposed, which expresses SHB's output as a convolution of the true source strength distribution and the point spread function (PSF) defined as SHB's response to a unit-strength point source. Additionally, the typical deconvolution methods initially suggested for planar arrays, deconvolution approach for the mapping of acoustic sources (DAMAS), nonnegative least-squares (NNLS), Richardson-Lucy (RL) and CLEAN, are adapted to SHB successfully, which are capable of giving rise to highly resolved and deblurred maps. Finally, the merits of the deconvolution methods are validated and the relationships of source strength and pressure contribution reconstructed by the deconvolution methods vs. focus distance are explored both with computer simulations and experimentally. Several interesting results have emerged from this study: (1) compared with SHB, DAMAS, NNLS, RL and CLEAN all can not only improve the spatial resolution dramatically but also reduce or even eliminate the sidelobes effectively, allowing clear and unambiguous identification of single source or incoherent sources. (2) The availability of RL for coherent sources is highest, then DAMAS and NNLS, and that of CLEAN is lowest due to its failure in suppressing sidelobes. (3) Whether or not the real distance from the source to the array center equals the assumed one that is referred to as focus distance, the previous two results hold. (4) The true source strength can be recovered by dividing the reconstructed one by a coefficient that is the square of the focus distance divided by the real distance from the source to the array center. (5) The reconstructed pressure contribution is almost not affected by the focus distance, always approximating to the true one. This study will be of great significance to the accurate localization and quantification of acoustic sources in cabin environments.

Dynamic full-field infrared imaging with multiple synchrotron beams

PubMed Central

Stavitski, Eli; Smith, Randy J.; Bourassa, Megan W.; Acerbo, Alvin S.; Carr, G. L.; Miller, Lisa M.

2013-01-01

Microspectroscopic imaging in the infrared (IR) spectral region allows for the examination of spatially resolved chemical composition on the microscale. More than a decade ago, it was demonstrated that diffraction limited spatial resolution can be achieved when an apertured, single pixel IR microscope is coupled to the high brightness of a synchrotron light source. Nowadays, many IR microscopes are equipped with multi-pixel Focal Plane Array (FPA) detectors, which dramatically improve data acquisition times for imaging large areas. Recently, progress been made toward efficiently coupling synchrotron IR beamlines to multi-pixel detectors, but they utilize expensive and highly customized optical schemes. Here we demonstrate the development and application of a simple optical configuration that can be implemented on most existing synchrotron IR beamlines in order to achieve full-field IR imaging with diffraction-limited spatial resolution. Specifically, the synchrotron radiation fan is extracted from the bending magnet and split into four beams that are combined on the sample, allowing it to fill a large section of the FPA. With this optical configuration, we are able to oversample an image by more than a factor of two, even at the shortest wavelengths, making image restoration through deconvolution algorithms possible. High chemical sensitivity, rapid acquisition times, and superior signal-to-noise characteristics of the instrument are demonstrated. The unique characteristics of this setup enabled the real time study of heterogeneous chemical dynamics with diffraction-limited spatial resolution for the first time. PMID:23458231

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

We describe a new multiscale deconvolution algorithm that can also be used in a multifrequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multiscale algorithm is over an order of magnitude faster than the casa multiscale algorithm, and produces results of similar quality. For multifrequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is two to three orders of magnitude faster than casa msmfs. We extend the multiscale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multiscale cleaning. We test a second deconvolution method that is a variant of the moresane deconvolution technique, and uses a convex optimization technique with isotropic undecimated wavelets as dictionary. On simple well-calibrated data, the convex optimization algorithm produces visually more representative models. On complex or imperfect data, the convex optimization algorithm has stability issues.

New regularization scheme for blind color image deconvolution

NASA Astrophysics Data System (ADS)

Chen, Li; He, Yu; Yap, Kim-Hui

2011-01-01

This paper proposes a new regularization scheme to address blind color image deconvolution. Color images generally have a significant correlation among the red, green, and blue channels. Conventional blind monochromatic deconvolution algorithms handle each color image channels independently, thereby ignoring the interchannel correlation present in the color images. In view of this, a unified regularization scheme for image is developed to recover edges of color images and reduce color artifacts. In addition, by using the color image properties, a spectral-based regularization operator is adopted to impose constraints on the blurs. Further, this paper proposes a reinforcement regularization framework that integrates a soft parametric learning term in addressing blind color image deconvolution. A blur modeling scheme is developed to evaluate the relevance of manifold parametric blur structures, and the information is integrated into the deconvolution scheme. An optimization procedure called alternating minimization is then employed to iteratively minimize the image- and blur-domain cost functions. Experimental results show that the method is able to achieve satisfactory restored color images under different blurring conditions.

Comparison of active-set method deconvolution and matched-filtering for derivation of an ultrasound transit time spectrum.

PubMed

Wille, M-L; Zapf, M; Ruiter, N V; Gemmeke, H; Langton, C M

2015-06-21

The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs versus 0.18 μs standard deviations), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity.

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.

PubMed

He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan

2018-01-01

Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.

Regression-assisted deconvolution.

PubMed

McIntyre, Julie; Stefanski, Leonard A

2011-06-30

We present a semi-parametric deconvolution estimator for the density function of a random variable biX that is measured with error, a common challenge in many epidemiological studies. Traditional deconvolution estimators rely only on assumptions about the distribution of X and the error in its measurement, and ignore information available in auxiliary variables. Our method assumes the availability of a covariate vector statistically related to X by a mean-variance function regression model, where regression errors are normally distributed and independent of the measurement errors. Simulations suggest that the estimator achieves a much lower integrated squared error than the observed-data kernel density estimator when models are correctly specified and the assumption of normal regression errors is met. We illustrate the method using anthropometric measurements of newborns to estimate the density function of newborn length. Copyright © 2011 John Wiley & Sons, Ltd.

An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

NASA Astrophysics Data System (ADS)

Li, Zhong-xiao; Li, Zhen-chun

2016-09-01

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

Isotope pattern deconvolution as a tool to study iron metabolism in plants.

PubMed

Rodríguez-Castrillón, José Angel; Moldovan, Mariella; García Alonso, J Ignacio; Lucena, Juan José; García-Tomé, Maria Luisa; Hernández-Apaolaza, Lourdes

2008-01-01

Isotope pattern deconvolution is a mathematical technique for isolating distinct isotope signatures from mixtures of natural abundance and enriched tracers. In iron metabolism studies measurement of all four isotopes of the element by high-resolution multicollector or collision cell ICP-MS allows the determination of the tracer/tracee ratio with simultaneous internal mass bias correction and lower uncertainties. This technique was applied here for the first time to study iron uptake by cucumber plants using 57Fe-enriched iron chelates of the o,o and o,p isomers of ethylenediaminedi(o-hydroxyphenylacetic) acid (EDDHA) and ethylenediamine tetraacetic acid (EDTA). Samples of root, stem, leaves, and xylem sap, after exposure of the cucumber plants to the mentioned 57Fe chelates, were collected, dried, and digested using nitric acid. The isotopic composition of iron in the samples was measured by ICP-MS using a high-resolution multicollector instrument. Mass bias correction was computed using both a natural abundance iron standard and by internal correction using isotope pattern deconvolution. It was observed that, for plants with low 57Fe enrichment, isotope pattern deconvolution provided lower tracer/tracee ratio uncertainties than the traditional method applying external mass bias correction. The total amount of the element in the plants was determined by isotope dilution analysis, using a collision cell quadrupole ICP-MS instrument, after addition of 57Fe or natural abundance Fe in a known amount which depended on the isotopic composition of the sample.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study.

PubMed

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-21

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed 'MPD-AwTTV'. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

NASA Astrophysics Data System (ADS)

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Data enhancement and analysis through mathematical deconvolution of signals from scientific measuring instruments

NASA Technical Reports Server (NTRS)

Wood, G. M.; Rayborn, G. H.; Ioup, J. W.; Ioup, G. E.; Upchurch, B. T.; Howard, S. J.

1981-01-01

Mathematical deconvolution of digitized analog signals from scientific measuring instruments is shown to be a means of extracting important information which is otherwise hidden due to time-constant and other broadening or distortion effects caused by the experiment. Three different approaches to deconvolution and their subsequent application to recorded data from three analytical instruments are considered. To demonstrate the efficacy of deconvolution, the use of these approaches to solve the convolution integral for the gas chromatograph, magnetic mass spectrometer, and the time-of-flight mass spectrometer are described. Other possible applications of these types of numerical treatment of data to yield superior results from analog signals of the physical parameters normally measured in aerospace simulation facilities are suggested and briefly discussed.

Multi-frame partially saturated images blind deconvolution

NASA Astrophysics Data System (ADS)

Ye, Pengzhao; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2016-12-01

When blurred images have saturated or over-exposed pixels, conventional blind deconvolution approaches often fail to estimate accurate point spread function (PSF) and will introduce local ringing artifacts. In this paper, we propose a method to deal with the problem under the modified multi-frame blind deconvolution framework. First, in the kernel estimation step, a light streak detection scheme using multi-frame blurred images is incorporated into the regularization constraint. Second, we deal with image regions affected by the saturated pixels separately by modeling a weighted matrix during each multi-frame deconvolution iteration process. Both synthetic and real-world examples show that more accurate PSFs can be estimated and restored images have richer details and less negative effects compared to state of art methods.

Parallelization of a blind deconvolution algorithm

NASA Astrophysics Data System (ADS)

Matson, Charles L.; Borelli, Kathy J.

2006-09-01

Often it is of interest to deblur imagery in order to obtain higher-resolution images. Deblurring requires knowledge of the blurring function - information that is often not available separately from the blurred imagery. Blind deconvolution algorithms overcome this problem by jointly estimating both the high-resolution image and the blurring function from the blurred imagery. Because blind deconvolution algorithms are iterative in nature, they can take minutes to days to deblur an image depending how many frames of data are used for the deblurring and the platforms on which the algorithms are executed. Here we present our progress in parallelizing a blind deconvolution algorithm to increase its execution speed. This progress includes sub-frame parallelization and a code structure that is not specialized to a specific computer hardware architecture.

Improved deconvolution of very weak confocal signals.

PubMed

Day, Kasey J; La Rivière, Patrick J; Chandler, Talon; Bindokas, Vytas P; Ferrier, Nicola J; Glick, Benjamin S

2017-01-01

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

Fast Fourier-based deconvolution for three-dimensional acoustic source identification with solid spherical arrays

NASA Astrophysics Data System (ADS)

Yang, Yang; Chu, Zhigang; Shen, Linbang; Ping, Guoli; Xu, Zhongming

2018-07-01

Being capable of demystifying the acoustic source identification result fast, Fourier-based deconvolution has been studied and applied widely for the delay and sum (DAS) beamforming with two-dimensional (2D) planar arrays. It is, however so far, still blank in the context of spherical harmonics beamforming (SHB) with three-dimensional (3D) solid spherical arrays. This paper is motivated to settle this problem. Firstly, for the purpose of determining the effective identification region, the premise of deconvolution, a shift-invariant point spread function (PSF), is analyzed with simulations. To make the premise be satisfied approximately, the opening angle in elevation dimension of the surface of interest should be small, while no restriction is imposed to the azimuth dimension. Then, two kinds of deconvolution theories are built for SHB using the zero and the periodic boundary conditions respectively. Both simulations and experiments demonstrate that the periodic boundary condition is superior to the zero one, and fits the 3D acoustic source identification with solid spherical arrays better. Finally, four periodic boundary condition based deconvolution methods are formulated, and their performance is disclosed both with simulations and experimentally. All the four methods offer enhanced spatial resolution and reduced sidelobe contaminations over SHB. The recovered source strength approximates to the exact one multiplied with a coefficient that is the square of the focus distance divided by the distance from the source to the array center, while the recovered pressure contribution is scarcely affected by the focus distance, always approximating to the exact one.

Detection of increased vasa vasorum in artery walls: improving CT number accuracy using image deconvolution

NASA Astrophysics Data System (ADS)

Rajendran, Kishore; Leng, Shuai; Jorgensen, Steven M.; Abdurakhimova, Dilbar; Ritman, Erik L.; McCollough, Cynthia H.

2017-03-01

Changes in arterial wall perfusion are an indicator of early atherosclerosis. This is characterized by an increased spatial density of vasa vasorum (VV), the micro-vessels that supply oxygen and nutrients to the arterial wall. Detection of increased VV during contrast-enhanced computed tomography (CT) imaging is limited due to contamination from blooming effect from the contrast-enhanced lumen. We report the application of an image deconvolution technique using a measured system point-spread function, on CT data obtained from a photon-counting CT system to reduce blooming and to improve the CT number accuracy of arterial wall, which enhances detection of increased VV. A phantom study was performed to assess the accuracy of the deconvolution technique. A porcine model was created with enhanced VV in one carotid artery; the other carotid artery served as a control. CT images at an energy range of 25-120 keV were reconstructed. CT numbers were measured for multiple locations in the carotid walls and for multiple time points, pre and post contrast injection. The mean CT number in the carotid wall was compared between the left (increased VV) and right (control) carotid arteries. Prior to deconvolution, results showed similar mean CT numbers in the left and right carotid wall due to the contamination from blooming effect, limiting the detection of increased VV in the left carotid artery. After deconvolution, the mean CT number difference between the left and right carotid arteries was substantially increased at all the time points, enabling detection of the increased VV in the artery wall.

SU-C-9A-03: Simultaneous Deconvolution and Segmentation for PET Tumor Delineation Using a Variational Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, L; Tan, S; Lu, W

2014-06-01

Purpose: To implement a new method that integrates deconvolution with segmentation under the variational framework for PET tumor delineation. Methods: Deconvolution and segmentation are both challenging problems in image processing. The partial volume effect (PVE) makes tumor boundaries in PET image blurred which affects the accuracy of tumor segmentation. Deconvolution aims to obtain a PVE-free image, which can help to improve the segmentation accuracy. Conversely, a correct localization of the object boundaries is helpful to estimate the blur kernel, and thus assist in the deconvolution. In this study, we proposed to solve the two problems simultaneously using a variational methodmore » so that they can benefit each other. The energy functional consists of a fidelity term and a regularization term, and the blur kernel was limited to be the isotropic Gaussian kernel. We minimized the energy functional by solving the associated Euler-Lagrange equations and taking the derivative with respect to the parameters of the kernel function. An alternate minimization method was used to iterate between segmentation, deconvolution and blur-kernel recovery. The performance of the proposed method was tested on clinic PET images of patients with non-Hodgkin's lymphoma, and compared with seven other segmentation methods using the dice similarity index (DSI) and volume error (VE). Results: Among all segmentation methods, the proposed one (DSI=0.81, VE=0.05) has the highest accuracy, followed by the active contours without edges (DSI=0.81, VE=0.25), while other methods including the Graph Cut and the Mumford-Shah (MS) method have lower accuracy. A visual inspection shows that the proposed method localizes the real tumor contour very well. Conclusion: The result showed that deconvolution and segmentation can contribute to each other. The proposed variational method solve the two problems simultaneously, and leads to a high performance for tumor segmentation in PET. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant Nos. 60971112 and 61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.« less

Septal penetration correction in I-131 imaging following thyroid cancer treatment

NASA Astrophysics Data System (ADS)

Barrack, Fiona; Scuffham, James; McQuaid, Sarah

2018-04-01

Whole body gamma camera images acquired after I-131 treatment for thyroid cancer can suffer from collimator septal penetration artefacts because of the high energy of the gamma photons. This results in the appearance of ‘spoke’ artefacts, emanating from regions of high activity concentration, caused by the non-isotropic attenuation of the collimator. Deconvolution has the potential to reduce such artefacts, by taking into account the non-Gaussian point-spread-function (PSF) of the system. A Richardson–Lucy deconvolution algorithm, with and without prior scatter-correction was tested as a method of reducing septal penetration in planar gamma camera images. Phantom images (hot spheres within a warm background) were acquired and deconvolution using a measured PSF was applied. The results were evaluated through region-of-interest and line profile analysis to determine the success of artefact reduction and the optimal number of deconvolution iterations and damping parameter (λ). Without scatter-correction, the optimal results were obtained with 15 iterations and λ  =  0.01, with the counts in the spokes reduced to 20% of the original value, indicating a substantial decrease in their prominence. When a triple-energy-window scatter-correction was applied prior to deconvolution, the optimal results were obtained with six iterations and λ  =  0.02, which reduced the spoke counts to 3% of the original value. The prior application of scatter-correction therefore produced the best results, with a marked change in the appearance of the images. The optimal settings were then applied to six patient datasets, to demonstrate its utility in the clinical setting. In all datasets, spoke artefacts were substantially reduced after the application of scatter-correction and deconvolution, with the mean spoke count being reduced to 10% of the original value. This indicates that deconvolution is a promising technique for septal penetration artefact reduction that could potentially improve the diagnostic accuracy of I-131 imaging. Novelty and significance This work has demonstrated that scatter correction combined with deconvolution can be used to substantially reduce the appearance of septal penetration artefacts in I-131 phantom and patient gamma camera planar images, enable improved visualisation of the I-131 distribution. Deconvolution with symmetric PSF has previously been used to reduce artefacts in gamma camera images however this work details the novel use of an asymmetric PSF to remove the angularly dependent septal penetration artefacts.

Evaluating performance in three-dimensional fluorescence microscopy

PubMed Central

MURRAY, JOHN M; APPLETON, PAUL L; SWEDLOW, JASON R; WATERS, JENNIFER C

2007-01-01

In biological fluorescence microscopy, image contrast is often degraded by a high background arising from out of focus regions of the specimen. This background can be greatly reduced or eliminated by several modes of thick specimen microscopy, including techniques such as 3-D deconvolution and confocal. There has been a great deal of interest and some confusion about which of these methods is ‘better’, in principle or in practice. The motivation for the experiments reported here is to establish some rough guidelines for choosing the most appropriate method of microscopy for a given biological specimen. The approach is to compare the efficiency of photon collection, the image contrast and the signal-to-noise ratio achieved by the different methods at equivalent illumination, using a specimen in which the amount of out of focus background is adjustable over the range encountered with biological samples. We compared spot scanning confocal, spinning disk confocal and wide-field/deconvolution (WFD) microscopes and find that the ratio of out of focus background to in-focus signal can be used to predict which method of microscopy will provide the most useful image. We also find that the precision of measurements of net fluorescence yield is very much lower than expected for all modes of microscopy. Our analysis enabled a clear, quantitative delineation of the appropriate use of different imaging modes relative to the ratio of out-of-focus background to in-focus signal, and defines an upper limit to the useful range of the three most common modes of imaging. PMID:18045334

PinX1 is recruited to the mitotic chromosome periphery by Nucleolin and facilitates chromosome congression.

PubMed

Li, Na; Yuan, Kai; Yan, Feng; Huo, Yuda; Zhu, Tongge; Liu, Xing; Guo, Zhen; Yao, Xuebiao

2009-06-19

Mitotic chromosome movements are orchestrated by interactions between spindle microtubules and chromosomes. It is well known that kinetochore is the major site where microtubule-chromosome attachment occurs. However, the functions of other domains of chromosome such as chromosome periphery have remained elusive. Our previous studies show that PinX1 distributes to chromosome periphery and kinetochore during mitosis, and harbors the microtubule binding activity. Here we report that PinX1 interacts with Nucleolin, a chromosome periphery protein, through its C-termini. Deconvolution microscopic analyses show PinX1 mainly co-localizes with Nucleolin at chromosome periphery in prometaphase. Moreover, depletion of Nucleolin abolishes chromosome periphery localizations of PinX1, suggesting a functional interrelationship between PinX1 and Nucleolin. Importantly, repression of PinX1 and Nucleolin abrogates chromosome segregation in real-time mitosis, validating the functional importance of PinX1-Nucleolin interaction. We propose PinX1 is recruited to chromosome periphery by Nucleolin and a complex of PinX1 and Nucleolin is essential for faithful chromosome congression.

Source Pulse Estimation of Mine Shock by Blind Deconvolution

NASA Astrophysics Data System (ADS)

Makowski, R.

The objective of seismic signal deconvolution is to extract from the signal information concerning the rockmass or the signal in the source of the shock. In the case of blind deconvolution, we have to extract information regarding both quantities. Many methods of deconvolution made use of in prospective seismology were found to be of minor utility when applied to shock-induced signals recorded in the mines of the Lubin Copper District. The lack of effectiveness should be attributed to the inadequacy of the model on which the methods are based, with respect to the propagation conditions for that type of signal. Each of the blind deconvolution methods involves a number of assumptions; hence, only if these assumptions are fulfilled, we may expect reliable results.Consequently, we had to formulate a different model for the signals recorded in the copper mines of the Lubin District. The model is based on the following assumptions: (1) The signal emitted by the sh ock source is a short-term signal. (2) The signal transmitting system (rockmass) constitutes a parallel connection of elementary systems. (3) The elementary systems are of resonant type. Such a model seems to be justified by the geological structure as well as by the positions of the shock foci and seismometers. The results of time-frequency transformation also support the dominance of resonant-type propagation.Making use of the model, a new method for the blind deconvolution of seismic signals has been proposed. The adequacy of the new model, as well as the efficiency of the proposed method, has been confirmed by the results of blind deconvolution. The slight approximation errors obtained with a small number of approximating elements additionally corroborate the adequacy of the model.

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

DOE PAGES

Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy; ...

2018-02-07

The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy

The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less

Improving Range Estimation of a 3-Dimensional Flash Ladar via Blind Deconvolution

DTIC Science & Technology

2010-09-01

12 2.1.4 Optical Imaging as a Linear and Nonlinear System 15 2.1.5 Coherence Theory and Laser Light Statistics . . . 16 2.2 Deconvolution...rather than deconvolution. 2.1.5 Coherence Theory and Laser Light Statistics. Using [24] and [25], this section serves as background on coherence theory...the laser light incident on the detector surface. The image intensity related to different types of coherence is governed by the laser light’s spatial

Faceting for direction-dependent spectral deconvolution

NASA Astrophysics Data System (ADS)

Tasse, C.; Hugo, B.; Mirmont, M.; Smirnov, O.; Atemkeng, M.; Bester, L.; Hardcastle, M. J.; Lakhoo, R.; Perkins, S.; Shimwell, T.

2018-04-01

The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (DDFacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of DDFacet presented here can account for any externally defined Jones matrices and/or beam patterns.

4Pi microscopy deconvolution with a variable point-spread function.

PubMed

Baddeley, David; Carl, Christian; Cremer, Christoph

2006-09-20

To remove the axial sidelobes from 4Pi images, deconvolution forms an integral part of 4Pi microscopy. As a result of its high axial resolution, the 4Pi point spread function (PSF) is particularly susceptible to imperfect optical conditions within the sample. This is typically observed as a shift in the position of the maxima under the PSF envelope. A significantly varying phase shift renders deconvolution procedures based on a spatially invariant PSF essentially useless. We present a technique for computing the forward transformation in the case of a varying phase at a computational expense of the same order of magnitude as that of the shift invariant case, a method for the estimation of PSF phase from an acquired image, and a deconvolution procedure built on these techniques.

Improved deconvolution of very weak confocal signals

PubMed Central

Day, Kasey J.; La Rivière, Patrick J.; Chandler, Talon; Bindokas, Vytas P.; Ferrier, Nicola J.; Glick, Benjamin S.

2017-01-01

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage. PMID:28868135

Improved deconvolution of very weak confocal signals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Day, Kasey J.; La Riviere, Patrick J.; Chandler, Talon

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal ofmore » background noise. Here, this approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.« less

Improved deconvolution of very weak confocal signals

DOE PAGES

Day, Kasey J.; La Riviere, Patrick J.; Chandler, Talon; ...

2017-06-06

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal ofmore » background noise. Here, this approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.« less

Parallel detecting super-resolution microscopy using correlation based image restoration

NASA Astrophysics Data System (ADS)

Yu, Zhongzhi; Liu, Shaocong; Zhu, Dazhao; Kuang, Cuifang; Liu, Xu

2017-12-01

A novel approach to achieve the image restoration is proposed in which each detector's relative position in the detector array is no longer a necessity. We can identify each detector's relative location by extracting a certain area from one of the detector's image and scanning it on other detectors' images. According to this location, we can generate the point spread functions (PSF) for each detector and perform deconvolution for image restoration. Equipped with this method, the microscope with discretionally designed detector array can be easily constructed without the concern of exact relative locations of detectors. The simulated results and experimental results show the total improvement in resolution with a factor of 1.7 compared to conventional confocal fluorescence microscopy. With the significant enhancement in resolution and easiness for application of this method, this novel method should have potential for a wide range of application in fluorescence microscopy based on parallel detecting.

Convex blind image deconvolution with inverse filtering

NASA Astrophysics Data System (ADS)

Lv, Xiao-Guang; Li, Fang; Zeng, Tieyong

2018-03-01

Blind image deconvolution is the process of estimating both the original image and the blur kernel from the degraded image with only partial or no information about degradation and the imaging system. It is a bilinear ill-posed inverse problem corresponding to the direct problem of convolution. Regularization methods are used to handle the ill-posedness of blind deconvolution and get meaningful solutions. In this paper, we investigate a convex regularized inverse filtering method for blind deconvolution of images. We assume that the support region of the blur object is known, as has been done in a few existing works. By studying the inverse filters of signal and image restoration problems, we observe the oscillation structure of the inverse filters. Inspired by the oscillation structure of the inverse filters, we propose to use the star norm to regularize the inverse filter. Meanwhile, we use the total variation to regularize the resulting image obtained by convolving the inverse filter with the degraded image. The proposed minimization model is shown to be convex. We employ the first-order primal-dual method for the solution of the proposed minimization model. Numerical examples for blind image restoration are given to show that the proposed method outperforms some existing methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), visual quality and time consumption.

Blind deconvolution post-processing of images corrected by adaptive optics

NASA Astrophysics Data System (ADS)

Christou, Julian C.

1995-08-01

Experience with the adaptive optics system at the Starfire Optical Range has shown that the point spread function is non-uniform and varies both spatially and temporally as well as being object dependent. Because of this, the application of a standard linear and non-linear deconvolution algorithms make it difficult to deconvolve out the point spread function. In this paper we demonstrate the application of a blind deconvolution algorithm to adaptive optics compensated data where a separate point spread function is not needed.

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program.

PubMed

Afouxenidis, D; Polymeris, G S; Tsirliganis, N C; Kitis, G

2012-05-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the GLOw Curve ANalysis INtercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters.

Deconvolution of noisy transient signals: a Kalman filtering application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candy, J.V.; Zicker, J.E.

The deconvolution of transient signals from noisy measurements is a common problem occuring in various tests at Lawrence Livermore National Laboratory. The transient deconvolution problem places atypical constraints on algorithms presently available. The Schmidt-Kalman filter, a time-varying, tunable predictor, is designed using a piecewise constant model of the transient input signal. A simulation is developed to test the algorithm for various input signal bandwidths and different signal-to-noise ratios for the input and output sequences. The algorithm performance is reasonable.

A comparison of deconvolution and the Rutland-Patlak plot in parenchymal renal uptake rate.

PubMed

Al-Shakhrah, Issa A

2012-07-01

Deconvolution and the Rutland-Patlak (R-P) plot are two of the most commonly used methods for analyzing dynamic radionuclide renography. Both methods allow estimation of absolute and relative renal uptake of radiopharmaceutical and of its rate of transit through the kidney. Seventeen patients (32 kidneys) were referred for further evaluation by renal scanning. All patients were positioned supine with their backs to the scintillation gamma camera, so that the kidneys and the heart are both in the field of view. Approximately 5-7 mCi of (99m)Tc-DTPA (diethylinetriamine penta-acetic acid) in about 0.5 ml of saline is injected intravenously and sequential 20 s frames were acquired, the study on each patient lasts for approximately 20 min. The time-activity curves of the parenchymal region of interest of each kidney, as well as the heart were obtained for analysis. The data were then analyzed with deconvolution and the R-P plot. A strong positive association (n = 32; r = 0.83; R (2) = 0.68) was found between the values that obtained by applying the two methods. Bland-Altman statistical analysis demonstrated that ninety seven percent of the values in the study (31 cases from 32 cases, 97% of the cases) were within limits of agreement (mean ± 1.96 standard deviation). We believe that R-P analysis method is expected to be more reproducible than iterative deconvolution method, because the deconvolution technique (the iterative method) relies heavily on the accuracy of the first point analyzed, as any errors are carried forward into the calculations of all the subsequent points, whereas R-P technique is based on an initial analysis of the data by means of the R-P plot, and it can be considered as an alternative technique to find and calculate the renal uptake rate.

A mathematical deconvolution formulation for superficial dose distribution measurement by Cerenkov light dosimetry.

PubMed

Brost, Eric Edward; Watanabe, Yoichi

2018-06-01

Cerenkov photons are created by high-energy radiation beams used for radiation therapy. In this study, we developed a Cerenkov light dosimetry technique to obtain a two-dimensional dose distribution in a superficial region of medium from the images of Cerenkov photons by using a deconvolution method. An integral equation was derived to represent the Cerenkov photon image acquired by a camera for a given incident high-energy photon beam by using convolution kernels. Subsequently, an equation relating the planar dose at a depth to a Cerenkov photon image using the well-known relationship between the incident beam fluence and the dose distribution in a medium was obtained. The final equation contained a convolution kernel called the Cerenkov dose scatter function (CDSF). The CDSF function was obtained by deconvolving the Cerenkov scatter function (CSF) with the dose scatter function (DSF). The GAMOS (Geant4-based Architecture for Medicine-Oriented Simulations) Monte Carlo particle simulation software was used to obtain the CSF and DSF. The dose distribution was calculated from the Cerenkov photon intensity data using an iterative deconvolution method with the CDSF. The theoretical formulation was experimentally evaluated by using an optical phantom irradiated by high-energy photon beams. The intensity of the deconvolved Cerenkov photon image showed linear dependence on the dose rate and the photon beam energy. The relative intensity showed a field size dependence similar to the beam output factor. Deconvolved Cerenkov images showed improvement in dose profiles compared with the raw image data. In particular, the deconvolution significantly improved the agreement in the high dose gradient region, such as in the penumbra. Deconvolution with a single iteration was found to provide the most accurate solution of the dose. Two-dimensional dose distributions of the deconvolved Cerenkov images agreed well with the reference distributions for both square fields and a multileaf collimator (MLC) defined, irregularly shaped field. The proposed technique improved the accuracy of the Cerenkov photon dosimetry in the penumbra region. The results of this study showed initial validation of the deconvolution method for beam profile measurements in a homogeneous media. The new formulation accounted for the physical processes of Cerenkov photon transport in the medium more accurately than previously published methods. © 2018 American Association of Physicists in Medicine.

Image restoration and superresolution as probes of small scale far-IR structure in star forming regions

NASA Technical Reports Server (NTRS)

Lester, D. F.; Harvey, P. M.; Joy, M.; Ellis, H. B., Jr.

1986-01-01

Far-infrared continuum studies from the Kuiper Airborne Observatory are described that are designed to fully exploit the small-scale spatial information that this facility can provide. This work gives the clearest picture to data on the structure of galactic and extragalactic star forming regions in the far infrared. Work is presently being done with slit scans taken simultaneously at 50 and 100 microns, yielding one-dimensional data. Scans of sources in different directions have been used to get certain information on two dimensional structure. Planned work with linear arrays will allow us to generalize our techniques to two dimensional image restoration. For faint sources, spatial information at the diffraction limit of the telescope is obtained, while for brighter sources, nonlinear deconvolution techniques have allowed us to improve over the diffraction limit by as much as a factor of four. Information on the details of the color temperature distribution is derived as well. This is made possible by the accuracy with which the instrumental point-source profile (PSP) is determined at both wavelengths. While these two PSPs are different, data at different wavelengths can be compared by proper spatial filtering. Considerable effort has been devoted to implementing deconvolution algorithms. Nonlinear deconvolution methods offer the potential of superresolution -- that is, inference of power at spatial frequencies that exceed D lambda. This potential is made possible by the implicit assumption by the algorithm of positivity of the deconvolved data, a universally justifiable constraint for photon processes. We have tested two nonlinear deconvolution algorithms on our data; the Richardson-Lucy (R-L) method and the Maximum Entropy Method (MEM). The limits of image deconvolution techniques for achieving spatial resolution are addressed.

Range resolution improvement in passive bistatic radars using nested FM channels and least squares approach

NASA Astrophysics Data System (ADS)

Arslan, Musa T.; Tofighi, Mohammad; Sevimli, Rasim A.; ćetin, Ahmet E.

2015-05-01

One of the main disadvantages of using commercial broadcasts in a Passive Bistatic Radar (PBR) system is the range resolution. Using multiple broadcast channels to improve the radar performance is offered as a solution to this problem. However, it suffers from detection performance due to the side-lobes that matched filter creates for using multiple channels. In this article, we introduce a deconvolution algorithm to suppress the side-lobes. The two-dimensional matched filter output of a PBR is further analyzed as a deconvolution problem. The deconvolution algorithm is based on making successive projections onto the hyperplanes representing the time delay of a target. Resulting iterative deconvolution algorithm is globally convergent because all constraint sets are closed and convex. Simulation results in an FM based PBR system are presented.

Application of deconvolution interferometry with both Hi-net and KiK-net data

NASA Astrophysics Data System (ADS)

Nakata, N.

2013-12-01

Application of deconvolution interferometry to wavefields observed by KiK-net, a strong-motion recording network in Japan, is useful for estimating wave velocities and S-wave splitting in the near surface. Using this technique, for example, Nakata and Snieder (2011, 2012) found changed in velocities caused by Tohoku-Oki earthquake in Japan. At the location of the borehole accelerometer of each KiK-net station, a velocity sensor is also installed as a part of a high-sensitivity seismograph network (Hi-net). I present a technique that uses both Hi-net and KiK-net records for computing deconvolution interferometry. The deconvolved waveform obtained from the combination of Hi-net and KiK-net data is similar to the waveform computed from KiK-net data only, which indicates that one can use Hi-net wavefields for deconvolution interferometry. Because Hi-net records have a high signal-to-noise ratio (S/N) and high dynamic resolution, the S/N and the quality of amplitude and phase of deconvolved waveforms can be improved with Hi-net data. These advantages are especially important for short-time moving-window seismic interferometry and deconvolution interferometry using later coda waves.

Peptide de novo sequencing of mixture tandem mass spectra

PubMed Central

Hotta, Stéphanie Yuki Kolbeck; Verano‐Braga, Thiago; Kjeldsen, Frank

2016-01-01

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co‐isolation and thus prone to false identifications. The deconvolution approach matched complementary b‐, y‐ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co‐isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20–35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications. PMID:27329701

Deconvolution using a neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehman, S.K.

1990-11-15

Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

Deconvolution of gas chromatographic data

NASA Technical Reports Server (NTRS)

Howard, S.; Rayborn, G. H.

1980-01-01

The use of deconvolution methods on gas chromatographic data to obtain an accurate determination of the relative amounts of each material present by mathematically separating the merged peaks is discussed. Data were obtained on a gas chromatograph with a flame ionization detector. Chromatograms of five xylenes with differing degrees of separation were generated by varying the column temperature at selected rates. The merged peaks were then successfully separated by deconvolution. The concept of function continuation in the frequency domain was introduced in striving to reach the theoretical limit of accuracy, but proved to be only partially successful.

Detailed interpretation of aeromagnetic data from the Patagonia Mountains area, southeastern Arizona

USGS Publications Warehouse

Bultman, Mark W.

2015-01-01

Euler deconvolution depth estimates derived from aeromagnetic data with a structural index of 0 show that mapped faults on the northern margin of the Patagonia Mountains generally agree with the depth estimates in the new geologic model. The deconvolution depth estimates also show that the concealed Patagonia Fault southwest of the Patagonia Mountains is more complex than recent geologic mapping represents. Additionally, Euler deconvolution depth estimates with a structural index of 2 locate many potential intrusive bodies that might be associated with known and unknown mineralization.

SU-G-IeP3-08: Image Reconstruction for Scanning Imaging System Based On Shape-Modulated Point Spreading Function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Ruixing; Yang, LV; Xu, Kele

Purpose: Deconvolution is a widely used tool in the field of image reconstruction algorithm when the linear imaging system has been blurred by the imperfect system transfer function. However, due to the nature of Gaussian-liked distribution for point spread function (PSF), the components with coherent high frequency in the image are hard to restored in most of the previous scanning imaging system, even the relatively accurate PSF is acquired. We propose a novel method for deconvolution of images which are obtained by using shape-modulated PSF. Methods: We use two different types of PSF - Gaussian shape and donut shape -more » to convolute the original image in order to simulate the process of scanning imaging. By employing deconvolution of the two images with corresponding given priors, the image quality of the deblurred images are compared. Then we find the critical size of the donut shape compared with the Gaussian shape which has similar deconvolution results. Through calculation of tightened focusing process using radially polarized beam, such size of donut is achievable under same conditions. Results: The effects of different relative size of donut and Gaussian shapes are investigated. When the full width at half maximum (FWHM) ratio of donut and Gaussian shape is set about 1.83, similar resolution results are obtained through our deconvolution method. Decreasing the size of donut will favor the deconvolution method. A mask with both amplitude and phase modulation is used to create a donut-shaped PSF compared with the non-modulated Gaussian PSF. Donut with size smaller than our critical value is obtained. Conclusion: The utility of donutshaped PSF are proved useful and achievable in the imaging and deconvolution processing, which is expected to have potential practical applications in high resolution imaging for biological samples.« less

Spectral identification of a 90Sr source in the presence of masking nuclides using Maximum-Likelihood deconvolution

NASA Astrophysics Data System (ADS)

Neuer, Marcus J.

2013-11-01

A technique for the spectral identification of strontium-90 is shown, utilising a Maximum-Likelihood deconvolution. Different deconvolution approaches are discussed and summarised. Based on the intensity distribution of the beta emission and Geant4 simulations, a combined response matrix is derived, tailored to the β- detection process in sodium iodide detectors. It includes scattering effects and attenuation by applying a base material decomposition extracted from Geant4 simulations with a CAD model for a realistic detector system. Inversion results of measurements show the agreement between deconvolution and reconstruction. A detailed investigation with additional masking sources like 40K, 226Ra and 131I shows that a contamination of strontium can be found in the presence of these nuisance sources. Identification algorithms for strontium are presented based on the derived technique. For the implementation of blind identification, an exemplary masking ratio is calculated.

A frequency-domain seismic blind deconvolution based on Gini correlations

NASA Astrophysics Data System (ADS)

Wang, Zhiguo; Zhang, Bing; Gao, Jinghuai; Huo Liu, Qing

2018-02-01

In reflection seismic processing, the seismic blind deconvolution is a challenging problem, especially when the signal-to-noise ratio (SNR) of the seismic record is low and the length of the seismic record is short. As a solution to this ill-posed inverse problem, we assume that the reflectivity sequence is independent and identically distributed (i.i.d.). To infer the i.i.d. relationships from seismic data, we first introduce the Gini correlations (GCs) to construct a new criterion for the seismic blind deconvolution in the frequency-domain. Due to a unique feature, the GCs are robust in their higher tolerance of the low SNR data and less dependent on record length. Applications of the seismic blind deconvolution based on the GCs show their capacity in estimating the unknown seismic wavelet and the reflectivity sequence, whatever synthetic traces or field data, even with low SNR and short sample record.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

PubMed

Carnevale Neto, Fausto; Pilon, Alan C; Selegato, Denise M; Freire, Rafael T; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis

PubMed Central

Carnevale Neto, Fausto; Pilon, Alan C.; Selegato, Denise M.; Freire, Rafael T.; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P.; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts. PMID:27747213

Automated processing for proton spectroscopic imaging using water reference deconvolution.

PubMed

Maudsley, A A; Wu, Z; Meyerhoff, D J; Weiner, M W

1994-06-01

Automated formation of MR spectroscopic images (MRSI) is necessary before routine application of these methods is possible for in vivo studies; however, this task is complicated by the presence of spatially dependent instrumental distortions and the complex nature of the MR spectrum. A data processing method is presented for completely automated formation of in vivo proton spectroscopic images, and applied for analysis of human brain metabolites. This procedure uses the water reference deconvolution method (G. A. Morris, J. Magn. Reson. 80, 547(1988)) to correct for line shape distortions caused by instrumental and sample characteristics, followed by parametric spectral analysis. Results for automated image formation were found to compare favorably with operator dependent spectral integration methods. While the water reference deconvolution processing was found to provide good correction of spatially dependent resonance frequency shifts, it was found to be susceptible to errors for correction of line shape distortions. These occur due to differences between the water reference and the metabolite distributions.

A Robust Gold Deconvolution Approach for LiDAR Waveform Data Processing to Characterize Vegetation Structure

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.; Sheridan, R.; Ku, N. W.

2014-12-01

Increasing attention has been paid in the remote sensing community to the next generation Light Detection and Ranging (lidar) waveform data systems for extracting information on topography and the vertical structure of vegetation. However, processing waveform lidar data raises some challenges compared to analyzing discrete return data. The overall goal of this study was to present a robust de-convolution algorithm- Gold algorithm used to de-convolve waveforms in a lidar dataset acquired within a 60 x 60m study area located in the Harvard Forest in Massachusetts. The waveform lidar data was collected by the National Ecological Observatory Network (NEON). Specific objectives were to: (1) explore advantages and limitations of various waveform processing techniques to derive topography and canopy height information; (2) develop and implement a novel de-convolution algorithm, the Gold algorithm, to extract elevation and canopy metrics; and (3) compare results and assess accuracy. We modeled lidar waveforms with a mixture of Gaussian functions using the Non-least squares (NLS) algorithm implemented in R and derived a Digital Terrain Model (DTM) and canopy height. We compared our waveform-derived topography and canopy height measurements using the Gold de-convolution algorithm to results using the Richardson-Lucy algorithm. Our findings show that the Gold algorithm performed better than the Richardson-Lucy algorithm in terms of recovering the hidden echoes and detecting false echoes for generating a DTM, which indicates that the Gold algorithm could potentially be applied to processing of waveform lidar data to derive information on terrain elevation and canopy characteristics.

Scientific Visualization Made Easy for the Scientist

NASA Astrophysics Data System (ADS)

Westerhoff, M.; Henderson, B.

2002-12-01

amirar is an application program used in creating 3D visualizations and geometric models of 3D image data sets from various application areas, e.g. medicine, biology, biochemistry, chemistry, physics, and engineering. It has demonstrated significant adoption in the market place since becoming commercially available in 2000. The rapid adoption has expanded the features being requested by the user base and broadened the scope of the amira product offering. The amira product offering includes amira Standard, amiraDevT, used to extend the product capabilities by users, amiraMolT, used for molecular visualization, amiraDeconvT, used to improve quality of image data, and amiraVRT, used in immersive VR environments. amira allows the user to construct a visualization tailored to his or her needs without requiring any programming knowledge. It also allows 3D objects to be represented as grids suitable for numerical simulations, notably as triangular surfaces and volumetric tetrahedral grids. The amira application also provides methods to generate such grids from voxel data representing an image volume, and it includes a general-purpose interactive 3D viewer. amiraDev provides an application-programming interface (API) that allows the user to add new components by C++ programming. amira supports many import formats including a 'raw' format allowing immediate access to your native uniform data sets. amira uses the power and speed of the OpenGLr and Open InventorT graphics libraries and 3D graphics accelerators to allow you to access over 145 modules, enabling you to process, probe, analyze and visualize your data. The amiraMolT extension adds powerful tools for molecular visualization to the existing amira platform. amiraMolT contains support for standard molecular file formats, tools for visualization and analysis of static molecules as well as molecular trajectories (time series). amiraDeconv adds tools for the deconvolution of 3D microscopic images. Deconvolution is the process of increasing image quality and resolution by computationally compensating artifacts of the recording process. amiraDeconv supports 3D wide field microscopy as well as 3D confocal microscopy. It offers both non-blind and blind image deconvolution algorithms. Non-blind deconvolution uses an individual measured point spread function, while non-blind algorithms work on the basis of only a few recording parameters (like numerical aperture or zoom factor). amiraVR is a specialized and extended version of the amira visualization system which is dedicated for use in immersive installations, such as large-screen stereoscopic projections, CAVEr or Holobenchr systems. Among others, it supports multi-threaded multi-pipe rendering, head-tracking, advanced 3D interaction concepts, and 3D menus allowing interaction with any amira object in the same way as on the desktop. With its unique set of features, amiraVR represents both a VR (Virtual Reality) ready application for scientific and medical visualization in immersive environments, and a development platform that allows building VR applications.

A digital algorithm for spectral deconvolution with noise filtering and peak picking: NOFIPP-DECON

NASA Technical Reports Server (NTRS)

Edwards, T. R.; Settle, G. L.; Knight, R. D.

1975-01-01

Noise-filtering, peak-picking deconvolution software incorporates multiple convoluted convolute integers and multiparameter optimization pattern search. The two theories are described and three aspects of the software package are discussed in detail. Noise-filtering deconvolution was applied to a number of experimental cases ranging from noisy, nondispersive X-ray analyzer data to very noisy photoelectric polarimeter data. Comparisons were made with published infrared data, and a man-machine interactive language has evolved for assisting in very difficult cases. A modified version of the program is being used for routine preprocessing of mass spectral and gas chromatographic data.

Toxoplasma Modulates Signature Pathways of Human Epilepsy, Neurodegeneration & Cancer.

PubMed

Ngô, Huân M; Zhou, Ying; Lorenzi, Hernan; Wang, Kai; Kim, Taek-Kyun; Zhou, Yong; El Bissati, Kamal; Mui, Ernest; Fraczek, Laura; Rajagopala, Seesandra V; Roberts, Craig W; Henriquez, Fiona L; Montpetit, Alexandre; Blackwell, Jenefer M; Jamieson, Sarra E; Wheeler, Kelsey; Begeman, Ian J; Naranjo-Galvis, Carlos; Alliey-Rodriguez, Ney; Davis, Roderick G; Soroceanu, Liliana; Cobbs, Charles; Steindler, Dennis A; Boyer, Kenneth; Noble, A Gwendolyn; Swisher, Charles N; Heydemann, Peter T; Rabiah, Peter; Withers, Shawn; Soteropoulos, Patricia; Hood, Leroy; McLeod, Rima

2017-09-13

One third of humans are infected lifelong with the brain-dwelling, protozoan parasite, Toxoplasma gondii. Approximately fifteen million of these have congenital toxoplasmosis. Although neurobehavioral disease is associated with seropositivity, causality is unproven. To better understand what this parasite does to human brains, we performed a comprehensive systems analysis of the infected brain: We identified susceptibility genes for congenital toxoplasmosis in our cohort of infected humans and found these genes are expressed in human brain. Transcriptomic and quantitative proteomic analyses of infected human, primary, neuronal stem and monocytic cells revealed effects on neurodevelopment and plasticity in neural, immune, and endocrine networks. These findings were supported by identification of protein and miRNA biomarkers in sera of ill children reflecting brain damage and T. gondii infection. These data were deconvoluted using three systems biology approaches: "Orbital-deconvolution" elucidated upstream, regulatory pathways interconnecting human susceptibility genes, biomarkers, proteomes, and transcriptomes. "Cluster-deconvolution" revealed visual protein-protein interaction clusters involved in processes affecting brain functions and circuitry, including lipid metabolism, leukocyte migration and olfaction. Finally, "disease-deconvolution" identified associations between the parasite-brain interactions and epilepsy, movement disorders, Alzheimer's disease, and cancer. This "reconstruction-deconvolution" logic provides templates of progenitor cells' potentiating effects, and components affecting human brain parasitism and diseases.

Peptide de novo sequencing of mixture tandem mass spectra.

PubMed

Gorshkov, Vladimir; Hotta, Stéphanie Yuki Kolbeck; Verano-Braga, Thiago; Kjeldsen, Frank

2016-09-01

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co-isolation and thus prone to false identifications. The deconvolution approach matched complementary b-, y-ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co-isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20-35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Epi-Fluorescence Microscopy

PubMed Central

Webb, Donna J.; Brown, Claire M.

2012-01-01

Epi-fluorescence microscopy is available in most life sciences research laboratories, and when optimized can be a central laboratory tool. In this chapter, the epi-fluorescence light path is introduced and the various components are discussed in detail. Recommendations are made for incident lamp light sources, excitation and emission filters, dichroic mirrors, objective lenses, and charge-coupled device (CCD) cameras in order to obtain the most sensitive epi-fluorescence microscope. The even illumination of metal-halide lamps combined with new “hard” coated filters and mirrors, a high resolution monochrome CCD camera, and a high NA objective lens are all recommended for high resolution and high sensitivity fluorescence imaging. Recommendations are also made for multicolor imaging with the use of monochrome cameras, motorized filter turrets, individual filter cubes, and corresponding dyes that are the best choice for sensitive, high resolution multicolor imaging. Images should be collected using Nyquist sampling and should be corrected for background intensity contributions and nonuniform illumination across the field of view. Photostable fluorescent probes and proteins that absorb a lot of light (i.e., high extinction co-efficients) and generate a lot of fluorescence signal (i.e., high quantum yields) are optimal. A neuronal immune-fluorescence labeling protocol is also presented. Finally, in order to maximize the utility of sensitive wide-field microscopes and generate the highest resolution images with high signal-to-noise, advice for combining wide-field epi-fluorescence imaging with restorative image deconvolution is presented. PMID:23026996

Electromagnetic-radiation absorption by water

NASA Astrophysics Data System (ADS)

Lunkenheimer, P.; Emmert, S.; Gulich, R.; Köhler, M.; Wolf, M.; Schwab, M.; Loidl, A.

2017-12-01

Why does a microwave oven work? How does biological tissue absorb electromagnetic radiation? Astonishingly, we do not have a definite answer to these simple questions because the microscopic processes governing the absorption of electromagnetic waves by water are largely unclarified. This absorption can be quantified by dielectric loss spectra, which reveal a huge peak at a frequency of the exciting electric field of about 20 GHz and a gradual tailing off toward higher frequencies. The microscopic interpretation of such spectra is highly controversial and various superpositions of relaxation and resonance processes ascribed to single-molecule or molecule-cluster motions have been proposed for their analysis. By combining dielectric, microwave, THz, and far-infrared spectroscopy, here we provide nearly continuous temperature-dependent broadband spectra of water. Moreover, we find that corresponding spectra for aqueous solutions reveal the same features as pure water. However, in contrast to the latter, crystallization in these solutions can be avoided by supercooling. As different spectral contributions tend to disentangle at low temperatures, this enables us to deconvolute them when approaching the glass transition under cooling. We find that the overall spectral development, including the 20 GHz feature (employed for microwave heating), closely resembles the behavior known for common supercooled liquids. Thus water's absorption of electromagnetic waves at room temperature is not unusual but very similar to that of glass-forming liquids at elevated temperatures, deep in the low-viscosity liquid regime, and should be interpreted along similar lines.

Gabor Deconvolution as Preliminary Method to Reduce Pitfall in Deeper Target Seismic Data

NASA Astrophysics Data System (ADS)

Oktariena, M.; Triyoso, W.

2018-03-01

Anelastic attenuation process during seismic wave propagation is the trigger of seismic non-stationary characteristic. An absorption and a scattering of energy are causing the seismic energy loss as the depth increasing. A series of thin reservoir layers found in the study area is located within Talang Akar Fm. Level, showing an indication of interpretation pitfall due to attenuation effect commonly occurred in deeper level seismic data. Attenuation effect greatly influences the seismic images of deeper target level, creating pitfalls in several aspect. Seismic amplitude in deeper target level often could not represent its real subsurface character due to a low amplitude value or a chaotic event nearing the Basement. Frequency wise, the decaying could be seen as the frequency content diminishing in deeper target. Meanwhile, seismic amplitude is the simple tool to point out Direct Hydrocarbon Indicator (DHI) in preliminary Geophysical study before a further advanced interpretation method applied. A quick-look of Post-Stack Seismic Data shows the reservoir associated with a bright spot DHI while another bigger bright spot body detected in the North East area near the field edge. A horizon slice confirms a possibility that the other bright spot zone has smaller delineation; an interpretation pitfall commonly occurs in deeper level of seismic. We evaluates this pitfall by applying Gabor Deconvolution to address the attenuation problem. Gabor Deconvolution forms a Partition of Unity to factorize the trace into smaller convolution window that could be processed as stationary packets. Gabor Deconvolution estimates both the magnitudes of source signature alongside its attenuation function. The enhanced seismic shows a better imaging in the pitfall area that previously detected as a vast bright spot zone. When the enhanced seismic is used for further advanced reprocessing process, the Seismic Impedance and Vp/Vs Ratio slices show a better reservoir delineation, in which the pitfall area is reduced and some morphed as background lithology. Gabor Deconvolution removes the attenuation by performing Gabor Domain spectral division, which in extension also reduces interpretation pitfall in deeper target seismic.

Towards robust deconvolution of low-dose perfusion CT: sparse perfusion deconvolution using online dictionary learning.

PubMed

Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C

2013-05-01

Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

Deconvolution of azimuthal mode detection measurements

NASA Astrophysics Data System (ADS)

Sijtsma, Pieter; Brouwer, Harry

2018-05-01

Unequally spaced transducer rings make it possible to extend the range of detectable azimuthal modes. The disadvantage is that the response of the mode detection algorithm to a single mode is distributed over all detectable modes, similarly to the Point Spread Function of Conventional Beamforming with microphone arrays. With multiple modes the response patterns interfere, leading to a relatively high "noise floor" of spurious modes in the detected mode spectrum, in other words, to a low dynamic range. In this paper a deconvolution strategy is proposed for increasing this dynamic range. It starts with separating the measured sound into shaft tones and broadband noise. For broadband noise modes, a standard Non-Negative Least Squares solver appeared to be a perfect deconvolution tool. For shaft tones a Matching Pursuit approach is proposed, taking advantage of the sparsity of dominant modes. The deconvolution methods were applied to mode detection measurements in a fan rig. An increase in dynamic range of typically 10-15 dB was found.

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1991-01-01

The final report for work on the determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution is presented. Papers and theses prepared during the research report period are included. Among all the research results reported, note should be made of the specific investigation of the determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution. A methodology was developed to determine design and operation parameters for error minimization when deconvolution is included in data analysis. An error surface is plotted versus the signal-to-noise ratio (SNR) and all parameters of interest. Instrumental characteristics will determine a curve in this space. The SNR and parameter values which give the projection from the curve to the surface, corresponding to the smallest value for the error, are the optimum values. These values are constrained by the curve and so will not necessarily correspond to an absolute minimum in the error surface.

Monitoring of Time-Dependent System Profiles by Multiplex Gas Chromatography with Maximum Entropy Demodulation

NASA Technical Reports Server (NTRS)

Becker, Joseph F.; Valentin, Jose

1996-01-01

The maximum entropy technique was successfully applied to the deconvolution of overlapped chromatographic peaks. An algorithm was written in which the chromatogram was represented as a vector of sample concentrations multiplied by a peak shape matrix. Simulation results demonstrated that there is a trade off between the detector noise and peak resolution in the sense that an increase of the noise level reduced the peak separation that could be recovered by the maximum entropy method. Real data originated from a sample storage column was also deconvoluted using maximum entropy. Deconvolution is useful in this type of system because the conservation of time dependent profiles depends on the band spreading processes in the chromatographic column, which might smooth out the finer details in the concentration profile. The method was also applied to the deconvolution of previously interpretted Pioneer Venus chromatograms. It was found in this case that the correct choice of peak shape function was critical to the sensitivity of maximum entropy in the reconstruction of these chromatograms.

Joint deconvolution and classification with applications to passive acoustic underwater multipath.

PubMed

Anderson, Hyrum S; Gupta, Maya R

2008-11-01

This paper addresses the problem of classifying signals that have been corrupted by noise and unknown linear time-invariant (LTI) filtering such as multipath, given labeled uncorrupted training signals. A maximum a posteriori approach to the deconvolution and classification is considered, which produces estimates of the desired signal, the unknown channel, and the class label. For cases in which only a class label is needed, the classification accuracy can be improved by not committing to an estimate of the channel or signal. A variant of the quadratic discriminant analysis (QDA) classifier is proposed that probabilistically accounts for the unknown LTI filtering, and which avoids deconvolution. The proposed QDA classifier can work either directly on the signal or on features whose transformation by LTI filtering can be analyzed; as an example a classifier for subband-power features is derived. Results on simulated data and real Bowhead whale vocalizations show that jointly considering deconvolution with classification can dramatically improve classification performance over traditional methods over a range of signal-to-noise ratios.

A new scoring function for top-down spectral deconvolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kou, Qiang; Wu, Si; Liu, Xiaowen

2014-12-18

Background: Top-down mass spectrometry plays an important role in intact protein identification and characterization. Top-down mass spectra are more complex than bottom-up mass spectra because they often contain many isotopomer envelopes from highly charged ions, which may overlap with one another. As a result, spectral deconvolution, which converts a complex top-down mass spectrum into a monoisotopic mass list, is a key step in top-down spectral interpretation. Results: In this paper, we propose a new scoring function, L-score, for evaluating isotopomer envelopes. By combining L-score with MS-Deconv, a new software tool, MS-Deconv+, was developed for top-down spectral deconvolution. Experimental results showedmore » that MS-Deconv+ outperformed existing software tools in top-down spectral deconvolution. Conclusions: L-score shows high discriminative ability in identification of isotopomer envelopes. Using L-score, MS-Deconv+ reports many correct monoisotopic masses missed by other software tools, which are valuable for proteoform identification and characterization.« less

Bayesian Deconvolution for Angular Super-Resolution in Forward-Looking Scanning Radar

PubMed Central

Zha, Yuebo; Huang, Yulin; Sun, Zhichao; Wang, Yue; Yang, Jianyu

2015-01-01

Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution of a scanning radar image is poor compared to the achievable range resolution. This paper presents a deconvolution algorithm for angular super-resolution in scanning radar based on Bayesian theory, which states that the angular super-resolution can be realized by solving the corresponding deconvolution problem with the maximum a posteriori (MAP) criterion. The algorithm considers that the noise is composed of two mutually independent parts, i.e., a Gaussian signal-independent component and a Poisson signal-dependent component. In addition, the Laplace distribution is used to represent the prior information about the targets under the assumption that the radar image of interest can be represented by the dominant scatters in the scene. Experimental results demonstrate that the proposed deconvolution algorithm has higher precision for angular super-resolution compared with the conventional algorithms, such as the Tikhonov regularization algorithm, the Wiener filter and the Richardson–Lucy algorithm. PMID:25806871

Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning

PubMed Central

Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C.

2014-01-01

Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. PMID:23542422

Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

NASA Astrophysics Data System (ADS)

Floberg, J. M.; Holden, J. E.

2013-02-01

We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications.

Processing of single channel air and water gun data for imaging an impact structure at the Chesapeake Bay

USGS Publications Warehouse

Lee, Myung W.

1999-01-01

Processing of 20 seismic profiles acquired in the Chesapeake Bay area aided in analysis of the details of an impact structure and allowed more accurate mapping of the depression caused by a bolide impact. Particular emphasis was placed on enhancement of seismic reflections from the basement. Application of wavelet deconvolution after a second zero-crossing predictive deconvolution improved the resolution of shallow reflections, and application of a match filter enhanced the basement reflections. The use of deconvolution and match filtering with a two-dimensional signal enhancement technique (F-X filtering) significantly improved the interpretability of seismic sections.

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: III. Convolution and deconvolution.

PubMed

Langenbucher, Frieder

2003-11-01

Convolution and deconvolution are the classical in-vitro-in-vivo correlation tools to describe the relationship between input and weighting/response in a linear system, where input represents the drug release in vitro, weighting/response any body response in vivo. While functional treatment, e.g. in terms of polyexponential or Weibull distribution, is more appropriate for general survey or prediction, numerical algorithms are useful for treating actual experimental data. Deconvolution is not considered an algorithm by its own, but the inversion of a corresponding convolution. MS Excel is shown to be a useful tool for all these applications.

High quality image-pair-based deblurring method using edge mask and improved residual deconvolution

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Zhao, Jufeng; Gao, Xiumin; Feng, Huajun; Chen, Yueting

2017-04-01

Image deconvolution problem is a challenging task in the field of image process. Using image pairs could be helpful to provide a better restored image compared with the deblurring method from a single blurred image. In this paper, a high quality image-pair-based deblurring method is presented using the improved RL algorithm and the gain-controlled residual deconvolution technique. The input image pair includes a non-blurred noisy image and a blurred image captured for the same scene. With the estimated blur kernel, an improved RL deblurring method based on edge mask is introduced to obtain the preliminary deblurring result with effective ringing suppression and detail preservation. Then the preliminary deblurring result is served as the basic latent image and the gain-controlled residual deconvolution is utilized to recover the residual image. A saliency weight map is computed as the gain map to further control the ringing effects around the edge areas in the residual deconvolution process. The final deblurring result is obtained by adding the preliminary deblurring result with the recovered residual image. An optical experimental vibration platform is set up to verify the applicability and performance of the proposed algorithm. Experimental results demonstrate that the proposed deblurring framework obtains a superior performance in both subjective and objective assessments and has a wide application in many image deblurring fields.

Windprofiler optimization using digital deconvolution procedures

NASA Astrophysics Data System (ADS)

Hocking, W. K.; Hocking, A.; Hocking, D. G.; Garbanzo-Salas, M.

2014-10-01

Digital improvements to data acquisition procedures used for windprofiler radars have the potential for improving the height coverage at optimum resolution, and permit improved height resolution. A few newer systems already use this capability. Real-time deconvolution procedures offer even further optimization, and this has not been effectively employed in recent years. In this paper we demonstrate the advantages of combining these features, with particular emphasis on the advantages of real-time deconvolution. Using several multi-core CPUs, we have been able to achieve speeds of up to 40 GHz from a standard commercial motherboard, allowing data to be digitized and processed without the need for any type of hardware except for a transmitter (and associated drivers), a receiver and a digitizer. No Digital Signal Processor chips are needed, allowing great flexibility with analysis algorithms. By using deconvolution procedures, we have then been able to not only optimize height resolution, but also have been able to make advances in dealing with spectral contaminants like ground echoes and other near-zero-Hz spectral contamination. Our results also demonstrate the ability to produce fine-resolution measurements, revealing small-scale structures within the backscattered echoes that were previously not possible to see. Resolutions of 30 m are possible for VHF radars. Furthermore, our deconvolution technique allows the removal of range-aliasing effects in real time, a major bonus in many instances. Results are shown using new radars in Canada and Costa Rica.

Grid indentation analysis of mechanical properties of composite electrodes in Li-ion batteries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vasconcelos, Luize Scalco de; Xu, Rong; Li, Jianlin

We report that electrodes in commercial rechargeable batteries are microscopically heterogeneous materials. The constituent components, including active materials, polymeric binders, and porous conductive matrix, often have large variation in their mechanical properties, making the mechanical characterization of composite electrodes a challenging task. In a model system of LiNi 0.5Mn 0.3Co 0.2O 2 cathode, we employ the instrumented grid indentation to determine the elastic modulus and hardness of the constituent phases. The approach relies on a large array of nanoindentation experiments and statistical analysis of the resulting data provided that the maximum indentation depth is carefully chosen. The statistically extracted propertiesmore » of the active particles and the surrounding medium are in good agreement with the tests of targeted indentation at selected sites. Lastly, the combinatory technique of grid indentation and statistical deconvolution represents a fast and reliable route to quantify the mechanical properties of composite electrodes that feed the parametric input for the mechanics models.« less

Grid indentation analysis of mechanical properties of composite electrodes in Li-ion batteries

DOE PAGES

Vasconcelos, Luize Scalco de; Xu, Rong; Li, Jianlin; ...

2016-03-09

We report that electrodes in commercial rechargeable batteries are microscopically heterogeneous materials. The constituent components, including active materials, polymeric binders, and porous conductive matrix, often have large variation in their mechanical properties, making the mechanical characterization of composite electrodes a challenging task. In a model system of LiNi 0.5Mn 0.3Co 0.2O 2 cathode, we employ the instrumented grid indentation to determine the elastic modulus and hardness of the constituent phases. The approach relies on a large array of nanoindentation experiments and statistical analysis of the resulting data provided that the maximum indentation depth is carefully chosen. The statistically extracted propertiesmore » of the active particles and the surrounding medium are in good agreement with the tests of targeted indentation at selected sites. Lastly, the combinatory technique of grid indentation and statistical deconvolution represents a fast and reliable route to quantify the mechanical properties of composite electrodes that feed the parametric input for the mechanics models.« less

Investigation of composition and structure of spongy and hard bone tissue using FTIR spectroscopy, XRD and SEM

NASA Astrophysics Data System (ADS)

Al-Akhras, M.-Ali H.; Hasan Qaseer, M. K.; Albiss, B. A.; Alebrhim, M. Anwar; Gezawa, Umar S.

2018-02-01

Valuable structural and chemical features can be obtained for spongy and hard bone by infrared spectroscopy and X-ray diffraction. A better understanding of chemical and structural differences between spongy and hard bone is a very important contributor to bone quality. Our data according to IR data showed that the collagen cross-links occurred to be higher in spongy bone, and crystallinity was lower in spongy bone. Deconvolution of the infrared band near 870 cm-1 reveals evidence for A2-type carbonate substitution on hydroxyapatite of spongy bone in addition to the A and B type carbonate substitution that are also found in hard bone. IR and XRD data confirmed the results of each other since full width at half maximum of 002-apatite pattern of XRD showed that the crystallinity was lower in spongy bone. The microstructure was examined by using scanning electron microscope and the result showed that the lattice of thin threads in spongy bone and is less dense than hard bone.

Physicochemical properties and micro-structural characteristics in starch from kudzu root as affected by cross-linking.

PubMed

Chen, Boru; Dang, Leping; Zhang, Xiao; Fang, Wenzhi; Hou, Mengna; Liu, Tiankuo; Wang, Zhanzhong

2017-03-15

Kudzu starch was cross-linked with sodium trimetaphosphate (STMP) at different temperatures, time and of STMP concentrations in this work. The cross-linked starches (CLSs) were fractionated further into cross-linked amylose and amylopectin in order to compare the effect of cross-linking on the microstructure. According to scanning electron microscope (SEM), CLSs displayed the resemble appearance of spherical and polygonal shapes like NS. X-ray diffraction (XRD) revealed that amylose of native starch (A), NS and CLS displayed a combination of A-type and B-type structure, while that was not found in amylose of cross-linked starch (CLA). The deconvoluted fourier transform infrared (FT-IR) indicated that crystal structure of kudzu starch was losing with the proceeding of cross-linking reaction. The CLSs exhibited a higher retrogradation and freeze-thaw stability than NS. This was accompanied by a significant decrease in sedimentation, transparency, swelling power and solubility. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial studies of planetary nebulae with IRAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hawkins, G.W.; Zuckerman, B.

1991-06-01

The infrared sizes at the four IRAS wavelengths of 57 planetaries, most with 20-60 arcsec optical size, are derived from spatial deconvolution of one-dimensional survey mode scans. Survey observations from multiple detectors and hours confirmed (HCON) observations are combined to increase the sampling to a rate that is sufficient for successful deconvolution. The Richardson-Lucy deconvolution algorithm is used to obtain an increase in resolution of a factor of about 2 or 3 from the normal IRAS detector sizes of 45, 45, 90, and 180 arcsec at wavelengths 12, 25, 60, and 100 microns. Most of the planetaries deconvolve at 12more » and 25 microns to sizes equal to or smaller than the optical size. Some of the planetaries with optical rings 60 arcsec or more in diameter show double-peaked IRAS profiles. Many, such as NGC 6720 and NGC 6543 show all infrared sizes equal to the optical size, while others indicate increasing infrared size with wavelength. Deconvolved IRAS profiles are presented for the 57 planetaries at nearly all wavelengths where IRAS flux densities are 1-2 Jy or higher. 60 refs.« less

Variation of High-Intensity Therapeutic Ultrasound (HITU) Pressure Field Characterization: Effects of Hydrophone Choice, Nonlinearity, Spatial Averaging and Complex Deconvolution.

PubMed

Liu, Yunbo; Wear, Keith A; Harris, Gerald R

2017-10-01

Reliable acoustic characterization is fundamental for patient safety and clinical efficacy during high-intensity therapeutic ultrasound (HITU) treatment. Technical challenges, such as measurement variation and signal analysis, still exist for HITU exposimetry using ultrasound hydrophones. In this work, four hydrophones were compared for pressure measurement: a robust needle hydrophone, a small polyvinylidene fluoride capsule hydrophone and two fiberoptic hydrophones. The focal waveform and beam distribution of a single-element HITU transducer (1.05 MHz and 3.3 MHz) were evaluated. Complex deconvolution between the hydrophone voltage signal and frequency-dependent complex sensitivity was performed to obtain pressure waveforms. Compressional pressure (p + ), rarefactional pressure (p - ) and focal beam distribution were compared up to 10.6/-6.0 MPa (p + /p - ) (1.05 MHz) and 20.65/-7.20 MPa (3.3 MHz). The effects of spatial averaging, local non-linear distortion, complex deconvolution and hydrophone damage thresholds were investigated. This study showed a variation of no better than 10%-15% among hydrophones during HITU pressure characterization. Published by Elsevier Inc.

Minimum entropy deconvolution optimized sinusoidal synthesis and its application to vibration based fault detection

NASA Astrophysics Data System (ADS)

Li, Gang; Zhao, Qing

2017-03-01

In this paper, a minimum entropy deconvolution based sinusoidal synthesis (MEDSS) filter is proposed to improve the fault detection performance of the regular sinusoidal synthesis (SS) method. The SS filter is an efficient linear predictor that exploits the frequency properties during model construction. The phase information of the harmonic components is not used in the regular SS filter. However, the phase relationships are important in differentiating noise from characteristic impulsive fault signatures. Therefore, in this work, the minimum entropy deconvolution (MED) technique is used to optimize the SS filter during the model construction process. A time-weighted-error Kalman filter is used to estimate the MEDSS model parameters adaptively. Three simulation examples and a practical application case study are provided to illustrate the effectiveness of the proposed method. The regular SS method and the autoregressive MED (ARMED) method are also implemented for comparison. The MEDSS model has demonstrated superior performance compared to the regular SS method and it also shows comparable or better performance with much less computational intensity than the ARMED method.

Thermoluminescence of nanocrystalline CaSO{sub 4}: Dy for gamma dosimetry and calculation of trapping parameters using deconvolution method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandlik, Nandkumar, E-mail: ntmandlik@gmail.com; Patil, B. J.; Bhoraskar, V. N.

2014-04-24

Nanorods of CaSO{sub 4}: Dy having diameter 20 nm and length 200 nm have been synthesized by the chemical coprecipitation method. These samples were irradiated with gamma radiation for the dose varying from 0.1 Gy to 50 kGy and their TL characteristics have been studied. TL dose response shows a linear behavior up to 5 kGy and further saturates with increase in the dose. A Computerized Glow Curve Deconvolution (CGCD) program was used for the analysis of TL glow curves. Trapping parameters for various peaks have been calculated by using CGCD program.

Thermoluminescence of nanocrystalline CaSO4: Dy for gamma dosimetry and calculation of trapping parameters using deconvolution method

NASA Astrophysics Data System (ADS)

Mandlik, Nandkumar; Patil, B. J.; Bhoraskar, V. N.; Sahare, P. D.; Dhole, S. D.

2014-04-01

Nanorods of CaSO4: Dy having diameter 20 nm and length 200 nm have been synthesized by the chemical coprecipitation method. These samples were irradiated with gamma radiation for the dose varying from 0.1 Gy to 50 kGy and their TL characteristics have been studied. TL dose response shows a linear behavior up to 5 kGy and further saturates with increase in the dose. A Computerized Glow Curve Deconvolution (CGCD) program was used for the analysis of TL glow curves. Trapping parameters for various peaks have been calculated by using CGCD program.

Strehl-constrained iterative blind deconvolution for post-adaptive-optics data

NASA Astrophysics Data System (ADS)

Desiderà, G.; Carbillet, M.

2009-12-01

Aims: We aim to improve blind deconvolution applied to post-adaptive-optics (AO) data by taking into account one of their basic characteristics, resulting from the necessarily partial AO correction: the Strehl ratio. Methods: We apply a Strehl constraint in the framework of iterative blind deconvolution (IBD) of post-AO near-infrared images simulated in a detailed end-to-end manner and considering a case that is as realistic as possible. Results: The results obtained clearly show the advantage of using such a constraint, from the point of view of both performance and stability, especially for poorly AO-corrected data. The proposed algorithm has been implemented in the freely-distributed and CAOS-based Software Package AIRY.

Calibration of a polarimetric imaging SAR

NASA Technical Reports Server (NTRS)

Sarabandi, K.; Pierce, L. E.; Ulaby, F. T.

1991-01-01

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

Histogram deconvolution - An aid to automated classifiers

NASA Technical Reports Server (NTRS)

Lorre, J. J.

1983-01-01

It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

PubMed

Rosen, I G; Luczak, Susan E; Weiss, Jordan

2014-03-15

We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

Point spread functions and deconvolution of ultrasonic images.

PubMed

Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten

2015-03-01

This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.

Deconvolution of astronomical images using SOR with adaptive relaxation.

PubMed

Vorontsov, S V; Strakhov, V N; Jefferies, S M; Borelli, K J

2011-07-04

We address the potential performance of the successive overrelaxation technique (SOR) in image deconvolution, focusing our attention on the restoration of astronomical images distorted by atmospheric turbulence. SOR is the classical Gauss-Seidel iteration, supplemented with relaxation. As indicated by earlier work, the convergence properties of SOR, and its ultimate performance in the deconvolution of blurred and noisy images, can be made competitive to other iterative techniques, including conjugate gradients, by a proper choice of the relaxation parameter. The question of how to choose the relaxation parameter, however, remained open, and in the practical work one had to rely on experimentation. In this paper, using constructive (rather than exact) arguments, we suggest a simple strategy for choosing the relaxation parameter and for updating its value in consecutive iterations to optimize the performance of the SOR algorithm (and its positivity-constrained version, +SOR) at finite iteration counts. We suggest an extension of the algorithm to the notoriously difficult problem of "blind" deconvolution, where both the true object and the point-spread function have to be recovered from the blurred image. We report the results of numerical inversions with artificial and real data, where the algorithm is compared with techniques based on conjugate gradients. In all of our experiments +SOR provides the highest quality results. In addition +SOR is found to be able to detect moderately small changes in the true object between separate data frames: an important quality for multi-frame blind deconvolution where stationarity of the object is a necesessity.

Deconvolution of ferredoxin, plastocyanin, and P700 transmittance changes in intact leaves with a new type of kinetic LED array spectrophotometer.

PubMed

Klughammer, Christof; Schreiber, Ulrich

2016-05-01

A newly developed compact measuring system for assessment of transmittance changes in the near-infrared spectral region is described; it allows deconvolution of redox changes due to ferredoxin (Fd), P700, and plastocyanin (PC) in intact leaves. In addition, it can also simultaneously measure chlorophyll fluorescence. The major opto-electronic components as well as the principles of data acquisition and signal deconvolution are outlined. Four original pulse-modulated dual-wavelength difference signals are measured (785-840 nm, 810-870 nm, 870-970 nm, and 795-970 nm). Deconvolution is based on specific spectral information presented graphically in the form of 'Differential Model Plots' (DMP) of Fd, P700, and PC that are derived empirically from selective changes of these three components under appropriately chosen physiological conditions. Whereas information on maximal changes of Fd is obtained upon illumination after dark-acclimation, maximal changes of P700 and PC can be readily induced by saturating light pulses in the presence of far-red light. Using the information of DMP and maximal changes, the new measuring system enables on-line deconvolution of Fd, P700, and PC. The performance of the new device is demonstrated by some examples of practical applications, including fast measurements of flash relaxation kinetics and of the Fd, P700, and PC changes paralleling the polyphasic fluorescence rise upon application of a 300-ms pulse of saturating light.

Photoacoustic imaging optimization with raw signal deconvolution and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Wang, Jing; Qin, Yu; Zhan, Hongchen; Yuan, Jie; Cheng, Qian; Wang, Xueding

2018-02-01

Photoacoustic (PA) signal of an ideal optical absorb particle is a single N-shape wave. PA signals of a complicated biological tissue can be considered as the combination of individual N-shape waves. However, the N-shape wave basis not only complicates the subsequent work, but also results in aliasing between adjacent micro-structures, which deteriorates the quality of the final PA images. In this paper, we propose a method to improve PA image quality through signal processing method directly working on raw signals, which including deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent point spread function (PSF) which is measured in advance. Then, EMD is adopted to adaptively re-shape the PA signals with two constraints, positive polarity and spectrum consistence. With our proposed method, the built PA images can yield more detail structural information. Micro-structures are clearly separated and revealed. To validate the effectiveness of this method, we present numerical simulations and phantom studies consist of a densely distributed point sources model and a blood vessel model. In the future, our study might hold the potential for clinical PA imaging as it can help to distinguish micro-structures from the optimized images and even measure the size of objects from deconvolved signals.

Approximate deconvolution model for the simulation of turbulent gas-solid flows: An a priori analysis

NASA Astrophysics Data System (ADS)

Schneiderbauer, Simon; Saeedipour, Mahdi

2018-02-01

Highly resolved two-fluid model (TFM) simulations of gas-solid flows in vertical periodic channels have been performed to study closures for the filtered drag force and the Reynolds-stress-like contribution stemming from the convective terms. An approximate deconvolution model (ADM) for the large-eddy simulation of turbulent gas-solid suspensions is detailed and subsequently used to reconstruct those unresolved contributions in an a priori manner. With such an approach, an approximation of the unfiltered solution is obtained by repeated filtering allowing the determination of the unclosed terms of the filtered equations directly. A priori filtering shows that predictions of the ADM model yield fairly good agreement with the fine grid TFM simulations for various filter sizes and different particle sizes. In particular, strong positive correlation (ρ > 0.98) is observed at intermediate filter sizes for all sub-grid terms. Additionally, our study reveals that the ADM results moderately depend on the choice of the filters, such as box and Gaussian filter, as well as the deconvolution order. The a priori test finally reveals that ADM is superior compared to isotropic functional closures proposed recently [S. Schneiderbauer, "A spatially-averaged two-fluid model for dense large-scale gas-solid flows," AIChE J. 63, 3544-3562 (2017)].

SU-E-I-08: Investigation of Deconvolution Methods for Blocker-Based CBCT Scatter Estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, C; Jin, M; Ouyang, L

2015-06-15

Purpose: To investigate whether deconvolution methods can improve the scatter estimation under different blurring and noise conditions for blocker-based scatter correction methods for cone-beam X-ray computed tomography (CBCT). Methods: An “ideal” projection image with scatter was first simulated for blocker-based CBCT data acquisition by assuming no blurring effect and no noise. The ideal image was then convolved with long-tail point spread functions (PSF) with different widths to mimic the blurring effect from the finite focal spot and detector response. Different levels of noise were also added. Three deconvolution Methods: 1) inverse filtering; 2) Wiener; and 3) Richardson-Lucy, were used tomore » recover the scatter signal in the blocked region. The root mean square error (RMSE) of estimated scatter serves as a quantitative measure for the performance of different methods under different blurring and noise conditions. Results: Due to the blurring effect, the scatter signal in the blocked region is contaminated by the primary signal in the unblocked region. The direct use of the signal in the blocked region to estimate scatter (“direct method”) leads to large RMSE values, which increase with the increased width of PSF and increased noise. The inverse filtering is very sensitive to noise and practically useless. The Wiener and Richardson-Lucy deconvolution methods significantly improve scatter estimation compared to the direct method. For a typical medium PSF and medium noise condition, both methods (∼20 RMSE) can achieve 4-fold improvement over the direct method (∼80 RMSE). The Wiener method deals better with large noise and Richardson-Lucy works better on wide PSF. Conclusion: We investigated several deconvolution methods to recover the scatter signal in the blocked region for blocker-based scatter correction for CBCT. Our simulation results demonstrate that Wiener and Richardson-Lucy deconvolution can significantly improve the scatter estimation compared to the direct method.« less

Electromagnetic-radiation absorption by water.

PubMed

Lunkenheimer, P; Emmert, S; Gulich, R; Köhler, M; Wolf, M; Schwab, M; Loidl, A

2017-12-01

Why does a microwave oven work? How does biological tissue absorb electromagnetic radiation? Astonishingly, we do not have a definite answer to these simple questions because the microscopic processes governing the absorption of electromagnetic waves by water are largely unclarified. This absorption can be quantified by dielectric loss spectra, which reveal a huge peak at a frequency of the exciting electric field of about 20 GHz and a gradual tailing off toward higher frequencies. The microscopic interpretation of such spectra is highly controversial and various superpositions of relaxation and resonance processes ascribed to single-molecule or molecule-cluster motions have been proposed for their analysis. By combining dielectric, microwave, THz, and far-infrared spectroscopy, here we provide nearly continuous temperature-dependent broadband spectra of water. Moreover, we find that corresponding spectra for aqueous solutions reveal the same features as pure water. However, in contrast to the latter, crystallization in these solutions can be avoided by supercooling. As different spectral contributions tend to disentangle at low temperatures, this enables us to deconvolute them when approaching the glass transition under cooling. We find that the overall spectral development, including the 20 GHz feature (employed for microwave heating), closely resembles the behavior known for common supercooled liquids. Thus water's absorption of electromagnetic waves at room temperature is not unusual but very similar to that of glass-forming liquids at elevated temperatures, deep in the low-viscosity liquid regime, and should be interpreted along similar lines.

Heterodyne Interferometry with a Scanning Optical Microscope.

NASA Astrophysics Data System (ADS)

Hobbs, Philip Charles Danby

The design and implementation of a confocal optical microscope which functions as an electronically scanned heterodyne interferometer are described. Theoretical models based on Fourier optics for general samples and on exact series solution of the scalar Helmholtz equation for a class of trench structures are developed and compared with experimental data. Good agreement is obtained. The associated data acquisition system, also described, enables the system to measure both the amplitude (to 12 bits) and the phase (to 0.1^circ) of a returned optical beam, at a continuous rate of 30,000 points per second. The microscope system uses a wide-band tellurium dioxide acousto-optic cell for electronic scanning, frequency shifting, and beam splitting/combining. It uses a stationary reference beam on the sample for vibration cancellation, which results in a system of great vibration immunity. It can measure relief ranging from a few tenths of a micron down to a few Angstroms, and line widths down to well below 0.4 micron, using light of 0.5 micron wavelength. Angstrom resolution can be achieved in a single full-speed scan, without special vibration isolation equipment, providing that folding mirrors are avoided. A signal processing algorithm based on Fourier deconvolution is presented; it takes advantage of the extra bandwidth of a confocal system and the availability of both amplitude and phase, to improve the lateral resolution by approximately a factor of two. Experimental results are shown, which demonstrate phase edge resolution (10%-90%) of 0.45 lambda (raw data), and 0.18 lambda (after filtering), in excellent agreement with the Fourier optics prediction. The exact scalar theory calculates the response of the microscope as it scans over an infinitely long rectangular trench in a plane boundary on which Dirichlet boundary conditions apply. An expansion in cavity modes inside the trench is used to match the field and its derivatives across the mouth of the trench to get the self-consistent solution. A listing is appended of a program for an HP personal computer which performs the simulation in 1 to 5 minutes' running time for most cases. The trench theory is compared with the Fourier theory and with experimental results for actual metal trenches, with good results.

Spectrophotometric Determination of the Dissociation Constant of an Acid-Base Indicator Using a Mathematical Deconvolution Technique

ERIC Educational Resources Information Center

Alter, Krystyn P.; Molloy, John L.; Niemeyer, Emily D.

2005-01-01

A laboratory experiment reinforces the concept of acid-base equilibria while introducing a common application of spectrophotometry and can easily be completed within a standard four-hour laboratory period. It provides students with an opportunity to use advanced data analysis techniques like data smoothing and spectral deconvolution to…

Deconvolution of Energy Spectra in the ATIC Experiment

NASA Technical Reports Server (NTRS)

Batkov, K. E.; Panov, A. D.; Adams, J. H.; Ahn, H. S.; Bashindzhagyan, G. L.; Chang, J.; Christl, M.; Fazley, A. R.; Ganel, O.; Gunasigha, R. M.;

Sequential deconvolution from wave-front sensing using bivariate simplex splines

NASA Astrophysics Data System (ADS)

Guo, Shiping; Zhang, Rongzhi; Li, Jisheng; Zou, Jianhua; Xu, Rong; Liu, Changhai

2015-05-01

Deconvolution from wave-front sensing (DWFS) is an imaging compensation technique for turbulence degraded images based on simultaneous recording of short exposure images and wave-front sensor data. This paper employs the multivariate splines method for the sequential DWFS: a bivariate simplex splines based average slopes measurement model is built firstly for Shack-Hartmann wave-front sensor; next, a well-conditioned least squares estimator for the spline coefficients is constructed using multiple Shack-Hartmann measurements; then, the distorted wave-front is uniquely determined by the estimated spline coefficients; the object image is finally obtained by non-blind deconvolution processing. Simulated experiments in different turbulence strength show that our method performs superior image restoration results and noise rejection capability especially when extracting the multidirectional phase derivatives.

Study of the Auger line shape of polyethylene and diamond

NASA Technical Reports Server (NTRS)

Dayan, M.; Pepper, S. V.

1984-01-01

The KVV Auger electron line shapes of carbon in polyethylene and diamond have been studied. The spectra were obtained in derivative form by electron beam excitation. They were treated by background subtraction, integration and deconvolution to produce the intrinsic Auger line shape. Electron energy loss spectra provided the response function in the deconvolution procedure. The line shape from polyethylene is compared with spectra from linear alkanes and with a previous spectrum of Kelber et al. Both spectra are compared with the self-convolution of their full valence band densities of states and of their p-projected densities. The experimental spectra could not be understood in terms of existing theories. This is so even when correlation effects are qualitatively taken into account account to the theories of Cini and Sawatzky and Lenselink.

Digital sorting of complex tissues for cell type-specific gene expression profiles.

PubMed

Zhong, Yi; Wan, Ying-Wooi; Pang, Kaifang; Chow, Lionel M L; Liu, Zhandong

2013-03-07

Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in vitro expression profiles. Furthermore, these algorithms tend to report biased estimations. Here, we describe a Digital Sorting Algorithm (DSA) for extracting cell-type specific gene expression profiles from mixed tissue samples that is unbiased and does not require prior knowledge of cell type frequencies. The results suggest that DSA is a specific and sensitivity algorithm in gene expression profile deconvolution and will be useful in studying individual cell types of complex tissues.

DECONVOLUTION OF IMAGES FROM BLAST 2005: INSIGHT INTO THE K3-50 AND IC 5146 STAR-FORMING REGIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy, Arabindo; Netterfield, Calvin B.; Ade, Peter A. R.

2011-04-01

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed itsmore » performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4.'5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and {sup 12}CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below {approx} 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.« less

Deconvolution of Images from BLAST 2005: Insight into the K3-50 and IC 5146 Star-forming Regions

NASA Astrophysics Data System (ADS)

Roy, Arabindo; Ade, Peter A. R.; Bock, James J.; Brunt, Christopher M.; Chapin, Edward L.; Devlin, Mark J.; Dicker, Simon R.; France, Kevin; Gibb, Andrew G.; Griffin, Matthew; Gundersen, Joshua O.; Halpern, Mark; Hargrave, Peter C.; Hughes, David H.; Klein, Jeff; Marsden, Gaelen; Martin, Peter G.; Mauskopf, Philip; Netterfield, Calvin B.; Olmi, Luca; Patanchon, Guillaume; Rex, Marie; Scott, Douglas; Semisch, Christopher; Truch, Matthew D. P.; Tucker, Carole; Tucker, Gregory S.; Viero, Marco P.; Wiebe, Donald V.

2011-04-01

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed its performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4farcm5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and 12CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below ~ 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.

Application of Deconvolution Algorithm of Point Spread Function in Improving Image Quality: An Observer Preference Study on Chest Radiography.

PubMed

Chae, Kum Ju; Goo, Jin Mo; Ahn, Su Yeon; Yoo, Jin Young; Yoon, Soon Ho

2018-01-01

To evaluate the preference of observers for image quality of chest radiography using the deconvolution algorithm of point spread function (PSF) (TRUVIEW ART algorithm, DRTECH Corp.) compared with that of original chest radiography for visualization of anatomic regions of the chest. Prospectively enrolled 50 pairs of posteroanterior chest radiographs collected with standard protocol and with additional TRUVIEW ART algorithm were compared by four chest radiologists. This algorithm corrects scattered signals generated by a scintillator. Readers independently evaluated the visibility of 10 anatomical regions and overall image quality with a 5-point scale of preference. The significance of the differences in reader's preference was tested with a Wilcoxon's signed rank test. All four readers preferred the images applied with the algorithm to those without algorithm for all 10 anatomical regions (mean, 3.6; range, 3.2-4.0; p < 0.001) and for the overall image quality (mean, 3.8; range, 3.3-4.0; p < 0.001). The most preferred anatomical regions were the azygoesophageal recess, thoracic spine, and unobscured lung. The visibility of chest anatomical structures applied with the deconvolution algorithm of PSF was superior to the original chest radiography.

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

NASA Technical Reports Server (NTRS)

Pan, Jianqiang

1992-01-01

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

Generative adversarial networks recover features in astrophysical images of galaxies beyond the deconvolution limit

NASA Astrophysics Data System (ADS)

Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Santhanam, Gokula Krishnan

2017-05-01

Observations of astrophysical objects such as galaxies are limited by various sources of random and systematic noise from the sky background, the optical system of the telescope and the detector used to record the data. Conventional deconvolution techniques are limited in their ability to recover features in imaging data by the Shannon-Nyquist sampling theorem. Here, we train a generative adversarial network (GAN) on a sample of 4550 images of nearby galaxies at 0.01 < z < 0.02 from the Sloan Digital Sky Survey and conduct 10× cross-validation to evaluate the results. We present a method using a GAN trained on galaxy images that can recover features from artificially degraded images with worse seeing and higher noise than the original with a performance that far exceeds simple deconvolution. The ability to better recover detailed features such as galaxy morphology from low signal to noise and low angular resolution imaging data significantly increases our ability to study existing data sets of astrophysical objects as well as future observations with observatories such as the Large Synoptic Sky Telescope (LSST) and the Hubble and James Webb space telescopes.

Efficient volumetric estimation from plenoptic data

NASA Astrophysics Data System (ADS)

Anglin, Paul; Reeves, Stanley J.; Thurow, Brian S.

2013-03-01

The commercial release of the Lytro camera, and greater availability of plenoptic imaging systems in general, have given the image processing community cost-effective tools for light-field imaging. While this data is most commonly used to generate planar images at arbitrary focal depths, reconstruction of volumetric fields is also possible. Similarly, deconvolution is a technique that is conventionally used in planar image reconstruction, or deblurring, algorithms. However, when leveraged with the ability of a light-field camera to quickly reproduce multiple focal planes within an imaged volume, deconvolution offers a computationally efficient method of volumetric reconstruction. Related research has shown than light-field imaging systems in conjunction with tomographic reconstruction techniques are also capable of estimating the imaged volume and have been successfully applied to particle image velocimetry (PIV). However, while tomographic volumetric estimation through algorithms such as multiplicative algebraic reconstruction techniques (MART) have proven to be highly accurate, they are computationally intensive. In this paper, the reconstruction problem is shown to be solvable by deconvolution. Deconvolution offers significant improvement in computational efficiency through the use of fast Fourier transforms (FFTs) when compared to other tomographic methods. This work describes a deconvolution algorithm designed to reconstruct a 3-D particle field from simulated plenoptic data. A 3-D extension of existing 2-D FFT-based refocusing techniques is presented to further improve efficiency when computing object focal stacks and system point spread functions (PSF). Reconstruction artifacts are identified; their underlying source and methods of mitigation are explored where possible, and reconstructions of simulated particle fields are provided.

VizieR Online Data Catalog: Spatial deconvolution code (Quintero Noda+, 2015)

NASA Astrophysics Data System (ADS)

Quintero Noda, C.; Asensio Ramos, A.; Orozco Suarez, D.; Ruiz Cobo, B.

2015-05-01

This deconvolution method follows the scheme presented in Ruiz Cobo & Asensio Ramos (2013A&A...549L...4R) The Stokes parameters are projected onto a few spectral eigenvectors and the ensuing maps of coefficients are deconvolved using a standard Lucy-Richardson algorithm. This introduces a stabilization because the PCA filtering reduces the amount of noise. (1 data file).

A method to measure the presampling MTF in digital radiography using Wiener deconvolution

NASA Astrophysics Data System (ADS)

Zhou, Zhongxing; Zhu, Qingzhen; Gao, Feng; Zhao, Huijuan; Zhang, Lixin; Li, Guohui

2013-03-01

We developed a novel method for determining the presampling modulation transfer function (MTF) of digital radiography systems from slanted edge images based on Wiener deconvolution. The degraded supersampled edge spread function (ESF) was obtained from simulated slanted edge images with known MTF in the presence of poisson noise, and its corresponding ideal ESF without degration was constructed according to its central edge position. To meet the requirements of the absolute integrable condition of Fourier transformation, the origianl ESFs were mirrored to construct the symmetric pattern of ESFs. Then based on Wiener deconvolution technique, the supersampled line spread function (LSF) could be acquired from the symmetric pattern of degraded supersampled ESFs in the presence of ideal symmetric ESFs and system noise. The MTF is then the normalized magnitude of the Fourier transform of the LSF. The determined MTF showed a strong agreement with the theoritical true MTF when appropriated Wiener parameter was chosen. The effects of Wiener parameter value and the width of square-like wave peak in symmetric ESFs were illustrated and discussed. In conclusion, an accurate and simple method to measure the presampling MTF was established using Wiener deconvolution technique according to slanted edge images.

Deconvolution of interferometric data using interior point iterative algorithms

NASA Astrophysics Data System (ADS)

Theys, C.; Lantéri, H.; Aime, C.

2016-09-01

We address the problem of deconvolution of astronomical images that could be obtained with future large interferometers in space. The presentation is made in two complementary parts. The first part gives an introduction to the image deconvolution with linear and nonlinear algorithms. The emphasis is made on nonlinear iterative algorithms that verify the constraints of non-negativity and constant flux. The Richardson-Lucy algorithm appears there as a special case for photon counting conditions. More generally, the algorithm published recently by Lanteri et al. (2015) is based on scale invariant divergences without assumption on the statistic model of the data. The two proposed algorithms are interior-point algorithms, the latter being more efficient in terms of speed of calculation. These algorithms are applied to the deconvolution of simulated images corresponding to an interferometric system of 16 diluted telescopes in space. Two non-redundant configurations, one disposed around a circle and the other on an hexagonal lattice, are compared for their effectiveness on a simple astronomical object. The comparison is made in the direct and Fourier spaces. Raw "dirty" images have many artifacts due to replicas of the original object. Linear methods cannot remove these replicas while iterative methods clearly show their efficacy in these examples.

Image deblurring by motion estimation for remote sensing

NASA Astrophysics Data System (ADS)

Chen, Yueting; Wu, Jiagu; Xu, Zhihai; Li, Qi; Feng, Huajun

2010-08-01

The imagery resolution of imaging systems for remote sensing is often limited by image degradation resulting from unwanted motion disturbances of the platform during image exposures. Since the form of the platform vibration can be arbitrary, the lack of priori knowledge about the motion function (the PSF) suggests blind restoration approaches. A deblurring method which combines motion estimation and image deconvolution both for area-array and TDI remote sensing has been proposed in this paper. The image motion estimation is accomplished by an auxiliary high-speed detector and a sub-pixel correlation algorithm. The PSF is then reconstructed from estimated image motion vectors. Eventually, the clear image can be recovered by the Richardson-Lucy (RL) iterative deconvolution algorithm from the blurred image of the prime camera with the constructed PSF. The image deconvolution for the area-array detector is direct. While for the TDICCD detector, an integral distortion compensation step and a row-by-row deconvolution scheme are applied. Theoretical analyses and experimental results show that, the performance of the proposed concept is convincing. Blurred and distorted images can be properly recovered not only for visual observation, but also with significant objective evaluation increment.

Chemometric Data Analysis for Deconvolution of Overlapped Ion Mobility Profiles

NASA Astrophysics Data System (ADS)

Zekavat, Behrooz; Solouki, Touradj

2012-11-01

We present the details of a data analysis approach for deconvolution of the ion mobility (IM) overlapped or unresolved species. This approach takes advantage of the ion fragmentation variations as a function of the IM arrival time. The data analysis involves the use of an in-house developed data preprocessing platform for the conversion of the original post-IM/collision-induced dissociation mass spectrometry (post-IM/CID MS) data to a Matlab compatible format for chemometric analysis. We show that principle component analysis (PCA) can be used to examine the post-IM/CID MS profiles for the presence of mobility-overlapped species. Subsequently, using an interactive self-modeling mixture analysis technique, we show how to calculate the total IM spectrum (TIMS) and CID mass spectrum for each component of the IM overlapped mixtures. Moreover, we show that PCA and IM deconvolution techniques provide complementary results to evaluate the validity of the calculated TIMS profiles. We use two binary mixtures with overlapping IM profiles, including (1) a mixture of two non-isobaric peptides (neurotensin (RRPYIL) and a hexapeptide (WHWLQL)), and (2) an isobaric sugar isomer mixture of raffinose and maltotriose, to demonstrate the applicability of the IM deconvolution.

Designing a stable feedback control system for blind image deconvolution.

PubMed

Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan

2018-05-01

Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impact of sensor's point spread function on land cover characterization: Assessment and deconvolution

USGS Publications Warehouse

Huang, C.; Townshend, J.R.G.; Liang, S.; Kalluri, S.N.V.; DeFries, R.S.

2002-01-01

Measured and modeled point spread functions (PSF) of sensor systems indicate that a significant portion of the recorded signal of each pixel of a satellite image originates from outside the area represented by that pixel. This hinders the ability to derive surface information from satellite images on a per-pixel basis. In this study, the impact of the PSF of the Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m bands was assessed using four images representing different landscapes. Experimental results showed that though differences between pixels derived with and without PSF effects were small on the average, the PSF generally brightened dark objects and darkened bright objects. This impact of the PSF lowered the performance of a support vector machine (SVM) classifier by 5.4% in overall accuracy and increased the overall root mean square error (RMSE) by 2.4% in estimating subpixel percent land cover. An inversion method based on the known PSF model reduced the signals originating from surrounding areas by as much as 53%. This method differs from traditional PSF inversion deconvolution methods in that the PSF was adjusted with lower weighting factors for signals originating from neighboring pixels than those specified by the PSF model. By using this deconvolution method, the lost classification accuracy due to residual impact of PSF effects was reduced to only 1.66% in overall accuracy. The increase in the RMSE of estimated subpixel land cover proportions due to the residual impact of PSF effects was reduced to 0.64%. Spatial aggregation also effectively reduced the errors in estimated land cover proportion images. About 50% of the estimation errors were removed after applying the deconvolution method and aggregating derived proportion images to twice their dimensional pixel size. ?? 2002 Elsevier Science Inc. All rights reserved.

A gene profiling deconvolution approach to estimating immune cell composition from complex tissues.

PubMed

Chen, Shu-Hwa; Kuo, Wen-Yu; Su, Sheng-Yao; Chung, Wei-Chun; Ho, Jen-Ming; Lu, Henry Horng-Shing; Lin, Chung-Yen

2018-05-08

A new emerged cancer treatment utilizes intrinsic immune surveillance mechanism that is silenced by those malicious cells. Hence, studies of tumor infiltrating lymphocyte populations (TILs) are key to the success of advanced treatments. In addition to laboratory methods such as immunohistochemistry and flow cytometry, in silico gene expression deconvolution methods are available for analyses of relative proportions of immune cell types. Herein, we used microarray data from the public domain to profile gene expression pattern of twenty-two immune cell types. Initially, outliers were detected based on the consistency of gene profiling clustering results and the original cell phenotype notation. Subsequently, we filtered out genes that are expressed in non-hematopoietic normal tissues and cancer cells. For every pair of immune cell types, we ran t-tests for each gene, and defined differentially expressed genes (DEGs) from this comparison. Equal numbers of DEGs were then collected as candidate lists and numbers of conditions and minimal values for building signature matrixes were calculated. Finally, we used v -Support Vector Regression to construct a deconvolution model. The performance of our system was finally evaluated using blood biopsies from 20 adults, in which 9 immune cell types were identified using flow cytometry. The present computations performed better than current state-of-the-art deconvolution methods. Finally, we implemented the proposed method into R and tested extensibility and usability on Windows, MacOS, and Linux operating systems. The method, MySort, is wrapped as the Galaxy platform pluggable tool and usage details are available at https://testtoolshed.g2.bx.psu.edu/view/moneycat/mysort/e3afe097e80a .

Transformation of chlorinated paraffins to olefins during metal work and thermal exposure - Deconvolution of mass spectra and kinetics.

PubMed

Schinkel, Lena; Lehner, Sandro; Knobloch, Marco; Lienemann, Peter; Bogdal, Christian; McNeill, Kristopher; Heeb, Norbert V

2018-03-01

Chlorinated paraffins (CPs) are high production volume chemicals widely used as additives in metal working fluids. Thereby, CPs are exposed to hot metal surfaces which may induce degradation processes. We hypothesized that the elimination of hydrochloric acid would transform CPs into chlorinated olefins (COs). Mass spectrometry is widely used to detect CPs, mostly in the selected ion monitoring mode (SIM) evaluating 2-3 ions at mass resolutions R < 20'000. This approach is not suited to detected COs, because their mass spectra strongly overlap with CPs. We applied a mathematical deconvolution method based on full-scan MS data to separate interfered CP/CO spectra. Metal drilling indeed induced HCl-losses. CO proportions in exposed mixtures of chlorotridecanes increased. Thermal exposure of chlorotridecanes at 160, 180, 200 and 220 °C also induced dehydrohalogenation reactions and CO proportions also increased. Deconvolution of respective mass spectra is needed to study the CP transformation kinetics without bias from CO interferences. Apparent first-order rate constants (k app ) increased up to 0.17, 0.29 and 0.46 h -1 for penta-, hexa- and heptachloro-tridecanes exposed at 220 °C. Respective half-life times (τ 1/2 ) decreased from 4.0 to 2.4 and 1.5 h. Thus, higher chlorinated paraffins degrade faster than lower chlorinated ones. In conclusion, exposure of CPs during metal drilling and thermal treatment induced HCl losses and CO formation. It is expected that CPs and COs are co-released from such processes. Full-scan mass spectra and subsequent deconvolution of interfered signals is a promising approach to tackle the CP/CO problem, in case of insufficient mass resolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Acceleration of image-based resolution modelling reconstruction using an expectation maximization nested algorithm.

PubMed

Angelis, G I; Reader, A J; Markiewicz, P J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2013-08-07

Recent studies have demonstrated the benefits of a resolution model within iterative reconstruction algorithms in an attempt to account for effects that degrade the spatial resolution of the reconstructed images. However, these algorithms suffer from slower convergence rates, compared to algorithms where no resolution model is used, due to the additional need to solve an image deconvolution problem. In this paper, a recently proposed algorithm, which decouples the tomographic and image deconvolution problems within an image-based expectation maximization (EM) framework, was evaluated. This separation is convenient, because more computational effort can be placed on the image deconvolution problem and therefore accelerate convergence. Since the computational cost of solving the image deconvolution problem is relatively small, multiple image-based EM iterations do not significantly increase the overall reconstruction time. The proposed algorithm was evaluated using 2D simulations, as well as measured 3D data acquired on the high-resolution research tomograph. Results showed that bias reduction can be accelerated by interleaving multiple iterations of the image-based EM algorithm solving the resolution model problem, with a single EM iteration solving the tomographic problem. Significant improvements were observed particularly for voxels that were located on the boundaries between regions of high contrast within the object being imaged and for small regions of interest, where resolution recovery is usually more challenging. Minor differences were observed using the proposed nested algorithm, compared to the single iteration normally performed, when an optimal number of iterations are performed for each algorithm. However, using the proposed nested approach convergence is significantly accelerated enabling reconstruction using far fewer tomographic iterations (up to 70% fewer iterations for small regions). Nevertheless, the optimal number of nested image-based EM iterations is hard to be defined and it should be selected according to the given application.

Multi-limit unsymmetrical MLIBD image restoration algorithm

NASA Astrophysics Data System (ADS)

Yang, Yang; Cheng, Yiping; Chen, Zai-wang; Bo, Chen

2012-11-01

A novel multi-limit unsymmetrical iterative blind deconvolution(MLIBD) algorithm was presented to enhance the performance of adaptive optics image restoration.The algorithm enhances the reliability of iterative blind deconvolution by introducing the bandwidth limit into the frequency domain of point spread(PSF),and adopts the PSF dynamic support region estimation to improve the convergence speed.The unsymmetrical factor is automatically computed to advance its adaptivity.Image deconvolution comparing experiments between Richardson-Lucy IBD and MLIBD were done,and the result indicates that the iteration number is reduced by 22.4% and the peak signal-to-noise ratio is improved by 10.18dB with MLIBD method. The performance of MLIBD algorithm is outstanding in the images restoration the FK5-857 adaptive optics and the double-star adaptive optics.

Upconversion microparticles as time-resolved luminescent probes for multiphoton microscopy: desired signal extraction from the streaking effect

NASA Astrophysics Data System (ADS)

Pominova, Daria V.; Ryabova, Anastasia V.; Grachev, Pavel V.; Romanishkin, Igor D.; Kuznetsov, Sergei V.; Rozhnova, Julia A.; Yasyrkina, Daria S.; Fedorov, Pavel P.; Loschenov, Victor B.

2016-09-01

The great interest in upconversion nanoparticles exists due to their high efficiency under multiphoton excitation. However, when these particles are used in scanning microscopy, the upconversion luminescence causes a streaking effect due to the long lifetime. This article describes a method of upconversion microparticle luminescence lifetime determination with help of modified Lucy-Richardson deconvolution of laser scanning microscope (LSM) image obtained under near-IR excitation using nondescanned detectors. Determination of the upconversion luminescence intensity and the decay time of separate microparticles was done by intensity profile along the image fast scan axis approximation. We studied upconversion submicroparticles based on fluoride hosts doped with Yb3+-Er3+ and Yb3+-Tm3+ rare earth ion pairs, and the characteristic decay times were 0.1 to 1.5 ms. We also compared the results of LSM measurements with the photon counting method results; the spread of values was about 13% and was associated with the approximation error. Data obtained from live cells showed the possibility of distinguishing the position of upconversion submicroparticles inside and outside the cells by the difference of their lifetime. The proposed technique allows using the upconversion microparticles without shells as probes for the presence of OH- ions and CO2 molecules.

3-D reconstruction of neurons from multichannel confocal laser scanning image series.

PubMed

Wouterlood, Floris G

2014-04-10

A confocal laser scanning microscope (CLSM) collects information from a thin, focal plane and ignores out-of-focus information. Scanning of a specimen, with stepwise axial (Z-) movement of the stage in between each scan, produces Z-series of confocal images of a tissue volume, which then can be used to 3-D reconstruct structures of interest. The operator first configures separate channels (e.g., laser, filters, and detector settings) for each applied fluorochrome and then acquires Z-series of confocal images: one series per channel. Channel signal separation is extremely important. Measures to avoid bleaching are vital. Post-acquisition deconvolution of the image series is often performed to increase resolution before 3-D reconstruction takes place. In the 3-D reconstruction programs described in this unit, reconstructions can be inspected in real time from any viewing angle. By altering viewing angles and by switching channels off and on, the spatial relationships of 3-D-reconstructed structures with respect to structures visualized in other channels can be studied. Since each brand of CLSM, computer program, and 3-D reconstruction package has its own proprietary set of procedures, a general approach is provided in this protocol wherever possible. Copyright © 2014 John Wiley & Sons, Inc.

Quantitative classification of cryptosporidium oocysts and giardia cysts in water using UV/vis spectroscopy

NASA Astrophysics Data System (ADS)

Bacon, Christina P.; Rose, J. B.; Patten, K.; Garcia-Rubio, Luis H.

1995-05-01

Cryptosporidium and Giardia are enteric protozoa which cause waterborne diseases. To date, the detection of these organisms in water has relied upon microscopic immunofluorescent assay technology which uses antibodies directed against the cyst and oocyst forms of the protozoa. In this paper, the uv/vis extinction spectra of aqueous dispersions of Cryptosporidium and Giardia have been studied to investigate the potential use of light scattering-spectral deconvolution techniques as a rapid method for the identification and quantification of protozoa in water. Examination of purified samples of Cryptosporidium and Giardia suggests that spectral features apparent in the short wavelength region of the uv/vis spectra contain information that may be species specific for each protozoa. The spectral characteristics, as well as the particle size analysis, determined from the same spectra, allow for the quantitative classification, identification, and possibly, the assessment of the viability of the protozoa. To further increase the sensitivity of this technique, specific antibodies direction against these organisms, labelled with FITC and rhodamine are being used. It is demonstrated that uv/vis spectroscopy provides an alternative method for the characterization of Giardia and Cryptosporidium. The simplicity and reproducibility of uv/vis spectroscopy measurements makes this technique ideally suited for the development of on-line instrumentation for the rapid detection of microorganisms in water supplies.

A Comparative Study of Different Deblurring Methods Using Filters

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Kavitha, S.

2011-12-01

This paper attempts to undertake the study of Restored Gaussian Blurred Images by using four types of techniques of deblurring image viz., Wiener filter, Regularized filter, Lucy Richardson deconvolution algorithm and Blind deconvolution algorithm with an information of the Point Spread Function (PSF) corrupted blurred image. The same is applied to the scanned image of seven months baby in the womb and they are compared with one another, so as to choose the best technique for restored or deblurring image. This paper also attempts to undertake the study of restored blurred image using Regualr Filter(RF) with no information about the Point Spread Function (PSF) by using the same four techniques after executing the guess of the PSF. The number of iterations and the weight threshold of it to choose the best guesses for restored or deblurring image of these techniques are determined.

A MAP blind image deconvolution algorithm with bandwidth over-constrained

NASA Astrophysics Data System (ADS)

Ren, Zhilei; Liu, Jin; Liang, Yonghui; He, Yulong

2018-03-01

We demonstrate a maximum a posteriori (MAP) blind image deconvolution algorithm with bandwidth over-constrained and total variation (TV) regularization to recover a clear image from the AO corrected images. The point spread functions (PSFs) are estimated by bandwidth limited less than the cutoff frequency of the optical system. Our algorithm performs well in avoiding noise magnification. The performance is demonstrated on simulated data.

Successive Over-Relaxation Technique for High-Performance Blind Image Deconvolution

DTIC Science & Technology

2015-06-08

deconvolution, space surveillance, Gauss - Seidel iteration 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18, NUMBER OF PAGES 5...sensible approximate solutions to the ill-posed nonlinear inverse problem. These solutions are addresses as fixed points of the iteration which consists in...alternating approximations (AA) for the object and for the PSF performed with a prescribed number of inner iterative descents from trivial (zero

Toward Overcoming the Local Minimum Trap in MFBD

DTIC Science & Technology

2015-07-14

the first two years of this grant: • A. Cornelio, E. Loli -Piccolomini, and J. G. Nagy. Constrained Variable Projection Method for Blind Deconvolution...Cornelio, E. Loli -Piccolomini, and J. G. Nagy. Constrained Numerical Optimization Meth- ods for Blind Deconvolution, Numerical Algorithms, volume 65, issue 1...Publications (published) during reporting period: A. Cornelio, E. Loli Piccolomini, and J. G. Nagy. Constrained Variable Projection Method for Blind

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution.

PubMed

Harper, Brett; Neumann, Elizabeth K; Stow, Sarah M; May, Jody C; McLean, John A; Solouki, Touradj

2016-10-05

Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting "pure" IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) "shift factors" to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.8 Å(2), 295.1 Å(2), 296.8 Å(2), and 300.1 Å(2); all four of these CCS values were within 1.5% of independently measured DTIM-MS values. Copyright © 2016 Elsevier B.V. All rights reserved.

Punch stretching process monitoring using acoustic emission signal analysis. II - Application of frequency domain deconvolution

NASA Technical Reports Server (NTRS)

Liang, Steven Y.; Dornfeld, David A.; Nickerson, Jackson A.

1987-01-01

The coloring effect on the acoustic emission signal due to the frequency response of the data acquisition/processing instrumentation may bias the interpretation of AE signal characteristics. In this paper, a frequency domain deconvolution technique, which involves the identification of the instrumentation transfer functions and multiplication of the AE signal spectrum by the inverse of these system functions, has been carried out. In this way, the change in AE signal characteristics can be better interpreted as the result of the change in only the states of the process. Punch stretching process was used as an example to demonstrate the application of the technique. Results showed that, through the deconvolution, the frequency characteristics of AE signals generated during the stretching became more distinctive and can be more effectively used as tools for process monitoring.

Improving the Ability of Image Sensors to Detect Faint Stars and Moving Objects Using Image Deconvolution Techniques

PubMed Central

Fors, Octavi; Núñez, Jorge; Otazu, Xavier; Prades, Albert; Cardinal, Robert D.

2010-01-01

In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors. PMID:22294896

Improving the ability of image sensors to detect faint stars and moving objects using image deconvolution techniques.

PubMed

Fors, Octavi; Núñez, Jorge; Otazu, Xavier; Prades, Albert; Cardinal, Robert D

2010-01-01

In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors.

Verifying the Presence of Low Levels of Neptunium in a Uranium Matrix with Electron Energy-Loss Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buck, Edgar C.; Douglas, Matthew; Wittman, Richard S.

2010-01-01

This paper examines the problems associated with the analysis of low levels of neptunium (Np) in a uranium (U) matrix with electron energy-loss spectroscopy (EELS) on the transmission electron microscope (TEM). The detection of Np in a matrix of uranium (U) can be impeded by the occurrence of a plural scattering event from U (U-M5 + U-O4,5) that results in severe overlap on the Np-M5 edge at 3665 eV. Low levels (1600 - 6300 ppm) of Np can be detected in U solids by confirming the energy gap between the Np-M5 and Np-M4 edges is at 184 eV and showingmore » that the M4/M5 ratio for the Np is smaller than that for U. The Richardson-Lucy deconvolution method was applied to energy-loss spectral images and was shown to increase the signal to noise. This method also improves the limits of detection for Np in a U matrix.« less

Improving multiphoton STED nanoscopy with separation of photons by LIfetime Tuning (SPLIT)

NASA Astrophysics Data System (ADS)

Coto Hernández, Iván.; Lanzano, Luca; Castello, Marco; Jowett, Nate; Tortarolo, Giorgio; Diaspro, Alberto; Vicidomini, Giuseppe

2018-02-01

Stimulated emission depletion (STED) microscopy is a powerful bio-imaging technique since it provides molecular spatial resolution whilst preserving the most important assets of fluorescence microscopy. When combined with twophoton excitation (2PE) microscopy (2PE-STED), the sub-diffraction imaging ability of STED microscopy can be achieved also on thick biological samples. The most straightforward implementation of 2PE-STED microscopy is obtained by introducing a STED beam operating in continuous wave (CW) into a conventional Ti:Sapphire based 2PE microscope (2PE-CW-STED). In this implementation, an effective resolution enhancement is mainly obtained implementing a time-gated detection scheme, which however can drastically reduce the signal-to-noise/background ratio of the final image. Herein, we combine the lifetime tuning (SPLIT) approach with 2PE-CW-STED to overcome this limitation. The SPLIT approach is employed to discard fluorescence photons lacking super-resolution information, by means of a pixel-by-pixel phasor approach. Combining the SPLIT approach with image deconvolution further optimizes the signal-to-noise/background ratio.

XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

NASA Astrophysics Data System (ADS)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-08-01

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

Chemometric Deconvolution of Continuous Electrokinetic Injection Micellar Electrokinetic Chromatography Data for the Quantitation of Trinitrotoluene in Mixtures of Other Nitroaromatic Compounds

DTIC Science & Technology

2014-02-24

Suite 600 Washington, DC 20036 NRL/MR/ 6110 --14-9521 Approved for public release; distribution is unlimited. 1Science & Engineering Apprenticeship...Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/ 6110 --14-9521 Chemometric Deconvolution of Continuous Electrokinetic Injection Micellar... Engineering Apprenticeship Program American Society for Engineering Education Washington, DC Kevin Johnson Navy Technology Center for Safety and

Enhanced Seismic Imaging of Turbidite Deposits in Chicontepec Basin, Mexico

NASA Astrophysics Data System (ADS)

Chavez-Perez, S.; Vargas-Meleza, L.

2007-05-01

We test, as postprocessing tools, a combination of migration deconvolution and geometric attributes to attack the complex problems of reflector resolution and detection in migrated seismic volumes. Migration deconvolution has been empirically shown to be an effective approach for enhancing the illumination of migrated images, which are blurred versions of the subsurface reflectivity distribution, by decreasing imaging artifacts, improving spatial resolution, and alleviating acquisition footprint problems. We utilize migration deconvolution as a means to improve the quality and resolution of 3D prestack time migrated results from Chicontepec basin, Mexico, a very relevant portion of the producing onshore sector of Pemex, the Mexican petroleum company. Seismic data covers the Agua Fria, Coapechaca, and Tajin fields. It exhibits acquisition footprint problems, migration artifacts and a severe lack of resolution in the target area, where turbidite deposits need to be characterized between major erosional surfaces. Vertical resolution is about 35 m and the main hydrocarbon plays are turbidite beds no more than 60 m thick. We also employ geometric attributes (e.g., coherent energy and curvature), computed after migration deconvolution, to detect and map out depositional features, and help design development wells in the area. Results of this workflow show imaging enhancement and allow us to identify meandering channels and individual sand bodies, previously undistinguishable in the original seismic migrated images.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

Data Dependent Peak Model Based Spectrum Deconvolution for Analysis of High Resolution LC-MS Data

PubMed Central

2015-01-01

A data dependent peak model (DDPM) based spectrum deconvolution method was developed for analysis of high resolution LC-MS data. To construct the selected ion chromatogram (XIC), a clustering method, the density based spatial clustering of applications with noise (DBSCAN), is applied to all m/z values of an LC-MS data set to group the m/z values into each XIC. The DBSCAN constructs XICs without the need for a user defined m/z variation window. After the XIC construction, the peaks of molecular ions in each XIC are detected using both the first and the second derivative tests, followed by an optimized chromatographic peak model selection method for peak deconvolution. A total of six chromatographic peak models are considered, including Gaussian, log-normal, Poisson, gamma, exponentially modified Gaussian, and hybrid of exponential and Gaussian models. The abundant nonoverlapping peaks are chosen to find the optimal peak models that are both data- and retention-time-dependent. Analysis of 18 spiked-in LC-MS data demonstrates that the proposed DDPM spectrum deconvolution method outperforms the traditional method. On average, the DDPM approach not only detected 58 more chromatographic peaks from each of the testing LC-MS data but also improved the retention time and peak area 3% and 6%, respectively. PMID:24533635

Motion correction of PET brain images through deconvolution: I. Theoretical development and analysis in software simulations

NASA Astrophysics Data System (ADS)

Faber, T. L.; Raghunath, N.; Tudorascu, D.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. Existing correction methods that use known patient motion obtained from tracking devices either require multi-frame acquisitions, detailed knowledge of the scanner, or specialized reconstruction algorithms. A deconvolution algorithm has been developed that alleviates these drawbacks by using the reconstructed image to estimate the original non-blurred image using maximum likelihood estimation maximization (MLEM) techniques. A high-resolution digital phantom was created by shape-based interpolation of the digital Hoffman brain phantom. Three different sets of 20 movements were applied to the phantom. For each frame of the motion, sinograms with attenuation and three levels of noise were simulated and then reconstructed using filtered backprojection. The average of the 20 frames was considered the motion blurred image, which was restored with the deconvolution algorithm. After correction, contrast increased from a mean of 2.0, 1.8 and 1.4 in the motion blurred images, for the three increasing amounts of movement, to a mean of 2.5, 2.4 and 2.2. Mean error was reduced by an average of 55% with motion correction. In conclusion, deconvolution can be used for correction of motion blur when subject motion is known.

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

NASA Astrophysics Data System (ADS)

Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng

2017-01-01

Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.

Partitioning of nitroxides in dispersed systems investigated by ultrafiltration, EPR and NMR spectroscopy.

PubMed

Krudopp, Heimke; Sönnichsen, Frank D; Steffen-Heins, Anja

2015-08-15

The partitioning behavior of paramagnetic nitroxides in dispersed systems can be determined by deconvolution of electron paramagnetic resonance (EPR) spectra giving equivalent results with the validated methods of ultrafiltration techniques (UF) and pulsed-field gradient nuclear magnetic resonance spectroscopy (PFG-NMR). The partitioning behavior of nitroxides with increasing lipophilicity was investigated in anionic, cationic and nonionic micellar systems and 10 wt% o/w emulsions. Apart from EPR spectra deconvolution, the PFG-NMR was used in micellar solutions as a non-destructive approach, while UF based on separation of very small volume of the aqueous phase. As a function of their substituent and lipophilicity, the proportions of nitroxides that were solubilized in the micellar or emulsion interface increased with increasing nitroxide lipophilicity for all emulsifier used. Comparing the different approaches, EPR deconvolution and UF revealed comparable nitroxide proportions that were solubilized in the interfaces. Those proportions were higher than found with PFG-NMR. For PFG-NMR self-diffusion experiments the reduced nitroxides were used revealing a high dynamic of hydroxylamines and emulsifiers. Deconvolution of EPR spectra turned out to be the preferred method for measuring the partitioning behavior of paramagnetic molecules as it enables distinguishing between several populations at their individual solubilization sites. Copyright © 2015 Elsevier Inc. All rights reserved.

Extraction of near-surface properties for a lossy layered medium using the propagator matrix

USGS Publications Warehouse

Mehta, K.; Snieder, R.; Graizer, V.

2007-01-01

Near-surface properties play an important role in advancing earthquake hazard assessment. Other areas where near-surface properties are crucial include civil engineering and detection and delineation of potable groundwater. From an exploration point of view, near-surface properties are needed for wavefield separation and correcting for the local near-receiver structure. It has been shown that these properties can be estimated for a lossless homogeneous medium using the propagator matrix. To estimate the near-surface properties, we apply deconvolution to passive borehole recordings of waves excited by an earthquake. Deconvolution of these incoherent waveforms recorded by the sensors at different depths in the borehole with the recording at the surface results in waves that propagate upwards and downwards along the array. These waves, obtained by deconvolution, can be used to estimate the P- and S-wave velocities near the surface. As opposed to waves obtained by cross-correlation that represent filtered version of the sum of causal and acausal Green's function between the two receivers, the waves obtained by deconvolution represent the elements of the propagator matrix. Finally, we show analytically the extension of the propagator matrix analysis to a lossy layered medium for a special case of normal incidence. ?? 2007 The Authors Journal compilation ?? 2007 RAS.

Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion

NASA Astrophysics Data System (ADS)

Zhou, Q.; Michailovich, O.; Rathi, Y.

2014-03-01

High angular resolution diffusion imaging (HARDI) improves upon more traditional diffusion tensor imaging (DTI) in its ability to resolve the orientations of crossing and branching neural fibre tracts. The HARDI signals are measured over a spherical shell in q-space, and are usually used as an input to q-ball imaging (QBI) which allows estimation of the diffusion orientation distribution functions (ODFs) associated with a given region-of interest. Unfortunately, the partial nature of single-shell sampling imposes limits on the estimation accuracy. As a result, the recovered ODFs may not possess sufficient resolution to reveal the orientations of fibre tracts which cross each other at acute angles. A possible solution to the problem of limited resolution of QBI is provided by means of spherical deconvolution, a particular instance of which is sparse deconvolution. However, while capable of yielding high-resolution reconstructions over spacial locations corresponding to white matter, such methods tend to become unstable when applied to anatomical regions with a substantial content of isotropic diffusion. To resolve this problem, a new deconvolution approach is proposed in this paper. Apart from being uniformly stable across the whole brain, the proposed method allows one to quantify the isotropic component of cerebral diffusion, which is known to be a useful diagnostic measure by itself.

Model-free quantification of dynamic PET data using nonparametric deconvolution

PubMed Central

Zanderigo, Francesca; Parsey, Ramin V; Todd Ogden, R

2015-01-01

Dynamic positron emission tomography (PET) data are usually quantified using compartment models (CMs) or derived graphical approaches. Often, however, CMs either do not properly describe the tracer kinetics, or are not identifiable, leading to nonphysiologic estimates of the tracer binding. The PET data are modeled as the convolution of the metabolite-corrected input function and the tracer impulse response function (IRF) in the tissue. Using nonparametric deconvolution methods, it is possible to obtain model-free estimates of the IRF, from which functionals related to tracer volume of distribution and binding may be computed, but this approach has rarely been applied in PET. Here, we apply nonparametric deconvolution using singular value decomposition to simulated and test–retest clinical PET data with four reversible tracers well characterized by CMs ([11C]CUMI-101, [11C]DASB, [11C]PE2I, and [11C]WAY-100635), and systematically compare reproducibility, reliability, and identifiability of various IRF-derived functionals with that of traditional CMs outcomes. Results show that nonparametric deconvolution, completely free of any model assumptions, allows for estimates of tracer volume of distribution and binding that are very close to the estimates obtained with CMs and, in some cases, show better test–retest performance than CMs outcomes. PMID:25873427

THE EFFECT OF BACKGROUND SIGNAL AND ITS REPRESENTATION IN DECONVOLUTION OF EPR SPECTRA ON ACCURACY OF EPR DOSIMETRY IN BONE.

PubMed

Ciesielski, Bartlomiej; Marciniak, Agnieszka; Zientek, Agnieszka; Krefft, Karolina; Cieszyński, Mateusz; Boguś, Piotr; Prawdzik-Dampc, Anita

2016-12-01

This study is about the accuracy of EPR dosimetry in bones based on deconvolution of the experimental spectra into the background (BG) and the radiation-induced signal (RIS) components. The model RIS's were represented by EPR spectra from irradiated enamel or bone powder; the model BG signals by EPR spectra of unirradiated bone samples or by simulated spectra. Samples of compact and trabecular bones were irradiated in the 30-270 Gy range and the intensities of their RIS's were calculated using various combinations of those benchmark spectra. The relationships between the dose and the RIS were linear (R 2  > 0.995), with practically no difference between results obtained when using signals from irradiated enamel or bone as the model RIS. Use of different experimental spectra for the model BG resulted in variations in intercepts of the dose-RIS calibration lines, leading to systematic errors in reconstructed doses, in particular for high- BG samples of trabecular bone. These errors were reduced when simulated spectra instead of the experimental ones were used as the benchmark BG signal in the applied deconvolution procedures. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Wavefield iterative deconvolution to remove multiples and produce phase specific Ps receiver functions

NASA Astrophysics Data System (ADS)

Ainiwaer, A.; Gurrola, H.

2018-03-01

Common conversion point stacking or migration of receiver functions (RFs) and H-k (H is depth and k is Vp/Vs) stacking of RFs has become a common method to study the crust and upper mantle beneath broad-band three-component seismic stations. However, it can be difficult to interpret Pds RFs due to interference between the Pds, PPds and PSds phases, especially in the mantle portion of the lithosphere. We propose a phase separation method to isolate the prominent phases of the RFs and produce separate Pds, PPds and PSds `phase specific' receiver functions (referred to as PdsRFs, PPdsRFs and PSdsRFs, respectively) by deconvolution of the wavefield rather than single seismograms. One of the most important products of this deconvolution method is to produce Ps receiver functions (PdsRFs) that are free of crustal multiples. This is accomplished by using H-k analysis to identify specific phases in the wavefield from all seismograms recorded at a station which enables development of an iterative deconvolution procedure to produce the above-mentioned phase specific RFs. We refer to this method as wavefield iterative deconvolution (WID). The WID method differentiates and isolates different RF phases by exploiting their differences in moveout curves across the entire wave front. We tested the WID by applying it to synthetic seismograms produced using a modified version of the PREM velocity model. The WID effectively separates phases from each stacked RF in synthetic data. We also applied this technique to produce RFs from seismograms recorded at ARU (a broad-band station in Arti, Russia). The phase specific RFs produced using WID are easier to interpret than traditional RFs. The PdsRFs computed using WID are the most improved, owing to the distinct shape of its moveout curves as compared to the moveout curves for the PPds and PSds phases. The importance of this WID method is most significant in reducing interference between phases for depths of less than 300 km. Phases from deeper layers (i.e. P660s as compared to PP220s) are less likely to be misinterpreted because the large amount of moveout causes the appropriate phases to stack coherently if there is sufficient distribution in ray parameter. WID is most effective in producing clean PdsRFs that are relatively free of reverberations whereas PPdsRFs and PSdsRFs retain contamination from reverberations.

Analysis of gravity data beneath Endut geothermal prospect using horizontal gradient and Euler deconvolution

NASA Astrophysics Data System (ADS)

Supriyanto, Noor, T.; Suhanto, E.

2017-07-01

The Endut geothermal prospect is located in Banten Province, Indonesia. The geological setting of the area is dominated by quaternary volcanic, tertiary sediments and tertiary rock intrusion. This area has been in the preliminary study phase of geology, geochemistry, and geophysics. As one of the geophysical study, the gravity data measurement has been carried out and analyzed in order to understand geological condition especially subsurface fault structure that control the geothermal system in Endut area. After precondition applied to gravity data, the complete Bouguer anomaly have been analyzed using advanced derivatives method such as Horizontal Gradient (HG) and Euler Deconvolution (ED) to clarify the existance of fault structures. These techniques detected boundaries of body anomalies and faults structure that were compared with the lithologies in the geology map. The analysis result will be useful in making a further realistic conceptual model of the Endut geothermal area.

Image restoration using aberration taken by a Hartmann wavefront sensor on extended object, towards real-time deconvolution

NASA Astrophysics Data System (ADS)

Darudi, Ahmad; Bakhshi, Hadi; Asgari, Reza

2015-05-01

In this paper we present the results of image restoration using the data taken by a Hartmann sensor. The aberration is measure by a Hartmann sensor in which the object itself is used as reference. Then the Point Spread Function (PSF) is simulated and used for image reconstruction using the Lucy-Richardson technique. A technique is presented for quantitative evaluation the Lucy-Richardson technique for deconvolution.

Novel Image Quality Control Systems(Add-On). Innovative Computational Methods for Inverse Problems in Optical and SAR Imaging

DTIC Science & Technology

2007-02-28

Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex Medium Response, International Journal of Imaging Systems and...1767-1782, 2006. 31. Z. Mu, R. Plemmons, and P. Santago. Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex...rigorous mathematical and computational research on inverse problems in optical imaging of direct interest to the Army and also the intelligence agencies

Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Chang-hui; Wei, Kai

Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.

Forward Looking Radar Imaging by Truncated Singular Value Decomposition and Its Application for Adverse Weather Aircraft Landing.

PubMed

Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu

2015-06-18

The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward looking radar imaging based on deconvolution method is presented for adverse weather aircraft landing. We first present the theoretical background of forward looking radar imaging task and its application for aircraft landing. Then, we convert the forward looking radar imaging task into a corresponding deconvolution problem, which is solved in the framework of algebraic theory using truncated singular decomposition method. The key issue regarding the selecting of the truncated parameter is addressed using generalized cross validation approach. Simulation and experimental results demonstrate that the proposed method is effective in achieving angular resolution enhancement with suppressing the noise amplification in forward looking radar imaging.

Removing the echoes from terahertz pulse reflection system and sample

NASA Astrophysics Data System (ADS)

Liu, Haishun; Zhang, Zhenwei; Zhang, Cunlin

2018-01-01

Due to the echoes both from terahertz (THz) pulse reflection system and sample, the THz primary pulse will be distorted. The system echoes include two types. One preceding the main peak probably is caused by ultrafast laser pulse and the other at the back of the primary pulse is caused by the Fabry-Perot (F-P) etalon effect of detector. We attempt to remove the corresponding echoes by using two kinds of deconvolution. A Si wafer of 400μm was selected as the tested sample. Firstly, the method of double Gaussian filter (DGF) decnvolution was used to remove the systematic echoes, and then another deconvolution technique was employed to eliminate the two obvious echoes of the sample. The ultimate results indicated: although the combination of two deconvolution techniques could not entirely remove the echoes of sample and system, the echoes were largely reduced.

Determination of uronic acids in isolated hemicelluloses from kenaf using diffuse reflectance infrared fourier transform spectroscopy (DRIFTS) and the curve-fitting deconvolution method.

PubMed

Batsoulis, A N; Nacos, M K; Pappas, C S; Tarantilis, P A; Mavromoustakos, T; Polissiou, M G

2004-02-01

Hemicellulose samples were isolated from kenaf (Hibiscus cannabinus L.). Hemicellulosic fractions usually contain a variable percentage of uronic acids. The uronic acid content (expressed in polygalacturonic acid) of the isolated hemicelluloses was determined by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and the curve-fitting deconvolution method. A linear relationship between uronic acids content and the sum of the peak areas at 1745, 1715, and 1600 cm(-1) was established with a high correlation coefficient (0.98). The deconvolution analysis using the curve-fitting method allowed the elimination of spectral interferences from other cell wall components. The above method was compared with an established spectrophotometric method and was found equivalent for accuracy and repeatability (t-test, F-test). This method is applicable in analysis of natural or synthetic mixtures and/or crude substances. The proposed method is simple, rapid, and nondestructive for the samples.

FTIR of binary lead borate glass: Structural investigation

NASA Astrophysics Data System (ADS)

Othman, H. A.; Elkholy, H. S.; Hager, I. Z.

2016-02-01

The glass samples were prepared according to the following formula: (100-x) B2O3 - x PbO, where x = 20-80 mol% by melt quenching method. The density of the prepared samples was measured and molar volume was calculated. IR spectra were measured for the prepared samples to investigate the glass structure. The IR spectra were deconvoluted using curves of Gaussian shape at approximately the same frequencies. The deconvoluted data were used to study the effect of PbO content on all the structural borate groups. Some structural parameters such as density, packing density, bond length and bond force constant were theoretically calculated and were compared to the obtained experimental results. Deviation between the experimental and theoretically calculated parameters reflects the dual role of PbO content on the network of borate glass.

Application of Analytic Signal and Euler Deconvolution in Archaeo-Magnetic Prospection for Buried Ruins at the Ancient City of Pelusium, NW Sinai, Egypt: A Case Study

NASA Astrophysics Data System (ADS)

Aziz, Akram Mekhael; Sauck, William August; Shendi, El-Arabi Hendi; Rashed, Mohamed Ahmed; Abd El-Maksoud, Mohamed

2013-07-01

Progress in the past three decades in geophysical data processing and interpretation techniques was particularly focused in the field of aero-geophysics. The present study is to demonstrate the application of some of these techniques, including Analytic Signal, Located Euler Deconvolution, Standard Euler Deconvolution, and 2D inverse modelling, to help in enhancing and interpreting the archeo-magnetic measurements. A high-resolution total magnetic field survey was conducted at the ancient city of Pelusium (name derived from the ancient Pelusiac branch of the Nile, and recently called Tell el-Farama), located in the northwestern corner of the Sinai Peninsula. The historical city had served as a harbour throughout the Egyptian history. Different ruins at the site have been dated back to late Pharaonic, Graeco-Roman, Byzantine, Coptic, and Islamic periods. An area of 10,000 m2, to the west of the famous huge red brick citadel of Pelusium, was surveyed using the magnetic method. The chosen location was recommended by the Egyptian archaeologists, where they suspected the presence of buried foundations of a temple to the gods Zeus and Kasios. The interpretation of the results revealed interesting shallow-buried features, which may represent the Temple's outer walls. These walls are elongated in the same azimuth as the northern wall of the citadel, which supports the hypothesis of a controlling feature such as a former seacoast or shore of a distributary channel.

A Robust Deconvolution Method based on Transdimensional Hierarchical Bayesian Inference

NASA Astrophysics Data System (ADS)

Kolb, J.; Lekic, V.

2012-12-01

Analysis of P-S and S-P conversions allows us to map receiver side crustal and lithospheric structure. This analysis often involves deconvolution of the parent wave field from the scattered wave field as a means of suppressing source-side complexity. A variety of deconvolution techniques exist including damped spectral division, Wiener filtering, iterative time-domain deconvolution, and the multitaper method. All of these techniques require estimates of noise characteristics as input parameters. We present a deconvolution method based on transdimensional Hierarchical Bayesian inference in which both noise magnitude and noise correlation are used as parameters in calculating the likelihood probability distribution. Because the noise for P-S and S-P conversion analysis in terms of receiver functions is a combination of both background noise - which is relatively easy to characterize - and signal-generated noise - which is much more difficult to quantify - we treat measurement errors as an known quantity, characterized by a probability density function whose mean and variance are model parameters. This transdimensional Hierarchical Bayesian approach has been successfully used previously in the inversion of receiver functions in terms of shear and compressional wave speeds of an unknown number of layers [1]. In our method we used a Markov chain Monte Carlo (MCMC) algorithm to find the receiver function that best fits the data while accurately assessing the noise parameters. In order to parameterize the receiver function we model the receiver function as an unknown number of Gaussians of unknown amplitude and width. The algorithm takes multiple steps before calculating the acceptance probability of a new model, in order to avoid getting trapped in local misfit minima. Using both observed and synthetic data, we show that the MCMC deconvolution method can accurately obtain a receiver function as well as an estimate of the noise parameters given the parent and daughter components. Furthermore, we demonstrate that this new approach is far less susceptible to generating spurious features even at high noise levels. Finally, the method yields not only the most-likely receiver function, but also quantifies its full uncertainty. [1] Bodin, T., M. Sambridge, H. Tkalčić, P. Arroucau, K. Gallagher, and N. Rawlinson (2012), Transdimensional inversion of receiver functions and surface wave dispersion, J. Geophys. Res., 117, B02301

A deconvolution extraction method for 2D multi-object fibre spectroscopy based on the regularized least-squares QR-factorization algorithm

NASA Astrophysics Data System (ADS)

Yu, Jian; Yin, Qian; Guo, Ping; Luo, A.-li

2014-09-01

This paper presents an efficient method for the extraction of astronomical spectra from two-dimensional (2D) multifibre spectrographs based on the regularized least-squares QR-factorization (LSQR) algorithm. We address two issues: we propose a modified Gaussian point spread function (PSF) for modelling the 2D PSF from multi-emission-line gas-discharge lamp images (arc images), and we develop an efficient deconvolution method to extract spectra in real circumstances. The proposed modified 2D Gaussian PSF model can fit various types of 2D PSFs, including different radial distortion angles and ellipticities. We adopt the regularized LSQR algorithm to solve the sparse linear equations constructed from the sparse convolution matrix, which we designate the deconvolution spectrum extraction method. Furthermore, we implement a parallelized LSQR algorithm based on graphics processing unit programming in the Compute Unified Device Architecture to accelerate the computational processing. Experimental results illustrate that the proposed extraction method can greatly reduce the computational cost and memory use of the deconvolution method and, consequently, increase its efficiency and practicability. In addition, the proposed extraction method has a stronger noise tolerance than other methods, such as the boxcar (aperture) extraction and profile extraction methods. Finally, we present an analysis of the sensitivity of the extraction results to the radius and full width at half-maximum of the 2D PSF.

Unsupervised Learning for Monaural Source Separation Using Maximization–Minimization Algorithm with Time–Frequency Deconvolution †

PubMed Central

Bouridane, Ahmed; Ling, Bingo Wing-Kuen

2018-01-01

This paper presents an unsupervised learning algorithm for sparse nonnegative matrix factor time–frequency deconvolution with optimized fractional β-divergence. The β-divergence is a group of cost functions parametrized by a single parameter β. The Itakura–Saito divergence, Kullback–Leibler divergence and Least Square distance are special cases that correspond to β=0, 1, 2, respectively. This paper presents a generalized algorithm that uses a flexible range of β that includes fractional values. It describes a maximization–minimization (MM) algorithm leading to the development of a fast convergence multiplicative update algorithm with guaranteed convergence. The proposed model operates in the time–frequency domain and decomposes an information-bearing matrix into two-dimensional deconvolution of factor matrices that represent the spectral dictionary and temporal codes. The deconvolution process has been optimized to yield sparse temporal codes through maximizing the likelihood of the observations. The paper also presents a method to estimate the fractional β value. The method is demonstrated on separating audio mixtures recorded from a single channel. The paper shows that the extraction of the spectral dictionary and temporal codes is significantly more efficient by using the proposed algorithm and subsequently leads to better source separation performance. Experimental tests and comparisons with other factorization methods have been conducted to verify its efficacy. PMID:29702629

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

NASA Astrophysics Data System (ADS)

Reid, Deseree J.; Diesing, Jessica M.; Miller, Matthew A.; Perry, Scott M.; Wales, Jessica A.; Montfort, William R.; Marty, Michael T.

2018-04-01

The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. [Figure not available: see fulltext.

Deconvolution of magnetic acoustic change complex (mACC).

PubMed

Bardy, Fabrice; McMahon, Catherine M; Yau, Shu Hui; Johnson, Blake W

2014-11-01

The aim of this study was to design a novel experimental approach to investigate the morphological characteristics of auditory cortical responses elicited by rapidly changing synthesized speech sounds. Six sound-evoked magnetoencephalographic (MEG) responses were measured to a synthesized train of speech sounds using the vowels /e/ and /u/ in 17 normal hearing young adults. Responses were measured to: (i) the onset of the speech train, (ii) an F0 increment; (iii) an F0 decrement; (iv) an F2 decrement; (v) an F2 increment; and (vi) the offset of the speech train using short (jittered around 135ms) and long (1500ms) stimulus onset asynchronies (SOAs). The least squares (LS) deconvolution technique was used to disentangle the overlapping MEG responses in the short SOA condition only. Comparison between the morphology of the recovered cortical responses in the short and long SOAs conditions showed high similarity, suggesting that the LS deconvolution technique was successful in disentangling the MEG waveforms. Waveform latencies and amplitudes were different for the two SOAs conditions and were influenced by the spectro-temporal properties of the sound sequence. The magnetic acoustic change complex (mACC) for the short SOA condition showed significantly lower amplitudes and shorter latencies compared to the long SOA condition. The F0 transition showed a larger reduction in amplitude from long to short SOA compared to the F2 transition. Lateralization of the cortical responses were observed under some stimulus conditions and appeared to be associated with the spectro-temporal properties of the acoustic stimulus. The LS deconvolution technique provides a new tool to study the properties of the auditory cortical response to rapidly changing sound stimuli. The presence of the cortical auditory evoked responses for rapid transition of synthesized speech stimuli suggests that the temporal code is preserved at the level of the auditory cortex. Further, the reduced amplitudes and shorter latencies might reflect intrinsic properties of the cortical neurons to rapidly presented sounds. This is the first demonstration of the separation of overlapping cortical responses to rapidly changing speech sounds and offers a potential new biomarker of discrimination of rapid transition of sound. Crown Copyright © 2014. Published by Elsevier Ireland Ltd. All rights reserved.

Topography Estimation of the Core Mantle Boundary with ScS Reverberations and Diffraction Waves

NASA Astrophysics Data System (ADS)

Hein, B. E.; Nakata, N.

2017-12-01

In this study, we use the propagation of global seismic waves to study the Core Mantle Boundary (CMB). We focus on the use of S-wave reflections at the CMB (ScS reverberations) and outer-core diffracted waves. It is difficult imaging the CMB with the ScS wave because the complexity of the structure in the near surface ( 50 km); the complex structure degrades the signal-to-noise ratio of of the ScS. To avoid estimating the structure in the crust, we rely on the concept of seismic interferometry to extract wave propagation through mantle, but not through the crust. Our approach is compute the deconvolution between the ScS (and its reverberation) and direct S waves generated by intermediate to deep earthquakes (>50 km depth). Through this deconvolution, we have the ability to filter out the direct S wave and retrieve the wave field propagating from only the hypocenter to the outer core, but not between the hypocenter to the receiver. After the deconvolution, we can isolate the CMB reflected waves from the complicated wave phenomena because of the near-surface structure. Utilizing intermediate and deep earthquakes is key since we can suppress the near-surface effect from the surface to the hypocenter of the earthquakes. The variation of such waves (e.g., travel-time perturbation and/or wavefield decorrelation) at different receivers and earthquakes provides the information of the topography of the CMB. In order to get a more detailed image of the topography of the CMB we use diffracted seismic waves such as Pdiff , Sdiff, and P'P'. By using two intermediate to deep earthquakes on a great circle path with a station we can extract the wave propagation between the two earthquakes to simplify the waveform, similar to how it is preformed using the ScS wave. We generate more illumination of the CMB by using diffracted waves rather than only using ScS reverberations. The accurate topography of CMB obtained by these deconvolution analyses may provide new insight of the dynamics of the Earth such as heat flow at the CMB and through the mantle.

Effect of confounding variables on hemodynamic response function estimation using averaging and deconvolution analysis: An event-related NIRS study.

PubMed

Aarabi, Ardalan; Osharina, Victoria; Wallois, Fabrice

2017-07-15

Slow and rapid event-related designs are used in fMRI and functional near-infrared spectroscopy (fNIRS) experiments to temporally characterize the brain hemodynamic response to discrete events. Conventional averaging (CA) and the deconvolution method (DM) are the two techniques commonly used to estimate the Hemodynamic Response Function (HRF) profile in event-related designs. In this study, we conducted a series of simulations using synthetic and real NIRS data to examine the effect of the main confounding factors, including event sequence timing parameters, different types of noise, signal-to-noise ratio (SNR), temporal autocorrelation and temporal filtering on the performance of these techniques in slow and rapid event-related designs. We also compared systematic errors in the estimates of the fitted HRF amplitude, latency and duration for both techniques. We further compared the performance of deconvolution methods based on Finite Impulse Response (FIR) basis functions and gamma basis sets. Our results demonstrate that DM was much less sensitive to confounding factors than CA. Event timing was the main parameter largely affecting the accuracy of CA. In slow event-related designs, deconvolution methods provided similar results to those obtained by CA. In rapid event-related designs, our results showed that DM outperformed CA for all SNR, especially above -5 dB regardless of the event sequence timing and the dynamics of background NIRS activity. Our results also show that periodic low-frequency systemic hemodynamic fluctuations as well as phase-locked noise can markedly obscure hemodynamic evoked responses. Temporal autocorrelation also affected the performance of both techniques by inducing distortions in the time profile of the estimated hemodynamic response with inflated t-statistics, especially at low SNRs. We also found that high-pass temporal filtering could substantially affect the performance of both techniques by removing the low-frequency components of HRF profiles. Our results emphasize the importance of characterization of event timing, background noise and SNR when estimating HRF profiles using CA and DM in event-related designs. Copyright © 2017 Elsevier Inc. All rights reserved.

A Model Based Deconvolution Approach for Creating Surface Composition Maps of Irregularly Shaped Bodies from Limited Orbiting Nuclear Spectrometer Measurements

NASA Astrophysics Data System (ADS)

Dallmann, N. A.; Carlsten, B. E.; Stonehill, L. C.

2017-12-01

Orbiting nuclear spectrometers have contributed significantly to our understanding of the composition of solar system bodies. Gamma rays and neutrons are produced within the surfaces of bodies by impacting galactic cosmic rays (GCR) and by intrinsic radionuclide decay. Measuring the flux and energy spectrum of these products at one point in an orbit elucidates the elemental content of the area in view. Deconvolution of measurements from many spatially registered orbit points can produce detailed maps of elemental abundances. In applying these well-established techniques to small and irregularly shaped bodies like Phobos, one encounters unique challenges beyond those of a large spheroid. Polar mapping orbits are not possible for Phobos and quasistatic orbits will realize only modest inclinations unavoidably limiting surface coverage and creating North-South ambiguities in deconvolution. The irregular shape causes self-shadowing both of the body to the spectrometer but also of the body to the incoming GCR. The view angle to the surface normal as well as the distance between the surface and the spectrometer is highly irregular. These characteristics can be synthesized into a complicated and continuously changing measurement system point spread function. We have begun to explore different model-based, statistically rigorous, iterative deconvolution methods to produce elemental abundance maps for a proposed future investigation of Phobos. By incorporating the satellite orbit, the existing high accuracy shape-models of Phobos, and the spectrometer response function, a detailed and accurate system model can be constructed. Many aspects of this model formation are particularly well suited to modern graphics processing techniques and parallel processing. We will present the current status and preliminary visualizations of the Phobos measurement system model. We will also discuss different deconvolution strategies and their relative merit in statistical rigor, stability, achievable resolution, and exploitation of the irregular shape to partially resolve ambiguities. The general applicability of these new approaches to existing data sets from Mars, Mercury, and Lunar investigations will be noted.

Detection of high-risk atherosclerotic lesions by time-resolved fluorescence spectroscopy based on the Laguerre deconvolution technique

NASA Astrophysics Data System (ADS)

Jo, J. A.; Fang, Q.; Papaioannou, T.; Qiao, J. H.; Fishbein, M. C.; Beseth, B.; Dorafshar, A. H.; Reil, T.; Baker, D.; Freischlag, J.; Marcu, L.

2006-02-01

This study introduces new methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data analysis for tissue characterization. These analytical methods were applied for the detection of atherosclerotic vulnerable plaques. Upon pulsed nitrogen laser (337 nm, 1 ns) excitation, TR-LIFS measurements were obtained from carotid atherosclerotic plaque specimens (57 endarteroctomy patients) at 492 distinct areas. The emission was both spectrally- (360-600 nm range at 5 nm interval) and temporally- (0.3 ns resolution) resolved using a prototype clinically compatible fiber-optic catheter TR-LIFS apparatus. The TR-LIFS measurements were subsequently analyzed using a standard multiexponential deconvolution and a recently introduced Laguerre deconvolution technique. Based on their histopathology, the lesions were classified as early (thin intima), fibrotic (collagen-rich intima), and high-risk (thin cap over necrotic core and/or inflamed intima). Stepwise linear discriminant analysis (SLDA) was applied for lesion classification. Normalized spectral intensity values and Laguerre expansion coefficients (LEC) at discrete emission wavelengths (390, 450, 500 and 550 nm) were used as features for classification. The Laguerre based SLDA classifier provided discrimination of high-risk lesions with high sensitivity (SE>81%) and specificity (SP>95%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for the diagnosis of high-risk vulnerable atherosclerotic plaques.

Microseismic source locations with deconvolution migration

NASA Astrophysics Data System (ADS)

Wu, Shaojiang; Wang, Yibo; Zheng, Yikang; Chang, Xu

2018-03-01

Identifying and locating microseismic events are critical problems in hydraulic fracturing monitoring for unconventional resources exploration. In contrast to active seismic data, microseismic data are usually recorded with unknown source excitation time and source location. In this study, we introduce deconvolution migration by combining deconvolution interferometry with interferometric cross-correlation migration (CCM). This method avoids the need for the source excitation time and enhances both the spatial resolution and robustness by eliminating the square term of the source wavelets from CCM. The proposed algorithm is divided into the following three steps: (1) generate the virtual gathers by deconvolving the master trace with all other traces in the microseismic gather to remove the unknown excitation time; (2) migrate the virtual gather to obtain a single image of the source location and (3) stack all of these images together to get the final estimation image of the source location. We test the proposed method on complex synthetic and field data set from the surface hydraulic fracturing monitoring, and compare the results with those obtained by interferometric CCM. The results demonstrate that the proposed method can obtain a 50 per cent higher spatial resolution image of the source location, and more robust estimation with smaller errors of the localization especially in the presence of velocity model errors. This method is also beneficial for source mechanism inversion and global seismology applications.

Time-domain separation of interfering waves in cancellous bone using bandlimited deconvolution: simulation and phantom study.

PubMed

Wear, Keith A

2014-04-01

In through-transmission interrogation of cancellous bone, two longitudinal pulses ("fast" and "slow" waves) may be generated. Fast and slow wave properties convey information about material and micro-architectural characteristics of bone. However, these properties can be difficult to assess when fast and slow wave pulses overlap in time and frequency domains. In this paper, two methods are applied to decompose signals into fast and slow waves: bandlimited deconvolution and modified least-squares Prony's method with curve-fitting (MLSP + CF). The methods were tested in plastic and Zerdine(®) samples that provided fast and slow wave velocities commensurate with velocities for cancellous bone. Phase velocity estimates were accurate to within 6 m/s (0.4%) (slow wave with both methods and fast wave with MLSP + CF) and 26 m/s (1.2%) (fast wave with bandlimited deconvolution). Midband signal loss estimates were accurate to within 0.2 dB (1.7%) (fast wave with both methods), and 1.0 dB (3.7%) (slow wave with both methods). Similar accuracies were found for simulations based on fast and slow wave parameter values published for cancellous bone. These methods provide sufficient accuracy and precision for many applications in cancellous bone such that experimental error is likely to be a greater limiting factor than estimation error.

Estimating Fluctuating Pressures From Distorted Measurements

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Leondes, Cornelius T.

1994-01-01

Two algorithms extract estimates of time-dependent input (upstream) pressures from outputs of pressure sensors located at downstream ends of pneumatic tubes. Effect deconvolutions that account for distoring effects of tube upon pressure signal. Distortion of pressure measurements by pneumatic tubes also discussed in "Distortion of Pressure Signals in Pneumatic Tubes," (ARC-12868). Varying input pressure estimated from measured time-varying output pressure by one of two deconvolution algorithms that take account of measurement noise. Algorithms based on minimum-covariance (Kalman filtering) theory.

A Division-Dependent Compartmental Model for Computing Cell Numbers in CFSE-based Lymphocyte Proliferation Assays

DTIC Science & Technology

2012-02-12

is the total number of data points, is an approximately unbiased estimate of the “expected relative Kullback - Leibler distance” ( information loss...possible models). Thus, after each model from Table 2 is fit to a data set, we can compute the Akaike weights for the set of candidate models and use ...computed from the OLS best- fit model solution (top), from a deconvolution of the data using normal curves (middle) and from a deconvolution of the data

Fourier Deconvolution Methods for Resolution Enhancement in Continuous-Wave EPR Spectroscopy.

PubMed

Reed, George H; Poyner, Russell R

2015-01-01

An overview of resolution enhancement of conventional, field-swept, continuous-wave electron paramagnetic resonance spectra using Fourier transform-based deconvolution methods is presented. Basic steps that are involved in resolution enhancement of calculated spectra using an implementation based on complex discrete Fourier transform algorithms are illustrated. Advantages and limitations of the method are discussed. An application to an experimentally obtained spectrum is provided to illustrate the power of the method for resolving overlapped transitions. © 2015 Elsevier Inc. All rights reserved.

Least-Squares Deconvolution of Compton Telescope Data with the Positivity Constraint

NASA Technical Reports Server (NTRS)

Wheaton, William A.; Dixon, David D.; Tumer, O. Tumay; Zych, Allen D.

1993-01-01

We describe a Direct Linear Algebraic Deconvolution (DLAD) approach to imaging of data from Compton gamma-ray telescopes. Imposition of the additional physical constraint, that all components of the model be non-negative, has been found to have a powerful effect in stabilizing the results, giving spatial resolution at or near the instrumental limit. A companion paper (Dixon et al. 1993) presents preliminary images of the Crab Nebula region using data from COMPTEL on the Compton Gamma-Ray Observatory.

An l1-TV Algorithm for Deconvolution with Salt and Pepper Noise

DTIC Science & Technology

2009-04-01

deblurring in the presence of impulsive noise ,” Int. J. Comput. Vision, vol. 70, no. 3, pp. 279–298, Dec. 2006. [13] A. E. Beaton and J. W. Tukey, “The...AN 1-TV ALGORITHM FOR DECONVOLUTIONWITH SALT AND PEPPER NOISE Brendt Wohlberg∗ T-7 Mathematical Modeling and Analysis Los Alamos National Laboratory...and pepper noise , but the extension of this formulation to more general prob- lems, such as deconvolution, has received little attention. We consider

Fourier transform infrared spectroscopic studies of the secondary structure and thermal denaturation of CaATPase from rabbit skeletal muscle

NASA Astrophysics Data System (ADS)

Jaworsky, Mark; Brauner, Joseph W.; Mendelsohn, Richard

Fourier transform i.r. spectroscopy has been used to monitor structural alterations induced by thermal denaturation of the intrinsic membrane protein CaATPase in aqueous media. The protein has been isolated, purified and studied in five forms: (i) In its native lipid environment after isolation from rabbit sarcoplasmic reticulum, both in H 2O and D 2O suspensions. (ii) After both mild and extensive tryptic digestion has cleaved those residues external to the membrane bilayer. (iii) Reconstituted in vesicle form with bovine brain sphingomyelin. Fourier deconvolution techniques have been used to enhance the resolution of the intrinsically overlapped Amide I and Amide II spectral regions. Large spectral alterations apparent in the deconvoluted spectra occur in these regions upon thermal denaturation of the protein which are consistent with the formation of a large proportion of β-antiparallel sheet form. The alteration parallels the loss in ATPase activity. A mild tryptic digestion increases slightly the proportion of α-helix and/or random coil secondary structure. A thermal transition to a form containing a high proportion of β structure is still evident. Extensive tryptic digestion nearly abolishes the alpha helical plus random coil secondary structure, while producing a high proportion of β form which is resistant to further thermally induced structural alterations. Studies of CaATPase reconstituted into vesicles with bovine brain sphingomyelin reveal a higher proportion of β structure than the native enzyme, with further introduction of β structure on thermal denaturation. Both the utility of deconvolution techniques and the necessity for caution in their application are apparent from the current experiments.

Electrospray Ionization with High-Resolution Mass Spectrometry as a Tool for Lignomics: Lignin Mass Spectrum Deconvolution

NASA Astrophysics Data System (ADS)

Andrianova, Anastasia A.; DiProspero, Thomas; Geib, Clayton; Smoliakova, Irina P.; Kozliak, Evguenii I.; Kubátová, Alena

2018-05-01

The capability to characterize lignin, lignocellulose, and their degradation products is essential for the development of new renewable feedstocks. Electrospray ionization high-resolution time-of-flight mass spectrometry (ESI-HR TOF-MS) method was developed expanding the lignomics toolkit while targeting the simultaneous detection of low and high molecular weight (MW) lignin species. The effect of a broad range of electrolytes and various ionization conditions on ion formation and ionization effectiveness was studied using a suite of mono-, di-, and triarene lignin model compounds as well as kraft alkali lignin. Contrary to the previous studies, the positive ionization mode was found to be more effective for methoxy-substituted arenes and polyphenols, i.e., species of a broadly varied MW structurally similar to the native lignin. For the first time, we report an effective formation of multiply charged species of lignin with the subsequent mass spectrum deconvolution in the presence of 100 mmol L-1 formic acid in the positive ESI mode. The developed method enabled the detection of lignin species with an MW between 150 and 9000 Da or higher, depending on the mass analyzer. The obtained M n and M w values of 1500 and 2500 Da, respectively, were in good agreement with those determined by gel permeation chromatography. Furthermore, the deconvoluted ESI mass spectrum was similar to that obtained with matrix-assisted laser desorption/ionization (MALDI)-HR TOF-MS, yet featuring a higher signal-to-noise ratio. The formation of multiply charged species was confirmed with ion mobility ESI-HR Q-TOF-MS. [Figure not available: see fulltext.

Electrospray Ionization with High-Resolution Mass Spectrometry as a Tool for Lignomics: Lignin Mass Spectrum Deconvolution

NASA Astrophysics Data System (ADS)

Andrianova, Anastasia A.; DiProspero, Thomas; Geib, Clayton; Smoliakova, Irina P.; Kozliak, Evguenii I.; Kubátová, Alena

2018-03-01

The capability to characterize lignin, lignocellulose, and their degradation products is essential for the development of new renewable feedstocks. Electrospray ionization high-resolution time-of-flight mass spectrometry (ESI-HR TOF-MS) method was developed expanding the lignomics toolkit while targeting the simultaneous detection of low and high molecular weight (MW) lignin species. The effect of a broad range of electrolytes and various ionization conditions on ion formation and ionization effectiveness was studied using a suite of mono-, di-, and triarene lignin model compounds as well as kraft alkali lignin. Contrary to the previous studies, the positive ionization mode was found to be more effective for methoxy-substituted arenes and polyphenols, i.e., species of a broadly varied MW structurally similar to the native lignin. For the first time, we report an effective formation of multiply charged species of lignin with the subsequent mass spectrum deconvolution in the presence of 100 mmol L-1 formic acid in the positive ESI mode. The developed method enabled the detection of lignin species with an MW between 150 and 9000 Da or higher, depending on the mass analyzer. The obtained M n and M w values of 1500 and 2500 Da, respectively, were in good agreement with those determined by gel permeation chromatography. Furthermore, the deconvoluted ESI mass spectrum was similar to that obtained with matrix-assisted laser desorption/ionization (MALDI)-HR TOF-MS, yet featuring a higher signal-to-noise ratio. The formation of multiply charged species was confirmed with ion mobility ESI-HR Q-TOF-MS. [Figure not available: see fulltext.

Texas two-step: a framework for optimal multi-input single-output deconvolution.

PubMed

Neelamani, Ramesh; Deffenbaugh, Max; Baraniuk, Richard G

2007-11-01

Multi-input single-output deconvolution (MISO-D) aims to extract a deblurred estimate of a target signal from several blurred and noisy observations. This paper develops a new two step framework--Texas Two-Step--to solve MISO-D problems with known blurs. Texas Two-Step first reduces the MISO-D problem to a related single-input single-output deconvolution (SISO-D) problem by invoking the concept of sufficient statistics (SSs) and then solves the simpler SISO-D problem using an appropriate technique. The two-step framework enables new MISO-D techniques (both optimal and suboptimal) based on the rich suite of existing SISO-D techniques. In fact, the properties of SSs imply that a MISO-D algorithm is mean-squared-error optimal if and only if it can be rearranged to conform to the Texas Two-Step framework. Using this insight, we construct new wavelet- and curvelet-based MISO-D algorithms with asymptotically optimal performance. Simulated and real data experiments verify that the framework is indeed effective.

Voigt deconvolution method and its applications to pure oxygen absorption spectrum at 1270 nm band.

PubMed

Al-Jalali, Muhammad A; Aljghami, Issam F; Mahzia, Yahia M

2016-03-15

Experimental spectral lines of pure oxygen at 1270 nm band were analyzed by Voigt deconvolution method. The method gave a total Voigt profile, which arises from two overlapping bands. Deconvolution of total Voigt profile leads to two Voigt profiles, the first as a result of O2 dimol at 1264 nm band envelope, and the second from O2 monomer at 1268 nm band envelope. In addition, Voigt profile itself is the convolution of Lorentzian and Gaussian distributions. Competition between thermal and collisional effects was clearly observed through competition between Gaussian and Lorentzian width for each band envelope. Voigt full width at half-maximum height (Voigt FWHM) for each line, and the width ratio between Lorentzian and Gaussian width (ΓLΓG(-1)) have been investigated. The following applied pressures were at 1, 2, 3, 4, 5, and 8 bar, while the temperatures were at 298 K, 323 K, 348 K, and 373 K range. Copyright © 2015 Elsevier B.V. All rights reserved.

A novel SURE-based criterion for parametric PSF estimation.

PubMed

Xue, Feng; Blu, Thierry

2015-02-01

We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

Palladium-based Mass-Tag Cell Barcoding with a Doublet-Filtering Scheme and Single Cell Deconvolution Algorithm

PubMed Central

Zunder, Eli R.; Finck, Rachel; Behbehani, Gregory K.; Amir, El-ad D.; Krishnaswamy, Smita; Gonzalez, Veronica D.; Lorang, Cynthia G.; Bjornson, Zach; Spitzer, Matthew H.; Bodenmiller, Bernd; Fantl, Wendy J.; Pe’er, Dana; Nolan, Garry P.

2015-01-01

SUMMARY Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption, and shortens instrument measurement time. Here, we present an optimized MCB protocol with several improvements over previously described methods. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ~1 h per million cells. PMID:25612231

DECONV-TOOL: An IDL based deconvolution software package

NASA Technical Reports Server (NTRS)

Varosi, F.; Landsman, W. B.

1992-01-01

There are a variety of algorithms for deconvolution of blurred images, each having its own criteria or statistic to be optimized in order to estimate the original image data. Using the Interactive Data Language (IDL), we have implemented the Maximum Likelihood, Maximum Entropy, Maximum Residual Likelihood, and sigma-CLEAN algorithms in a unified environment called DeConv_Tool. Most of the algorithms have as their goal the optimization of statistics such as standard deviation and mean of residuals. Shannon entropy, log-likelihood, and chi-square of the residual auto-correlation are computed by DeConv_Tool for the purpose of determining the performance and convergence of any particular method and comparisons between methods. DeConv_Tool allows interactive monitoring of the statistics and the deconvolved image during computation. The final results, and optionally, the intermediate results, are stored in a structure convenient for comparison between methods and review of the deconvolution computation. The routines comprising DeConv_Tool are available via anonymous FTP through the IDL Astronomy User's Library.

Deconvolutions based on singular value decomposition and the pseudoinverse: a guide for beginners.

PubMed

Hendler, R W; Shrager, R I

1994-01-01

Singular value decomposition (SVD) is deeply rooted in the theory of linear algebra, and because of this is not readily understood by a large group of researchers who could profit from its application. In this paper, we discuss the subject on a level that should be understandable to scientists who are not well versed in linear algebra. However, because it is necessary that certain key concepts in linear algebra be appreciated in order to comprehend what is accomplished by SVD, we present the section, 'Bare basics of linear algebra'. This is followed by a discussion of the theory of SVD. Next we present step-by-step examples to illustrate how SVD is applied to deconvolute a titration involving a mixture of three pH indicators. One noiseless case is presented as well as two cases where either a fixed or varying noise level is present. Finally, we discuss additional deconvolutions of mixed spectra based on the use of the pseudoinverse.

Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

NASA Astrophysics Data System (ADS)

Gong, Changfei; Zeng, Dong; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

2016-03-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

Deconvoluting complex structural histories archived in brittle fault zones

NASA Astrophysics Data System (ADS)

Viola, G.; Scheiber, T.; Fredin, O.; Zwingmann, H.; Margreth, A.; Knies, J.

2016-11-01

Brittle deformation can saturate the Earth's crust with faults and fractures in an apparently chaotic fashion. The details of brittle deformational histories and implications on, for example, seismotectonics and landscape, can thus be difficult to untangle. Fortunately, brittle faults archive subtle details of the stress and physical/chemical conditions at the time of initial strain localization and eventual subsequent slip(s). Hence, reading those archives offers the possibility to deconvolute protracted brittle deformation. Here we report K-Ar isotopic dating of synkinematic/authigenic illite coupled with structural analysis to illustrate an innovative approach to the high-resolution deconvolution of brittle faulting and fluid-driven alteration of a reactivated fault in western Norway. Permian extension preceded coaxial reactivation in the Jurassic and Early Cretaceous fluid-related alteration with pervasive clay authigenesis. This approach represents important progress towards time-constrained structural models, where illite characterization and K-Ar analysis are a fundamental tool to date faulting and alteration in crystalline rocks.

Optimal application of Morrison's iterative noise removal for deconvolution. Appendices

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1987-01-01

Morrison's iterative method of noise removal, or Morrison's smoothing, is applied in a simulation to noise-added data sets of various noise levels to determine its optimum use. Morrison's smoothing is applied for noise removal alone, and for noise removal prior to deconvolution. For the latter, an accurate method is analyzed to provide confidence in the optimization. The method consists of convolving the data with an inverse filter calculated by taking the inverse discrete Fourier transform of the reciprocal of the transform of the response of the system. Various length filters are calculated for the narrow and wide Gaussian response functions used. Deconvolution of non-noisy data is performed, and the error in each deconvolution calculated. Plots are produced of error versus filter length; and from these plots the most accurate length filters determined. The statistical methodologies employed in the optimizations of Morrison's method are similar. A typical peak-type input is selected and convolved with the two response functions to produce the data sets to be analyzed. Both constant and ordinate-dependent Gaussian distributed noise is added to the data, where the noise levels of the data are characterized by their signal-to-noise ratios. The error measures employed in the optimizations are the L1 and L2 norms. Results of the optimizations for both Gaussians, both noise types, and both norms include figures of optimum iteration number and error improvement versus signal-to-noise ratio, and tables of results. The statistical variation of all quantities considered is also given.

Deconvolution of the vestibular evoked myogenic potential.

PubMed

Lütkenhöner, Bernd; Basel, Türker

2012-02-07

The vestibular evoked myogenic potential (VEMP) and the associated variance modulation can be understood by a convolution model. Two functions of time are incorporated into the model: the motor unit action potential (MUAP) of an average motor unit, and the temporal modulation of the MUAP rate of all contributing motor units, briefly called rate modulation. The latter is the function of interest, whereas the MUAP acts as a filter that distorts the information contained in the measured data. Here, it is shown how to recover the rate modulation by undoing the filtering using a deconvolution approach. The key aspects of our deconvolution algorithm are as follows: (1) the rate modulation is described in terms of just a few parameters; (2) the MUAP is calculated by Wiener deconvolution of the VEMP with the rate modulation; (3) the model parameters are optimized using a figure-of-merit function where the most important term quantifies the difference between measured and model-predicted variance modulation. The effectiveness of the algorithm is demonstrated with simulated data. An analysis of real data confirms the view that there are basically two components, which roughly correspond to the waves p13-n23 and n34-p44 of the VEMP. The rate modulation corresponding to the first, inhibitory component is much stronger than that corresponding to the second, excitatory component. But the latter is more extended so that the two modulations have almost the same equivalent rectangular duration. Copyright © 2011 Elsevier Ltd. All rights reserved.

ADAP-GC 3.0: Improved Peak Detection and Deconvolution of Co-eluting Metabolites from GC/TOF-MS Data for Metabolomics Studies

PubMed Central

Ni, Yan; Su, Mingming; Qiu, Yunping; Jia, Wei

2017-01-01

ADAP-GC is an automated computational pipeline for untargeted, GC-MS-based metabolomics studies. It takes raw mass spectrometry data as input and carries out a sequence of data processing steps including construction of extracted ion chromatograms, detection of chromatographic peak features, deconvolution of co-eluting compounds, and alignment of compounds across samples. Despite the increased accuracy from the original version to version 2.0 in terms of extracting metabolite information for identification and quantitation, ADAP-GC 2.0 requires appropriate specification of a number of parameters and has difficulty in extracting information of compounds that are in low concentration. To overcome these two limitations, ADAP-GC 3.0 was developed to improve both the robustness and sensitivity of compound detection. In this paper, we report how these goals were achieved and compare ADAP-GC 3.0 against three other software tools including ChromaTOF, AnalyzerPro, and AMDIS that are widely used in the metabolomics community. PMID:27461032

ADAP-GC 3.0: Improved Peak Detection and Deconvolution of Co-eluting Metabolites from GC/TOF-MS Data for Metabolomics Studies.

PubMed

Ni, Yan; Su, Mingming; Qiu, Yunping; Jia, Wei; Du, Xiuxia

2016-09-06

ADAP-GC is an automated computational pipeline for untargeted, GC/MS-based metabolomics studies. It takes raw mass spectrometry data as input and carries out a sequence of data processing steps including construction of extracted ion chromatograms, detection of chromatographic peak features, deconvolution of coeluting compounds, and alignment of compounds across samples. Despite the increased accuracy from the original version to version 2.0 in terms of extracting metabolite information for identification and quantitation, ADAP-GC 2.0 requires appropriate specification of a number of parameters and has difficulty in extracting information on compounds that are in low concentration. To overcome these two limitations, ADAP-GC 3.0 was developed to improve both the robustness and sensitivity of compound detection. In this paper, we report how these goals were achieved and compare ADAP-GC 3.0 against three other software tools including ChromaTOF, AnalyzerPro, and AMDIS that are widely used in the metabolomics community.

Understanding AuNP interaction with low-generation PAMAM dendrimers: a CIELab and deconvolution study

NASA Astrophysics Data System (ADS)

Jimenez-Ruiz, A.; Carnerero, J. M.; Castillo, P. M.; Prado-Gotor, R.

2017-01-01

Low-generation polyamidoamine (PAMAM) dendrimers are known to adsorb on the surface of gold nanoparticles (AuNPs) causing aggregation and color changes. In this paper, a thorough study of this affinity using absorption spectroscopy, colorimetric, and emission methods has been carried out. Results show that, for citrate-capped gold nanoparticles, interaction with the dendrimer is not only of an electrostatic character but instead occurs, at least in part, through the dendrimer's uncharged internal amino groups. The possibilities of the CIELab chromaticity system parameters' evolution have also been explored in order to quantify dendrimer interaction with the red-colored nanoparticles. By measuring and quantifying 17 nm citrate-capped AuNP color changes, which are strongly dependant on their aggregation state, binding free energies are obtained for the first time for these systems. Results are confirmed via an alternate fitting method which makes use of deconvolution parameters from absorbance spectra. Binding free energies obtained through the use of both means are in good agreement with each other.

Evanescent field microscopy techniques for studying dynamics at the surface of living cells

NASA Astrophysics Data System (ADS)

Sund, Susan E.

This thesis presents two distinct optical microscopy techniques for applications in cell biophysics: (a)the extension to living cells of an established technique, total internal reflection/fluorescence recovery after photobleaching (TIR/FRAP) for the first time in imaging mode; and (b)the novel development of polarized total internal reflection fluorescence (p- TIRF) to study membrane orientation in living cells. Although reversible chemistry is crucial to dynamical processes in living cells, relatively little is known about the relevant chemical kinetic rates in vivo. TIR/FRAP, an established technique which can measure reversible biomolecular kinetic rates at surfaces, is extended here to measure kinetic parameters of microinjected rhodamine actin at the cytofacial surface of the plasma membrane of living cultured smooth muscle cells. For the first time, spatial imaging (with a CCD camera) is used in conjunction with TIR/FRAP. TIR/FRAP imaging allows production of spatially resolved images of kinetic data, and calculation of correlation distances, cell-wide gradients, and kinetic parameter dependence on initial fluorescence intensity. In living cells, membrane curvature occurs both in easily imaged large scale morphological features, and also in less visualizable submicroscopic regions of activity such as endocytosis, exocytosis, and cell surface ruffling. A fluorescence microscopic method, p-TIRF, is introduced here to visualize such regions. The method is based on fluorescence of the oriented membrane probe diI- C18-(3) (diI) excited by evanescent field light polarized either perpendicular or parallel to the plane of the substrate coverslip. The excitation efficiency from each polarization depends on the membrane orientation, and thus the ratio of the observed fluorescence excited by these two polarizations vividly shows regions of microscopic and submicroscopic curvature of the membrane. A theoretical background of the technique and experimental verifications are presented in samples of protein solutions, model lipid bilayers, and living cells. Sequential digital images of the polarized TIR fluorescence ratios show spatially-resolved time- course maps of membrane orientations on diI labeled macrophages from which low visibility membrane structures can be identified and quantified. The TIR images are sharpened and contrast-enhanced by deconvoluting them with an experimentally-measured point spread function.

Real-time blind image deconvolution based on coordinated framework of FPGA and DSP

NASA Astrophysics Data System (ADS)

Wang, Ze; Li, Hang; Zhou, Hua; Liu, Hongjun

2015-10-01

Image restoration takes a crucial place in several important application domains. With the increasing of computation requirement as the algorithms become much more complexity, there has been a significant rise in the need for accelerating implementation. In this paper, we focus on an efficient real-time image processing system for blind iterative deconvolution method by means of the Richardson-Lucy (R-L) algorithm. We study the characteristics of algorithm, and an image restoration processing system based on the coordinated framework of FPGA and DSP (CoFD) is presented. Single precision floating-point processing units with small-scale cascade and special FFT/IFFT processing modules are adopted to guarantee the accuracy of the processing. Finally, Comparing experiments are done. The system could process a blurred image of 128×128 pixels within 32 milliseconds, and is up to three or four times faster than the traditional multi-DSPs systems.

Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.

PubMed

Wang, Chuangqi; Choi, Hee June; Kim, Sung-Jin; Desai, Aesha; Lee, Namgyu; Kim, Dohoon; Bae, Yongho; Lee, Kwonmoo

2018-04-27

Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanism of cell protrusion has been understood based on the ensemble average of actin regulator dynamics. Here, we establish a computational framework called HACKS (deconvolution of heterogeneous activity in coordination of cytoskeleton at the subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion from live cell imaging. HACKS identifies distinct subcellular protrusion phenotypes based on machine-learning algorithms and reveals their underlying actin regulator dynamics at the leading edge. Using our method, we discover "accelerating protrusion", which is driven by the temporally ordered coordination of Arp2/3 and VASP activities. We validate our finding by pharmacological perturbations and further identify the fine regulation of Arp2/3 and VASP recruitment associated with accelerating protrusion. Our study suggests HACKS can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation.

Comment on the paper "Thermoluminescence glow-curve deconvolution functions for mixed order of kinetics and continuous trap distribution by G. Kitis, J.M. Gomez-Ros, Nuclear Instruments and Methods in Physics Research A 440, 2000, pp 224-231"

NASA Astrophysics Data System (ADS)

Kazakis, Nikolaos A.

2018-01-01

The present comment concerns the correct presentation of an algorithm proposed in the above paper for the glow-curve deconvolution in the case of continuous distribution of trapping states. Since most researchers would use directly the proposed algorithm as published, they should be notified of its correct formulation during the fitting of TL glow curves of materials with continuous trap distribution using this Equation.

An l1-TV algorithm for deconvolution with salt and pepper noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wohlberg, Brendt; Rodriguez, Paul

2008-01-01

There has recently been considerable interest in applying Total Variation with an {ell}{sup 1} data fidelity term to the denoising of images subject to salt and pepper noise, but the extension of this formulation to more general problems, such as deconvolution, has received little attention, most probably because most efficient algorithms for {ell}{sup 1}-TV denoising can not handle more general inverse problems. We apply the Iteratively Reweighted Norm algorithm to this problem, and compare performance with an alternative algorithm based on the Mumford-Shah functional.

Machine Learning Approach to Deconvolution of Thermal Infrared (TIR) Spectrum of Mercury Supporting MERTIS Onboard ESA/JAXA BepiColombo

NASA Astrophysics Data System (ADS)

Varatharajan, I.; D'Amore, M.; Maturilli, A.; Helbert, J.; Hiesinger, H.

2018-04-01

Machine learning approach to spectral unmixing of emissivity spectra of Mercury is carried out using endmember spectral library measured at simulated daytime surface conditions of Mercury. Study supports MERTIS payload onboard ESA/JAXA BepiColombo.

Statistical Deconvolution for Superresolution Fluorescence Microscopy

PubMed Central

Mukamel, Eran A.; Babcock, Hazen; Zhuang, Xiaowei

2012-01-01

Superresolution microscopy techniques based on the sequential activation of fluorophores can achieve image resolution of ∼10 nm but require a sparse distribution of simultaneously activated fluorophores in the field of view. Image analysis procedures for this approach typically discard data from crowded molecules with overlapping images, wasting valuable image information that is only partly degraded by overlap. A data analysis method that exploits all available fluorescence data, regardless of overlap, could increase the number of molecules processed per frame and thereby accelerate superresolution imaging speed, enabling the study of fast, dynamic biological processes. Here, we present a computational method, referred to as deconvolution-STORM (deconSTORM), which uses iterative image deconvolution in place of single- or multiemitter localization to estimate the sample. DeconSTORM approximates the maximum likelihood sample estimate under a realistic statistical model of fluorescence microscopy movies comprising numerous frames. The model incorporates Poisson-distributed photon-detection noise, the sparse spatial distribution of activated fluorophores, and temporal correlations between consecutive movie frames arising from intermittent fluorophore activation. We first quantitatively validated this approach with simulated fluorescence data and showed that deconSTORM accurately estimates superresolution images even at high densities of activated fluorophores where analysis by single- or multiemitter localization methods fails. We then applied the method to experimental data of cellular structures and demonstrated that deconSTORM enables an approximately fivefold or greater increase in imaging speed by allowing a higher density of activated fluorophores/frame. PMID:22677393

Myocardial perfusion quantification using simultaneously acquired 13 NH3 -ammonia PET and dynamic contrast-enhanced MRI in patients at rest and stress.

PubMed

Kunze, Karl P; Nekolla, Stephan G; Rischpler, Christoph; Zhang, Shelley HuaLei; Hayes, Carmel; Langwieser, Nicolas; Ibrahim, Tareq; Laugwitz, Karl-Ludwig; Schwaiger, Markus

2018-04-19

Systematic differences with respect to myocardial perfusion quantification exist between DCE-MRI and PET. Using the potential of integrated PET/MRI, this study was conceived to compare perfusion quantification on the basis of simultaneously acquired 13 NH 3 -ammonia PET and DCE-MRI data in patients at rest and stress. Twenty-nine patients were examined on a 3T PET/MRI scanner. DCE-MRI was implemented in dual-sequence design and additional T 1 mapping for signal normalization. Four different deconvolution methods including a modified version of the Fermi technique were compared against 13 NH 3 -ammonia results. Cohort-average flow comparison yielded higher resting flows for DCE-MRI than for PET and, therefore, significantly lower DCE-MRI perfusion ratios under the common assumption of equal arterial and tissue hematocrit. Absolute flow values were strongly correlated in both slice-average (R 2  = 0.82) and regional (R 2  = 0.7) evaluations. Different DCE-MRI deconvolution methods yielded similar flow result with exception of an unconstrained Fermi method exhibiting outliers at high flows when compared with PET. Thresholds for Ischemia classification may not be directly tradable between PET and MRI flow values. Differences in perfusion ratios between PET and DCE-MRI may be lifted by using stress/rest-specific hematocrit conversion. Proper physiological constraints are advised in model-constrained deconvolution. © 2018 International Society for Magnetic Resonance in Medicine.

Coordinate axes, location of origin, and redundancy for the one and two-dimensional discrete Fourier transform

NASA Technical Reports Server (NTRS)

Ioup, G. E.; Ioup, J. W.

1985-01-01

Appendix 4 of the Study of One- and Two-Dimensional Filtering and Deconvolution Algorithms for a Streaming Array Computer discusses coordinate axes, location of origin, and redundancy for the one- and two-dimensional Fourier transform for complex and real data.

An improved method for polarimetric image restoration in interferometry

NASA Astrophysics Data System (ADS)

Pratley, Luke; Johnston-Hollitt, Melanie

2016-11-01

Interferometric radio astronomy data require the effects of limited coverage in the Fourier plane to be accounted for via a deconvolution process. For the last 40 years this process, known as `cleaning', has been performed almost exclusively on all Stokes parameters individually as if they were independent scalar images. However, here we demonstrate for the case of the linear polarization P, this approach fails to properly account for the complex vector nature resulting in a process which is dependent on the axes under which the deconvolution is performed. We present here an improved method, `Generalized Complex CLEAN', which properly accounts for the complex vector nature of polarized emission and is invariant under rotations of the deconvolution axes. We use two Australia Telescope Compact Array data sets to test standard and complex CLEAN versions of the Högbom and SDI (Steer-Dwedney-Ito) CLEAN algorithms. We show that in general the complex CLEAN version of each algorithm produces more accurate clean components with fewer spurious detections and lower computation cost due to reduced iterations than the current methods. In particular, we find that the complex SDI CLEAN produces the best results for diffuse polarized sources as compared with standard CLEAN algorithms and other complex CLEAN algorithms. Given the move to wide-field, high-resolution polarimetric imaging with future telescopes such as the Square Kilometre Array, we suggest that Generalized Complex CLEAN should be adopted as the deconvolution method for all future polarimetric surveys and in particular that the complex version of an SDI CLEAN should be used.

Water Residence Time estimation by 1D deconvolution in the form of a l2 -regularized inverse problem with smoothness, positivity and causality constraints

NASA Astrophysics Data System (ADS)

Meresescu, Alina G.; Kowalski, Matthieu; Schmidt, Frédéric; Landais, François

2018-06-01

The Water Residence Time distribution is the equivalent of the impulse response of a linear system allowing the propagation of water through a medium, e.g. the propagation of rain water from the top of the mountain towards the aquifers. We consider the output aquifer levels as the convolution between the input rain levels and the Water Residence Time, starting with an initial aquifer base level. The estimation of Water Residence Time is important for a better understanding of hydro-bio-geochemical processes and mixing properties of wetlands used as filters in ecological applications, as well as protecting fresh water sources for wells from pollutants. Common methods of estimating the Water Residence Time focus on cross-correlation, parameter fitting and non-parametric deconvolution methods. Here we propose a 1D full-deconvolution, regularized, non-parametric inverse problem algorithm that enforces smoothness and uses constraints of causality and positivity to estimate the Water Residence Time curve. Compared to Bayesian non-parametric deconvolution approaches, it has a fast runtime per test case; compared to the popular and fast cross-correlation method, it produces a more precise Water Residence Time curve even in the case of noisy measurements. The algorithm needs only one regularization parameter to balance between smoothness of the Water Residence Time and accuracy of the reconstruction. We propose an approach on how to automatically find a suitable value of the regularization parameter from the input data only. Tests on real data illustrate the potential of this method to analyze hydrological datasets.

Pulse-Inversion Subharmonic Ultrafast Active Cavitation Imaging in Tissue Using Fast Eigenspace-Based Adaptive Beamforming and Cavitation Deconvolution.

PubMed

Bai, Chen; Xu, Shanshan; Duan, Junbo; Jing, Bowen; Yang, Miao; Wan, Mingxi

2017-08-01

Pulse-inversion subharmonic (PISH) imaging can display information relating to pure cavitation bubbles while excluding that of tissue. Although plane-wave-based ultrafast active cavitation imaging (UACI) can monitor the transient activities of cavitation bubbles, its resolution and cavitation-to-tissue ratio (CTR) are barely satisfactory but can be significantly improved by introducing eigenspace-based (ESB) adaptive beamforming. PISH and UACI are a natural combination for imaging of pure cavitation activity in tissue; however, it raises two problems: 1) the ESB beamforming is hard to implement in real time due to the enormous amount of computation associated with the covariance matrix inversion and eigendecomposition and 2) the narrowband characteristic of the subharmonic filter will incur a drastic degradation in resolution. Thus, in order to jointly address these two problems, we propose a new PISH-UACI method using novel fast ESB (F-ESB) beamforming and cavitation deconvolution for nonlinear signals. This method greatly reduces the computational complexity by using F-ESB beamforming through dimensionality reduction based on principal component analysis, while maintaining the high quality of ESB beamforming. The degraded resolution is recovered using cavitation deconvolution through a modified convolution model and compressive deconvolution. Both simulations and in vitro experiments were performed to verify the effectiveness of the proposed method. Compared with the ESB-based PISH-UACI, the entire computation of our proposed approach was reduced by 99%, while the axial resolution gain and CTR were increased by 3 times and 2 dB, respectively, confirming that satisfactory performance can be obtained for monitoring pure cavitation bubbles in tissue erosion.

Wavespace-Based Coherent Deconvolution

NASA Technical Reports Server (NTRS)

Bahr, Christopher J.; Cattafesta, Louis N., III

2012-01-01

Array deconvolution is commonly used in aeroacoustic analysis to remove the influence of a microphone array's point spread function from a conventional beamforming map. Unfortunately, the majority of deconvolution algorithms assume that the acoustic sources in a measurement are incoherent, which can be problematic for some aeroacoustic phenomena with coherent, spatially-distributed characteristics. While several algorithms have been proposed to handle coherent sources, some are computationally intractable for many problems while others require restrictive assumptions about the source field. Newer generalized inverse techniques hold promise, but are still under investigation for general use. An alternate coherent deconvolution method is proposed based on a wavespace transformation of the array data. Wavespace analysis offers advantages over curved-wave array processing, such as providing an explicit shift-invariance in the convolution of the array sampling function with the acoustic wave field. However, usage of the wavespace transformation assumes the acoustic wave field is accurately approximated as a superposition of plane wave fields, regardless of true wavefront curvature. The wavespace technique leverages Fourier transforms to quickly evaluate a shift-invariant convolution. The method is derived for and applied to ideal incoherent and coherent plane wave fields to demonstrate its ability to determine magnitude and relative phase of multiple coherent sources. Multi-scale processing is explored as a means of accelerating solution convergence. A case with a spherical wave front is evaluated. Finally, a trailing edge noise experiment case is considered. Results show the method successfully deconvolves incoherent, partially-coherent, and coherent plane wave fields to a degree necessary for quantitative evaluation. Curved wave front cases warrant further investigation. A potential extension to nearfield beamforming is proposed.

Extracting the building response using seismic interferometry: Theory and application to the Millikan Library in Pasadena, California

USGS Publications Warehouse

Snieder, R.; Safak, E.

2006-01-01

The motion of a building depends on the excitation, the coupling of the building to the ground, and the mechanical properties of the building. We separate the building response from the excitation and the ground coupling by deconvolving the motion recorded at different levels in the building and apply this to recordings of the motion in the Robert A. Millikan Library in Pasadena, California. This deconvolution allows for the separation of instrinsic attenuation and radiation damping. The waveforms obtained from deconvolution with the motion in the top floor show a superposition of one upgoing and one downgoing wave. The waveforms obtained by deconvolution with the motion in the basement can be formulated either as a sum of upgoing and downgoing waves, or as a sum over normal modes. Because these deconvolved waves for late time have a monochromatic character, they are most easily analyzed with normal-mode theory. For this building we estimate a shear velocity c = 322 m/sec and a quality factor Q = 20. These values explain both the propagating waves and the normal modes.

Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy

NASA Astrophysics Data System (ADS)

Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

2011-06-01

With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality.

Supersampling multiframe blind deconvolution resolution enhancement of adaptive-optics-compensated imagery of LEO satellites

NASA Astrophysics Data System (ADS)

Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

2000-10-01

A post-processing methodology for reconstructing undersampled image sequences with randomly varying blur is described which can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive optics compensated imagery taken by the Starfire Optical Range 3.5 meter telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques which includes a representation of spatial sampling by the focal plane array elements in the forward stochastic model of the imaging system. This generalization enables the random shifts and shape of the adaptive compensated PSF to be used to partially eliminate the aliasing effects associated with sub- Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss which occurs when imaging in wide FOV modes.

Supersampling multiframe blind deconvolution resolution enhancement of adaptive optics compensated imagery of low earth orbit satellites

NASA Astrophysics Data System (ADS)

Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

2002-09-01

We describe a postprocessing methodology for reconstructing undersampled image sequences with randomly varying blur that can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive-optics-(AO)-compensated imagery taken by the Starfire Optical Range 3.5-m telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground-based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques that include a representation of spatial sampling by the focal plane array elements based on a forward stochastic model. This generalization enables the random shifts and shape of the AO- compensated point spread function (PSF) to be used to partially eliminate the aliasing effects associated with sub-Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss that occurs when imaging in wide- field-of-view (FOV) modes.

Pulse analysis of acoustic emission signals

NASA Technical Reports Server (NTRS)

Houghton, J. R.; Packman, P. F.

1977-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameter values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emission associated with (a) crack propagation, (b) ball dropping on a plate, (c) spark discharge, and (d) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train is shown to be the region in which the significant signatures of the acoustic emission event are to be found.

Scanning two-photon microscopy with upconverting lanthanide nanoparticles via Richardson-Lucy deconvolution.

PubMed

Gainer, Christian F; Utzinger, Urs; Romanowski, Marek

2012-07-01

The use of upconverting lanthanide nanoparticles in fast-scanning microscopy is hindered by a long luminescence decay time, which greatly blurs images acquired in a nondescanned mode. We demonstrate herein an image processing method based on Richardson-Lucy deconvolution that mitigates the detrimental effects of their luminescence lifetime. This technique generates images with lateral resolution on par with the system's performance, ∼1.2  μm, while maintaining an axial resolution of 5 μm or better at a scan rate comparable with traditional two-photon microscopy. Remarkably, this can be accomplished with near infrared excitation power densities of 850 W/cm(2), several orders of magnitude below those used in two-photon imaging with molecular fluorophores. By way of illustration, we introduce the use of lipids to coat and functionalize these nanoparticles, rendering them water dispersible and readily conjugated to biologically relevant ligands, in this case epidermal growth factor receptor antibody. This deconvolution technique combined with the functionalized nanoparticles will enable three-dimensional functional tissue imaging at exceptionally low excitation power densities.

A spatially-variant deconvolution method based on total variation for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Almasganj, Mohammad; Adabi, Saba; Fatemizadeh, Emad; Xu, Qiuyun; Sadeghi, Hamid; Daveluy, Steven; Nasiriavanaki, Mohammadreza

2017-03-01

Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.

A stopping criterion to halt iterations at the Richardson-Lucy deconvolution of radiographic images

NASA Astrophysics Data System (ADS)

Almeida, G. L.; Silvani, M. I.; Souza, E. S.; Lopes, R. T.

2015-07-01

Radiographic images, as any experimentally acquired ones, are affected by spoiling agents which degrade their final quality. The degradation caused by agents of systematic character, can be reduced by some kind of treatment such as an iterative deconvolution. This approach requires two parameters, namely the system resolution and the best number of iterations in order to achieve the best final image. This work proposes a novel procedure to estimate the best number of iterations, which replaces the cumbersome visual inspection by a comparison of numbers. These numbers are deduced from the image histograms, taking into account the global difference G between them for two subsequent iterations. The developed algorithm, including a Richardson-Lucy deconvolution procedure has been embodied into a Fortran program capable to plot the 1st derivative of G as the processing progresses and to stop it automatically when this derivative - within the data dispersion - reaches zero. The radiograph of a specially chosen object acquired with thermal neutrons from the Argonauta research reactor at Institutode Engenharia Nuclear - CNEN, Rio de Janeiro, Brazil, have undergone this treatment with fair results.

Fast online deconvolution of calcium imaging data

PubMed Central

Zhou, Pengcheng; Paninski, Liam

2017-01-01

Fluorescent calcium indicators are a popular means for observing the spiking activity of large neuronal populations, but extracting the activity of each neuron from raw fluorescence calcium imaging data is a nontrivial problem. We present a fast online active set method to solve this sparse non-negative deconvolution problem. Importantly, the algorithm 3progresses through each time series sequentially from beginning to end, thus enabling real-time online estimation of neural activity during the imaging session. Our algorithm is a generalization of the pool adjacent violators algorithm (PAVA) for isotonic regression and inherits its linear-time computational complexity. We gain remarkable increases in processing speed: more than one order of magnitude compared to currently employed state of the art convex solvers relying on interior point methods. Unlike these approaches, our method can exploit warm starts; therefore optimizing model hyperparameters only requires a handful of passes through the data. A minor modification can further improve the quality of activity inference by imposing a constraint on the minimum spike size. The algorithm enables real-time simultaneous deconvolution of O(105) traces of whole-brain larval zebrafish imaging data on a laptop. PMID:28291787

[Deconvolution of overlapped peaks in total ion chromatogram of essential oil from citri reticulatae pericarpium viride by automated mass spectral deconvolution & identification system].

PubMed

Wang, Jian; Chen, Hong-Ping; Liu, You-Ping; Wei, Zheng; Liu, Rong; Fan, Dan-Qing

2013-05-01

This experiment shows how to use the automated mass spectral deconvolution & identification system (AMDIS) to deconvolve the overlapped peaks in the total ion chromatogram (TIC) of volatile oil from Chineses materia medica (CMM). The essential oil was obtained by steam distillation. Its TIC was gotten by GC-MS, and the superimposed peaks in TIC were deconvolved by AMDIS. First, AMDIS can detect the number of components in TIC through the run function. Then, by analyzing the extracted spectrum of corresponding scan point of detected component and the original spectrum of this scan point, and their counterparts' spectra in the referred MS Library, researchers can ascertain the component's structure accurately or deny some compounds, which don't exist in nature. Furthermore, through examining the changeability of characteristic fragment ion peaks of identified compounds, the previous outcome can be affirmed again. The result demonstrated that AMDIS could efficiently deconvolve the overlapped peaks in TIC by taking out the spectrum of matching scan point of discerned component, which led to exact identification of the component's structure.

Thorium concentrations in the lunar surface. V - Deconvolution of the central highlands region

NASA Technical Reports Server (NTRS)

Metzger, A. E.; Etchegaray-Ramirez, M. I.; Haines, E. L.

1982-01-01

The distribution of thorium in the lunar central highlands measured from orbit by the Apollo 16 gamma-ray spectrometer is subjected to a deconvolution analysis to yield improved spatial resolution and contrast. Use of two overlapping data fields for complete coverage also provides a demonstration of the technique's ability to model concentrations several degrees beyond the data track. Deconvolution reveals an association between Th concentration and the Kant Plateau, Descartes Mountain and Cayley plains surface formations. The Kant Plateau and Descartes Mountains model with Th less than 1 part per million, which is typical of farside highlands but is infrequently seen over any other nearside highland portions of the Apollo 15 and 16 ground tracks. It is noted that, if the Cayley plains are the result of basin-forming impact ejecta, the distribution of Th concentration with longitude supports an origin from the Imbrium basin rather than the Nectaris or Orientale basins. Nectaris basin materials are found to have a Th concentration similar to that of the Descartes Mountains, evidence that the latter may have been emplaced as Nectaris basin impact deposits.

An Optimal Deconvolution Method for Reconstructing Pneumatically Distorted Near-Field Sonic Boom Pressure Measurements

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Haering, Edward A., Jr.; Ehernberger, L. J.

1996-01-01

In-flight measurements of the SR-71 near-field sonic boom were obtained by an F-16XL airplane at flightpath separation distances from 40 to 740 ft. Twenty-two signatures were obtained from Mach 1.60 to Mach 1.84 and altitudes from 47,600 to 49,150 ft. The shock wave signatures were measured by the total and static sensors on the F-16XL noseboo. These near-field signature measurements were distorted by pneumatic attenuation in the pitot-static sensors and accounting for their effects using optimal deconvolution. Measurement system magnitude and phase characteristics were determined from ground-based step-response tests and extrapolated to flight conditions using analytical models. Deconvolution was implemented using Fourier transform methods. Comparisons of the shock wave signatures reconstructed from the total and static pressure data are presented. The good agreement achieved gives confidence of the quality of the reconstruction analysis. although originally developed to reconstruct the sonic boom signatures from SR-71 sonic boom flight tests, the methods presented here generally apply to other types of highly attenuated or distorted pneumatic measurements.

Two-dimensional imaging of two types of radicals by the CW-EPR method

NASA Astrophysics Data System (ADS)

Czechowski, Tomasz; Krzyminiewski, Ryszard; Jurga, Jan; Chlewicki, Wojciech

2008-01-01

The CW-EPR method of image reconstruction is based on sample rotation in a magnetic field with a constant gradient (50 G/cm). In order to obtain a projection (radical density distribution) along a given direction, the EPR spectra are recorded with and without the gradient. Deconvolution, then gives the distribution of the spin density. Projection at 36 different angles gives the information that is necessary for reconstruction of the radical distribution. The problem becomes more complex when there are at least two types of radicals in the sample, because the deconvolution procedure does not give satisfactory results. We propose a method to calculate the projections for each radical, based on iterative procedures. The images of density distribution for each radical obtained by our procedure have proved that the method of deconvolution, in combination with iterative fitting, provides correct results. The test was performed on a sample of polymer PPS Br 111 ( p-phenylene sulphide) with glass fibres and minerals. The results indicated a heterogeneous distribution of radicals in the sample volume. The images obtained were in agreement with the known shape of the sample.

Pulse analysis of acoustic emission signals

NASA Technical Reports Server (NTRS)

Houghton, J. R.; Packman, P. F.

1977-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis, and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameters values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emissions associated with: (1) crack propagation, (2) ball dropping on a plate, (3) spark discharge and (4) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train are shown to be the region in which the significant signatures of the acoustic emission event are to be found.

Blind image deconvolution using the Fields of Experts prior

NASA Astrophysics Data System (ADS)

Dong, Wende; Feng, Huajun; Xu, Zhihai; Li, Qi

2012-11-01

In this paper, we present a method for single image blind deconvolution. To improve its ill-posedness, we formulate the problem under Bayesian probabilistic framework and use a prior named Fields of Experts (FoE) which is learnt from natural images to regularize the latent image. Furthermore, due to the sparse distribution of the point spread function (PSF), we adopt a Student-t prior to regularize it. An improved alternating minimization (AM) approach is proposed to solve the resulted optimization problem. Experiments on both synthetic and real world blurred images show that the proposed method can achieve results of high quality.

Application of the Lucy–Richardson Deconvolution Procedure to High Resolution Photoemission Spectra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rameau, J.; Yang, H.-B.; Johnson, P.D.

2010-07-01

Angle-resolved photoemission has developed into one of the leading probes of the electronic structure and associated dynamics of condensed matter systems. As with any experimental technique the ability to resolve features in the spectra is ultimately limited by the resolution of the instrumentation used in the measurement. Previously developed for sharpening astronomical images, the Lucy-Richardson deconvolution technique proves to be a useful tool for improving the photoemission spectra obtained in modern hemispherical electron spectrometers where the photoelectron spectrum is displayed as a 2D image in energy and momentum space.

Comment on ‘A novel method for fast and robust estimation of fluorescence decay dynamics using constrained least-square deconvolution with Laguerre expansion’

NASA Astrophysics Data System (ADS)

Zhang, Yongliang; Day-Uei Li, David

2017-02-01

This comment is to clarify that Poisson noise instead of Gaussian noise shall be included to assess the performances of least-squares deconvolution with Laguerre expansion (LSD-LE) for analysing fluorescence lifetime imaging data obtained from time-resolved systems. Moreover, we also corrected an equation in the paper. As the LSD-LE method is rapid and has the potential to be widely applied not only for diagnostic but for wider bioimaging applications, it is desirable to have precise noise models and equations.

Calculation of total cross sections for charge exchange in molecular collisions

NASA Technical Reports Server (NTRS)

Ioup, J.

1979-01-01

Areas of investigation summarized include nitrogen ion-nitrogen molecule collisions; molecular collisions with surfaces; molecular identification from analysis of cracking patterns of selected gases; computer modelling of a quadrupole mass spectrometer; study of space charge in a quadrupole; transmission of the 127 deg cylindrical electrostatic analyzer; and mass spectrometer data deconvolution.

Target Deconvolution Efforts on Wnt Pathway Screen Reveal Dual Modulation of Oxidative Phosphorylation and SERCA2.

PubMed

Casás-Selves, Matias; Zhang, Andrew X; Dowling, James E; Hallén, Stefan; Kawatkar, Aarti; Pace, Nicholas J; Denz, Christopher R; Pontz, Timothy; Garahdaghi, Farzin; Cao, Qing; Sabirsh, Alan; Thakur, Kumar; O'Connell, Nichole; Hu, Jun; Cornella-Taracido, Iván; Weerapana, Eranthie; Zinda, Michael; Goodnow, Robert A; Castaldi, M Paola

2017-06-21

Wnt signaling is critical for development, cell proliferation and differentiation, and mutations in this pathway resulting in constitutive signaling have been implicated in various cancers. A pathway screen using a Wnt-dependent reporter identified a chemical series based on a 1,2,3-thiadiazole-5-carboxamide (TDZ) core with sub-micromolar potency. Herein we report a comprehensive mechanism-of-action deconvolution study toward identifying the efficacy target(s) and biological implication of this chemical series involving bottom-up quantitative chemoproteomics, cell biology, and biochemical methods. Through observing the effects of our probes on metabolism and performing confirmatory cellular and biochemical assays, we found that this chemical series inhibits ATP synthesis by uncoupling the mitochondrial potential. Affinity chemoproteomics experiments identified sarco(endo)plasmic reticulum Ca 2+ -dependent ATPase (SERCA2) as a binding partner of the TDZ series, and subsequent validation studies suggest that the TDZ series can act as ionophores through SERCA2 toward Wnt pathway inhibition. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

TL-OSL correlation studies of LiMgPO4:Tb,B dosimetric phosphor

NASA Astrophysics Data System (ADS)

Singh, A. K.; Menon, S. N.; Dhabekar, Bhushan; Kadam, Sonal; Chougaonkar, M. P.; Mayya, Y. S.

2012-03-01

The recently synthesized LiMgPO4:Tb,B (LMP) is a highly sensitive Optically Stimulated Luminescence (OSL) phosphor for dosimetric applications. Studies were carried out to assess the correlation between thermoluminescence (TL) and OSL of this phosphor. Measurements like Residual TL (R-TL), Continuous Wave OSL (CW-OSL) and Linearly Modulated OSL (LM-OSL) of LMP were carried out and various curves thus obtained were de-convolved using Computerized Curve Deconvolution (CCD) program. The deconvolution of CW-OSL and LM-OSL curves showed five different first order components in LMP. It was observed that OSL signal of LMP has its origin from five traps having different photo-ionization cross-sections. Same traps were found to be responsible for both TL and OSL in this phosphor. Bleaching decay rates were calculated for each R-TL glow peaks and compared with the decay rates of individual OSL components. The value of decay rates of R-TL and OSL matches well. Experimental verification of presence of individual OSL components using tbleach-tmax method was carried out.

Combining a Deconvolution and a Universal Library Search Algorithm for the Nontarget Analysis of Data-Independent Acquisition Mode Liquid Chromatography-High-Resolution Mass Spectrometry Results.

PubMed

Samanipour, Saer; Reid, Malcolm J; Bæk, Kine; Thomas, Kevin V

2018-04-17

Nontarget analysis is considered one of the most comprehensive tools for the identification of unknown compounds in a complex sample analyzed via liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Due to the complexity of the data generated via LC-HRMS, the data-dependent acquisition mode, which produces the MS 2 spectra of a limited number of the precursor ions, has been one of the most common approaches used during nontarget screening. However, data-independent acquisition mode produces highly complex spectra that require proper deconvolution and library search algorithms. We have developed a deconvolution algorithm and a universal library search algorithm (ULSA) for the analysis of complex spectra generated via data-independent acquisition. These algorithms were validated and tested using both semisynthetic and real environmental data. A total of 6000 randomly selected spectra from MassBank were introduced across the total ion chromatograms of 15 sludge extracts at three levels of background complexity for the validation of the algorithms via semisynthetic data. The deconvolution algorithm successfully extracted more than 60% of the added ions in the analytical signal for 95% of processed spectra (i.e., 3 complexity levels multiplied by 6000 spectra). The ULSA ranked the correct spectra among the top three for more than 95% of cases. We further tested the algorithms with 5 wastewater effluent extracts for 59 artificial unknown analytes (i.e., their presence or absence was confirmed via target analysis). These algorithms did not produce any cases of false identifications while correctly identifying ∼70% of the total inquiries. The implications, capabilities, and the limitations of both algorithms are further discussed.

Raman Spectra of Crystalline Double Calcium Orthovanadates Ca10M(VO4)7 (M = Li, K, Na) and Their Interpretation Based on Deconvolution Into Voigt Profiles

NASA Astrophysics Data System (ADS)

Khodasevich, I. A.; Voitikov, S. V.; Orlovich, V. A.; Kosmyna, M. B.; Shekhovtsov, A. N.

2016-09-01

Unpolarized spontaneous Raman spectra of crystalline double calcium orthovanadates Ca10M(VO4)7 (M = Li, K, Na) in the range 150-1600 cm-1 were measured. Two vibrational bands with full-width at half-maximum (FWHM) of 37-50 cm-1 were found in the regions 150-500 and 700-1000 cm-1. The band shapes were approximated well by deconvolution into Voigt profiles. The band at 700-1000 cm-1 was stronger and deconvoluted into eight Voigt profiles. The frequencies of two strong lines were ~848 and ~862 cm-1 for Ca10Li(VO4)7; ~850 and ~866 cm-1 for Ca10Na(VO4)7; and ~844 and ~866 cm-1 for Ca10K(VO4)7. The Lorentzian width parameters of these lines in the Voigt profiles were ~5 times greater than those of the Gaussian width parameters. The FWHM of the Voigt profiles were ~18-42 cm-1. The two strongest lines had widths of 21-25 cm-1. The vibrational band at 300-500 cm-1 was ~5-6 times weaker than that at 700-1000 cm-1 and was deconvoluted into four lines with widths of 25-40 cm-1. The large FWHM of the Raman lines indicated that the crystal structures were disordered. These crystals could be of interest for Raman conversion of pico- and femtosecond laser pulses because of the intense vibrations with large FWHM in the Raman spectra.

Continuous monitoring of high-rise buildings using seismic interferometry

NASA Astrophysics Data System (ADS)

Mordret, A.; Sun, H.; Prieto, G. A.; Toksoz, M. N.; Buyukozturk, O.

2016-12-01

The linear seismic response of a building is commonly extracted from ambient vibration measurements. Seismic deconvolution interferometry performed on ambient vibration measurements can also be used to estimate the dynamic characteristics of a building, such as the velocity of shear-waves travelling inside the building as well as a damping parameter depending on the intrinsic attenuation of the building and the soil-structure coupling. The continuous nature of the ambient vibrations allows us to measure these parameters repeatedly and to observe their temporal variations. We used 2 weeks of ambient vibration recorded by 36 accelerometers installed in the Green Building on the Massachusetts Institute of Technology campus (Cambridge, MA) to continuously monitor the shear-wave speed and the attenuation factor of the building. Due to the low strain of the ambient vibrations, the observed changes are totally reversible. The relative velocity changes between a reference deconvolution function and the current deconvolution functions are measured with two different methods: 1) the Moving Window Cross-Spectral technique and 2) the stretching technique. Both methods show similar results. We show that measuring the stretching coefficient for the deconvolution functions filtered around the fundamental mode frequency is equivalent to measuring the wandering of the fundamental frequency in the raw ambient vibration data. By comparing these results with local weather parameters, we show that the relative air humidity is the factor dominating the relative seismic velocity variations in the Green Building, as well as the wandering of the fundamental mode. The one-day periodic variations are affected by both the temperature and the humidity. The attenuation factor, measured as the exponential decay of the fundamental mode waveforms, shows a more complex behaviour with respect to the weather measurements.

Thermal infrared spectroscopy and modeling of experimentally shocked plagioclase feldspars

USGS Publications Warehouse

Johnson, J. R.; Horz, F.; Staid, M.I.

2003-01-01

Thermal infrared emission and reflectance spectra (250-1400 cm-1; ???7???40 ??m) of experimentally shocked albite- and anorthite-rich rocks (17-56 GPa) demonstrate that plagioclase feldspars exhibit characteristic degradations in spectral features with increasing pressure. New measurements of albite (Ab98) presented here display major spectral absorptions between 1000-1250 cm-1 (8-10 ??m) (due to Si-O antisymmetric stretch motions of the silica tetrahedra) and weaker absorptions between 350-700 cm-1 (14-29 ??m) (due to Si-O-Si octahedral bending vibrations). Many of these features persist to higher pressures compared to similar features in measurements of shocked anorthite, consistent with previous thermal infrared absorption studies of shocked feldspars. A transparency feature at 855 cm-1 (11.7 ??m) observed in powdered albite spectra also degrades with increasing pressure, similar to the 830 cm-1 (12.0 ??m) transparency feature in spectra of powders of shocked anorthite. Linear deconvolution models demonstrate that combinations of common mineral and glass spectra can replicate the spectra of shocked anorthite relatively well until shock pressures of 20-25 GPa, above which model errors increase substantially, coincident with the onset of diaplectic glass formation. Albite deconvolutions exhibit higher errors overall but do not change significantly with pressure, likely because certain clay minerals selected by the model exhibit absorption features similar to those in highly shocked albite. The implication for deconvolution of thermal infrared spectra of planetary surfaces (or laboratory spectra of samples) is that the use of highly shocked anorthite spectra in end-member libraries could be helpful in identifying highly shocked calcic plagioclase feldspars.

Post-discharge gas composition of a large-gap DBD in humid air by UV-Vis absorption spectroscopy

NASA Astrophysics Data System (ADS)

Moiseev, T.; Misra, N. N.; Patil, S.; Cullen, P. J.; Bourke, P.; Keener, K. M.; Mosnier, J. P.

2014-12-01

Large gap dielectric barrier discharges (DBD) provide non-thermal, non-equilibrium plasmas that can generate specific gas chemistry with enhanced bactericidal effects when working in humid air. The present study investigates the post-discharge gas composition of such plasmas operated in humid air using UV-Vis (200-800 nm) absorption spectroscopy. Absorbance spectra have been de-convoluted using direct deconvolution and iterative methods and results are correlated to the DBD electrical parameters. The high-voltage (56 and 70 kV rms) DBD plasma generated at 50 Hz frequency in a closed container over a 20 mm gap in air with relative humidity (RH) of 5-70% has been characterized by I-V and capacitive methods. The post-discharge gas composition at each RH is assessed by UV-Vis absorption spectroscopy for plasma exposure times of 15-120 s. The concentration of ozone and nitrogen oxides (O3, NO2, NO3, N2O4) increases with plasma exposure time but a strong decrease in [O3] levels is obtained with increase in RH. The decrease in [O3] and an abundance of nitrogen oxides is ascribed to high specific power densities in the closed container and to increasing RH levels. The absorbance residual following deconvolution shows a strong band at 230-270 nm consistent with the presence of pernitric acid (HNO4) and other HNOx (x = 1, 3) species. Humid air large gap DBD plasmas in closed containers generate along with O3, high levels of nitrogen oxides and HNOx (x = 1, 4) acids leading to increased bactericidal rates.

A deconvolution method for deriving the transit time spectrum for ultrasound propagation through cancellous bone replica models.

PubMed

Langton, Christian M; Wille, Marie-Luise; Flegg, Mark B

2014-04-01

The acceptance of broadband ultrasound attenuation for the assessment of osteoporosis suffers from a limited understanding of ultrasound wave propagation through cancellous bone. It has recently been proposed that the ultrasound wave propagation can be described by a concept of parallel sonic rays. This concept approximates the detected transmission signal to be the superposition of all sonic rays that travel directly from transmitting to receiving transducer. The transit time of each ray is defined by the proportion of bone and marrow propagated. An ultrasound transit time spectrum describes the proportion of sonic rays having a particular transit time, effectively describing lateral inhomogeneity of transit times over the surface of the receiving ultrasound transducer. The aim of this study was to provide a proof of concept that a transit time spectrum may be derived from digital deconvolution of input and output ultrasound signals. We have applied the active-set method deconvolution algorithm to determine the ultrasound transit time spectra in the three orthogonal directions of four cancellous bone replica samples and have compared experimental data with the prediction from the computer simulation. The agreement between experimental and predicted ultrasound transit time spectrum analyses derived from Bland-Altman analysis ranged from 92% to 99%, thereby supporting the concept of parallel sonic rays for ultrasound propagation in cancellous bone. In addition to further validation of the parallel sonic ray concept, this technique offers the opportunity to consider quantitative characterisation of the material and structural properties of cancellous bone, not previously available utilising ultrasound.

Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

PubMed Central

Sun, Kun; Jiang, Peiyong; Chan, K. C. Allen; Wong, John; Cheng, Yvonne K. Y.; Liang, Raymond H. S.; Chan, Wai-kong; Ma, Edmond S. K.; Chan, Stephen L.; Cheng, Suk Hang; Chan, Rebecca W. Y.; Tong, Yu K.; Ng, Simon S. M.; Wong, Raymond S. M.; Hui, David S. C.; Leung, Tse Ngong; Leung, Tak Y.; Lai, Paul B. S.; Chiu, Rossa W. K.; Lo, Yuk Ming Dennis

2015-01-01

Plasma consists of DNA released from multiple tissues within the body. Using genome-wide bisulfite sequencing of plasma DNA and deconvolution of the sequencing data with reference to methylation profiles of different tissues, we developed a general approach for studying the major tissue contributors to the circulating DNA pool. We tested this method in pregnant women, patients with hepatocellular carcinoma, and subjects following bone marrow and liver transplantation. In most subjects, white blood cells were the predominant contributors to the circulating DNA pool. The placental contributions in the plasma of pregnant women correlated with the proportional contributions as revealed by fetal-specific genetic markers. The graft-derived contributions to the plasma in the transplant recipients correlated with those determined using donor-specific genetic markers. Patients with hepatocellular carcinoma showed elevated plasma DNA contributions from the liver, which correlated with measurements made using tumor-associated copy number aberrations. In hepatocellular carcinoma patients and in pregnant women exhibiting copy number aberrations in plasma, comparison of methylation deconvolution results using genomic regions with different copy number status pinpointed the tissue type responsible for the aberrations. In a pregnant woman diagnosed as having follicular lymphoma during pregnancy, methylation deconvolution indicated a grossly elevated contribution from B cells into the plasma DNA pool and localized B cells as the origin of the copy number aberrations observed in plasma. This method may serve as a powerful tool for assessing a wide range of physiological and pathological conditions based on the identification of perturbed proportional contributions of different tissues into plasma. PMID:26392541

Cell subpopulation deconvolution reveals breast cancer heterogeneity based on DNA methylation signature.

PubMed

Wen, Yanhua; Wei, Yanjun; Zhang, Shumei; Li, Song; Liu, Hongbo; Wang, Fang; Zhao, Yue; Zhang, Dongwei; Zhang, Yan

2017-05-01

Tumour heterogeneity describes the coexistence of divergent tumour cell clones within tumours, which is often caused by underlying epigenetic changes. DNA methylation is commonly regarded as a significant regulator that differs across cells and tissues. In this study, we comprehensively reviewed research progress on estimating of tumour heterogeneity. Bioinformatics-based analysis of DNA methylation has revealed the evolutionary relationships between breast cancer cell lines and tissues. Further analysis of the DNA methylation profiles in 33 breast cancer-related cell lines identified cell line-specific methylation patterns. Next, we reviewed the computational methods in inferring clonal evolution of tumours from different perspectives and then proposed a deconvolution strategy for modelling cell subclonal populations dynamics in breast cancer tissues based on DNA methylation. Further analysis of simulated cancer tissues and real cell lines revealed that this approach exhibits satisfactory performance and relative stability in estimating the composition and proportions of cellular subpopulations. The application of this strategy to breast cancer individuals of the Cancer Genome Atlas's identified different cellular subpopulations with distinct molecular phenotypes. Moreover, the current and potential future applications of this deconvolution strategy to clinical breast cancer research are discussed, and emphasis was placed on the DNA methylation-based recognition of intra-tumour heterogeneity. The wide use of these methods for estimating heterogeneity to further clinical cohorts will improve our understanding of neoplastic progression and the design of therapeutic interventions for treating breast cancer and other malignancies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3’-Diaminobenzidine&Haematoxylin

PubMed Central

2013-01-01

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the ’brown component’ extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without undercutting the area for true positive objects but with extra false positive objects. The Sauvola and the Bernsen methods gives complementary results what will be exploited when the new method of virtual tissue slides segmentation be develop. Virtual Slides The virtual slides for this article can be found here: slide 1: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617947952577 and slide 2: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617948230017. PMID:23531405

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3'-Diaminobenzidine&Haematoxylin.

PubMed

Korzynska, Anna; Roszkowiak, Lukasz; Lopez, Carlos; Bosch, Ramon; Witkowski, Lukasz; Lejeune, Marylene

2013-03-25

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the 'brown component' extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without undercutting the area for true positive objects but with extra false positive objects. The Sauvola and the Bernsen methods gives complementary results what will be exploited when the new method of virtual tissue slides segmentation be develop. The virtual slides for this article can be found here: slide 1: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617947952577 and slide 2: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617948230017.

The Olfactory System Revealed: Non-Invasive Mapping by using Constrained Spherical Deconvolution Tractography in Healthy Humans

PubMed Central

Milardi, Demetrio; Cacciola, Alberto; Calamuneri, Alessandro; Ghilardi, Maria F.; Caminiti, Fabrizia; Cascio, Filippo; Andronaco, Veronica; Anastasi, Giuseppe; Mormina, Enricomaria; Arrigo, Alessandro; Bruschetta, Daniele; Quartarone, Angelo

2017-01-01

Although the olfactory sense has always been considered with less interest than the visual, auditive or somatic senses, it does plays a major role in our ordinary life, with important implication in dangerous situations or in social and emotional behaviors. Traditional Diffusion Tensor signal model and related tractography have been used in the past years to reconstruct the cranial nerves, including the olfactory nerve (ON). However, no supplementary information with regard to the pathways of the olfactory network have been provided. Here, by using the more advanced Constrained Spherical Deconvolution (CSD) diffusion model, we show for the first time in vivo and non-invasively that, in healthy humans, the olfactory system has a widely distributed anatomical network to several cortical regions as well as to many subcortical structures. Although the present study focuses on an healthy sample size, a similar approach could be applied in the near future to gain important insights with regard to the early involvement of olfaction in several neurodegenerative disorders. PMID:28443000

[Application of numerical convolution in in vivo/in vitro correlation research].

PubMed

Yue, Peng

2009-01-01

This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.

Assessment of sub-grid scale dispersion closure with regularized deconvolution method in a particle-laden turbulent jet

NASA Astrophysics Data System (ADS)

Wang, Qing; Zhao, Xinyu; Ihme, Matthias

2017-11-01

Particle-laden turbulent flows are important in numerous industrial applications, such as spray combustion engines, solar energy collectors etc. It is of interests to study this type of flows numerically, especially using large-eddy simulations (LES). However, capturing the turbulence-particle interaction in LES remains challenging due to the insufficient representation of the effect of sub-grid scale (SGS) dispersion. In the present work, a closure technique for the SGS dispersion using regularized deconvolution method (RDM) is assessed. RDM was proposed as the closure for the SGS dispersion in a counterflow spray that is studied numerically using finite difference method on a structured mesh. A presumed form of LES filter is used in the simulations. In the present study, this technique has been extended to finite volume method with an unstructured mesh, where no presumption on the filter form is required. The method is applied to a series of particle-laden turbulent jets. Parametric analyses of the model performance are conducted for flows with different Stokes numbers and Reynolds numbers. The results from LES will be compared against experiments and direct numerical simulations (DNS).

Luminescence studies of rare earth doped yttrium gadolinium mixed oxide phosphor

NASA Astrophysics Data System (ADS)

Som, S.; Choubey, A.; Sharma, S. K.

2012-09-01

This paper reports the photoluminescence and thermoluminescence properties of gamma ray induced rare earth doped yttrium gadolinium mixed oxide phosphor. The europium (Eu3+) was used as rare earth dopant. The phosphor was prepared by chemical co-precipitation method according to the formula (Y2-x-yGdx) O3: Euy3+ (x=0.5; y=0.05). The photoluminescence emission spectrum of the prepared phosphor shows intense peaks in the red region at 615 nm for 5D0→7F2 transitions and the photoluminescence excitation spectra show a broad band located around 220-270 nm for the emission wavelength fixed at 615 nm. The thermoluminescence studies were carried out after irradiating the phosphor by gamma rays in the dose range from 100 Gy to 1 KGy. In the thermoluminescence glow curves, one single peak was observed at about 300 °C of which the intensity increases linearly in the studied dose range of gamma rays. The glow peak was deconvoluted by GlowFit program and the kinetic parameters associated with the deconvoluted peaks were calculated. The kinetic parameters were also calculated by various glow curve shape and heating rate methods.

Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery

NASA Technical Reports Server (NTRS)

Smith, Jeffrey

2012-01-01

The Iterative Transform Phase Diversity algorithm is designed to solve the problem of recovering the wavefront in the exit pupil of an optical system and the object being imaged. This algorithm builds upon the robust convergence capability of Variable Sampling Mapping (VSM), in combination with the known success of various deconvolution algorithms. VSM is an alternative method for enforcing the amplitude constraints of a Misell-Gerchberg-Saxton (MGS) algorithm. When provided the object and additional optical parameters, VSM can accurately recover the exit pupil wavefront. By combining VSM and deconvolution, one is able to simultaneously recover the wavefront and the object.

Deconvolution Method on OSL Curves from ZrO2 Irradiated by Beta and UV Radiations

NASA Astrophysics Data System (ADS)

Rivera, T.; Kitis, G.; Azorín, J.; Furetta, C.

This paper reports the optically stimulated luminescent (OSL) response of ZrO2 to beta and ultraviolet radiations in order to investigate the potential use of this material as a radiation dosimeter. The experimentally obtained OSL decay curves were analyzed using the computerized curve de-convolution (CCD) method. It was found that the OSL curve structure, for the short (practical) illumination time used, consists of three first order components. The individual OSL dose response behavior of each component was found. The values of the time at the OSL peak maximum and the decay constant of each component were also estimated.

Pooling across cells to normalize single-cell RNA sequencing data with many zero counts.

PubMed

Lun, Aaron T L; Bach, Karsten; Marioni, John C

2016-04-27

Normalization of single-cell RNA sequencing data is necessary to eliminate cell-specific biases prior to downstream analyses. However, this is not straightforward for noisy single-cell data where many counts are zero. We present a novel approach where expression values are summed across pools of cells, and the summed values are used for normalization. Pool-based size factors are then deconvolved to yield cell-based factors. Our deconvolution approach outperforms existing methods for accurate normalization of cell-specific biases in simulated data. Similar behavior is observed in real data, where deconvolution improves the relevance of results of downstream analyses.

Correction Factor for Gaussian Deconvolution of Optically Thick Linewidths in Homogeneous Sources

NASA Technical Reports Server (NTRS)

Kastner, S. O.; Bhatia, A. K.

1999-01-01

Profiles of optically thick, non-Gaussian emission line profiles convoluted with Gaussian instrumental profiles are constructed, and are deconvoluted on the usual Gaussian basis to examine the departure from accuracy thereby caused in "measured" linewidths. It is found that "measured" linewidths underestimate the true linewidths of optically thick lines, by a factor which depends on the resolution factor r congruent to Doppler width/instrumental width and on the optical thickness tau(sub 0). An approximating expression is obtained for this factor, applicable in the range of at least 0 <= tau(sub 0) <= 10, which can provide estimates of the true linewidth and optical thickness.

Time-Domain Receiver Function Deconvolution using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Moreira, L. P.

2017-12-01

Receiver Functions (RF) are well know method for crust modelling using passive seismological signals. Many different techniques were developed to calculate the RF traces, applying the deconvolution calculation to radial and vertical seismogram components. A popular method used a spectral division of both components, which requires human intervention to apply the Water Level procedure to avoid instabilities from division by small numbers. One of most used method is an iterative procedure to estimate the RF peaks and applying the convolution with vertical component seismogram, comparing the result with the radial component. This method is suitable for automatic processing, however several RF traces are invalid due to peak estimation failure.In this work it is proposed a deconvolution algorithm using Genetic Algorithm (GA) to estimate the RF peaks. This method is entirely processed in the time domain, avoiding the time-to-frequency calculations (and vice-versa), and totally suitable for automatic processing. Estimated peaks can be used to generate RF traces in a seismogram format for visualization. The RF trace quality is similar for high magnitude events, although there are less failures for RF calculation of smaller events, increasing the overall performance for high number of events per station.

Ultrasonic inspection of studs (bolts) using dynamic predictive deconvolution and wave shaping.

PubMed

Suh, D M; Kim, W W; Chung, J G

1999-01-01

Bolt degradation has become a major issue in the nuclear industry since the 1980's. If small cracks in stud bolts are not detected early enough, they grow rapidly and cause catastrophic disasters. Their detection, despite its importance, is known to be a very difficult problem due to the complicated structures of the stud bolts. This paper presents a method of detecting and sizing a small crack in the root between two adjacent crests in threads. The key idea is from the fact that the mode-converted Rayleigh wave travels slowly down the face of the crack and turns from the intersection of the crack and the root of thread to the transducer. Thus, when a crack exists, a small delayed pulse due to the Rayleigh wave is detected between large regularly spaced pulses from the thread. The delay time is the same as the propagation delay time of the slow Rayleigh wave and is proportional to the site of the crack. To efficiently detect the slow Rayleigh wave, three methods based on digital signal processing are proposed: wave shaping, dynamic predictive deconvolution, and dynamic predictive deconvolution combined with wave shaping.

Retinal image restoration by means of blind deconvolution

NASA Astrophysics Data System (ADS)

Marrugo, Andrés G.; Šorel, Michal; Šroubek, Filip; Millán, María S.

2011-11-01

Retinal imaging plays a key role in the diagnosis and management of ophthalmologic disorders, such as diabetic retinopathy, glaucoma, and age-related macular degeneration. Because of the acquisition process, retinal images often suffer from blurring and uneven illumination. This problem may seriously affect disease diagnosis and progression assessment. Here we present a method for color retinal image restoration by means of multichannel blind deconvolution. The method is applied to a pair of retinal images acquired within a lapse of time, ranging from several minutes to months. It consists of a series of preprocessing steps to adjust the images so they comply with the considered degradation model, followed by the estimation of the point-spread function and, ultimately, image deconvolution. The preprocessing is mainly composed of image registration, uneven illumination compensation, and segmentation of areas with structural changes. In addition, we have developed a procedure for the detection and visualization of structural changes. This enables the identification of subtle developments in the retina not caused by variation in illumination or blur. The method was tested on synthetic and real images. Encouraging experimental results show that the method is capable of significant restoration of degraded retinal images.

Optimisation of chromatographic resolution using objective functions including both time and spectral information.

PubMed

Torres-Lapasió, J R; Pous-Torres, S; Ortiz-Bolsico, C; García-Alvarez-Coque, M C

2015-01-16

The optimisation of the resolution in high-performance liquid chromatography is traditionally performed attending only to the time information. However, even in the optimal conditions, some peak pairs may remain unresolved. Such incomplete resolution can be still accomplished by deconvolution, which can be carried out with more guarantees of success by including spectral information. In this work, two-way chromatographic objective functions (COFs) that incorporate both time and spectral information were tested, based on the peak purity (analyte peak fraction free of overlapping) and the multivariate selectivity (figure of merit derived from the net analyte signal) concepts. These COFs are sensitive to situations where the components that coelute in a mixture show some spectral differences. Therefore, they are useful to find out experimental conditions where the spectrochromatograms can be recovered by deconvolution. Two-way multivariate selectivity yielded the best performance and was applied to the separation using diode-array detection of a mixture of 25 phenolic compounds, which remained unresolved in the chromatographic order using linear and multi-linear gradients of acetonitrile-water. Peak deconvolution was carried out using the combination of orthogonal projection approach and alternating least squares. Copyright © 2014 Elsevier B.V. All rights reserved.

A feasibility study for the application of seismic interferometry by multidimensional deconvolution for lithospheric-scale imaging

NASA Astrophysics Data System (ADS)

Ruigrok, Elmer; van der Neut, Joost; Djikpesse, Hugues; Chen, Chin-Wu; Wapenaar, Kees

2010-05-01

Active-source surveys are widely used for the delineation of hydrocarbon accumulations. Most source and receiver configurations are designed to illuminate the first 5 km of the earth. For a deep understanding of the evolution of the crust, much larger depths need to be illuminated. The use of large-scale active surveys is feasible, but rather costly. As an alternative, we use passive acquisition configurations, aiming at detecting responses from distant earthquakes, in combination with seismic interferometry (SI). SI refers to the principle of generating new seismic responses by combining seismic observations at different receiver locations. We apply SI to the earthquake responses to obtain responses as if there was a source at each receiver position in the receiver array. These responses are subsequently migrated to obtain an image of the lithosphere. Conventionally, SI is applied by a crosscorrelation of responses. Recently, an alternative implementation was proposed as SI by multidimensional deconvolution (MDD) (Wapenaar et al. 2008). SI by MDD compensates both for the source-sampling and the source wavelet irregularities. Another advantage is that the MDD relation also holds for media with severe anelastic losses. A severe restriction though for the implementation of MDD was the need to estimate responses without free-surface interaction, from the earthquake responses. To mitigate this restriction, Groenestijn en Verschuur (2009) proposed to introduce the incident wavefield as an additional unknown in the inversion process. As an alternative solution, van der Neut et al. (2010) showed that the required wavefield separation may be implemented after a crosscorrelation step. These last two approaches facilitate the application of MDD for lithospheric-scale imaging. In this work, we study the feasibility for the implementation of MDD when considering teleseismic wavefields. We address specific problems for teleseismic wavefields, such as long and complicated source wavelets, source-side reverberations and illumination gaps. We exemplify the feasibility of SI by MDD on synthetic data, based on field data from the Laramie and the POLARIS-MIT array. van Groenestijn, G.J.A. & Verschuur, D.J., 2009. Estimation of primaries by sparse inversion from passive seismic data, Expanded abstracts, 1597-1601, SEG. van der Neut, J.R, Ruigrok, E.N., Draganov, D.S., & Wapenaar, K., 2010. Retrieving the earth's reflection response by multi-dimensional deconvolution of ambient seismic noise, Extended abstracts, submitted, EAGE. Wapenaar, K., van der Neut, J., & Ruigrok, E.N., 2008. Passive seismic interferometry by multidimensional deconvolution, Geophysics, 75, A51-A56.

Toward 10 meV electron energy-loss spectroscopy resolution for plasmonics.

PubMed

Bellido, Edson P; Rossouw, David; Botton, Gianluigi A

2014-06-01

Energy resolution is one of the most important parameters in electron energy-loss spectroscopy. This is especially true for measurement of surface plasmon resonances, where high-energy resolution is crucial for resolving individual resonance peaks, in particular close to the zero-loss peak. In this work, we improve the energy resolution of electron energy-loss spectra of surface plasmon resonances, acquired with a monochromated beam in a scanning transmission electron microscope, by the use of the Richardson-Lucy deconvolution algorithm. We test the performance of the algorithm in a simulated spectrum and then apply it to experimental energy-loss spectra of a lithographically patterned silver nanorod. By reduction of the point spread function of the spectrum, we are able to identify low-energy surface plasmon peaks in spectra, more localized features, and higher contrast in surface plasmon energy-filtered maps. Thanks to the combination of a monochromated beam and the Richardson-Lucy algorithm, we improve the effective resolution down to 30 meV, and evidence of success up to 10 meV resolution for losses below 1 eV. We also propose, implement, and test two methods to limit the number of iterations in the algorithm. The first method is based on noise measurement and analysis, while in the second we monitor the change of slope in the deconvolved spectrum.

Microscopy using source and detector arrays

NASA Astrophysics Data System (ADS)

Sheppard, Colin J. R.; Castello, Marco; Vicidomini, Giuseppe; Duocastella, Martí; Diaspro, Alberto

2016-03-01

There are basically two types of microscope, which we call conventional and scanning. The former type is a full-field imaging system. In the latter type, the object is illuminated with a probe beam, and a signal detected. We can generalize the probe to a patterned illumination. Similarly we can generalize the detection to a patterned detection. Combining these we get a range of different modalities: confocal microscopy, structured illumination (with full-field imaging), spinning disk (with multiple illumination points), and so on. The combination allows the spatial frequency bandwidth of the system to be doubled. In general we can record a four dimensional (4D) image of a 2D object (or a 6D image from a 3D object, using an acoustic tuneable lens). The optimum way to directly reconstruct the resulting image is by image scanning microscopy (ISM). But the 4D image is highly redundant, so deconvolution-based approaches are also relevant. ISM can be performed in fluorescence, bright field or interference microscopy. Several different implementations have been described, with associated advantages and disadvantages. In two-photon microscopy, the illumination and detection point spread functions are very different. This is also the case when using pupil filters or when there is a large Stokes shift.

Analysis of mercerization process based on the intensity change of deconvoluted resonances of (13)C CP/MAS NMR: Cellulose mercerized under cooling and non-cooling conditions.

PubMed

Miura, Kento; Nakano, Takato

2015-08-01

The area intensity change of C1, C4, and C6 in spectrum obtained by (13)C CP/MAS NMR and the mutual relationship between their changes were examined for cellulose samples treated with various concentrations of aqueous NaOH solutions under non-cooling and cooling conditions. The area intensity of C1-up and C6-down changed cooperatively with that of C4-down which corresponds to the crystallinity of samples: "-up" and "-down" are the up- and down- field component in a splitting peak of NMR spectrum, respectively. The intensity change of C1-up starts to decrease with decreasing in that of C4-down after that of C6-down is almost complete. These changes were more clearly observed for samples treated under cooling condition. It can be suggested that their characteristic change relates closely to the change in conformation of cellulose chains by induced decrystallization and the subsequent crystallization of cellulose II, and presumed that their changes at microscopic level relate to the macroscopic morphological changes such as contraction along the length of cellulose chains and recovery along the length. Copyright © 2015 Elsevier B.V. All rights reserved.

Dynamic contrast-enhanced CT of head and neck tumors: perfusion measurements using a distributed-parameter tracer kinetic model. Initial results and comparison with deconvolution-based analysis

NASA Astrophysics Data System (ADS)

Bisdas, Sotirios; Konstantinou, George N.; Sherng Lee, Puor; Thng, Choon Hua; Wagenblast, Jens; Baghi, Mehran; San Koh, Tong

2007-10-01

The objective of this work was to evaluate the feasibility of a two-compartment distributed-parameter (DP) tracer kinetic model to generate functional images of several physiologic parameters from dynamic contrast-enhanced CT data obtained of patients with extracranial head and neck tumors and to compare the DP functional images to those obtained by deconvolution-based DCE-CT data analysis. We performed post-processing of DCE-CT studies, obtained from 15 patients with benign and malignant head and neck cancer. We introduced a DP model of the impulse residue function for a capillary-tissue exchange unit, which accounts for the processes of convective transport and capillary-tissue exchange. The calculated parametric maps represented blood flow (F), intravascular blood volume (v1), extravascular extracellular blood volume (v2), vascular transit time (t1), permeability-surface area product (PS), transfer ratios k12 and k21, and the fraction of extracted tracer (E). Based on the same regions of interest (ROI) analysis, we calculated the tumor blood flow (BF), blood volume (BV) and mean transit time (MTT) by using a modified deconvolution-based analysis taking into account the extravasation of the contrast agent for PS imaging. We compared the corresponding values by using Bland-Altman plot analysis. We outlined 73 ROIs including tumor sites, lymph nodes and normal tissue. The Bland-Altman plot analysis revealed that the two methods showed an accepted degree of agreement for blood flow, and, thus, can be used interchangeably for measuring this parameter. Slightly worse agreement was observed between v1 in the DP model and BV but even here the two tracer kinetic analyses can be used interchangeably. Under consideration of whether both techniques may be used interchangeably was the case of t1 and MTT, as well as for measurements of the PS values. The application of the proposed DP model is feasible in the clinical routine and it can be used interchangeably for measuring blood flow and vascular volume with the commercially available reference standard of the deconvolution-based approach. The lack of substantial agreement between the measurements of vascular transit time and permeability-surface area product may be attributed to the different tracer kinetic principles employed by both models and the detailed capillary tissue exchange physiological modeling of the DP technique.

Soot Oxidation in Hydrocarbon/Air Diffusion Flames at Atmospheric Pressure. Appendix K

NASA Technical Reports Server (NTRS)

Xu, F.; El-Leathy, A. M.; Faeth, G. M.; Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)

2001-01-01

Soot oxidation was studied experimentally in laminar hydrocarbon/air diffusion flames at atmospheric pressure. Measurements were carried out along the axes of round jets burning in coflowing air considering acetylene, ethylene, propylene and propane as fuels. Measurements were limited to the initial stages of soot oxidation (carbon consumption less than 70%) where soot oxidation mainly occurs at the surface of primary soot particles. The following properties were measured as a function of distance above the burner exit: soot concentrations by deconvoluted laser extinction, soot temperatures by deconvoluted multiline emission, soot structure by thermophoretic sampling and analysis using Transmission Electron Microscopy (TEM), concentrations of stable major gas species (N2, H2O, H2, O2, CO, CO2, CH4, C2H2,C2H4, C2H6, C3H6, and C3H8) by sampling and gas chromatography, concentrations of some radical species (H, OH, O) by the deconvoluted Li/LiOH atomic absorption technique and flow velocities by laser velocimetry. It was found that soot surface oxidation rates are not particularly affected by fuel type for laminar diffusion flames and are described reasonably well by the OH surface oxidation mechanism with a collision efficiency of 0.10, (standard deviation of 0.07) with no significant effect of fuel type in this behavior; these findings are in good agreement with the classical laminar premixed flame measurements of Neoh et al. Finally, direct rates of surface oxidation by O2 were small compared to OH oxidation for present conditions, based on estimated O2 oxidation rates due to Nagle and Strickland-Constable (1962), because soot oxidation was completed near the flame sheet where O2 concentrations were less than 1.2% by volume.

Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization

PubMed Central

Canales-Rodríguez, Erick J.; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M.; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond

2015-01-01

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024

Linear MALDI-ToF simultaneous spectrum deconvolution and baseline removal.

PubMed

Picaud, Vincent; Giovannelli, Jean-Francois; Truntzer, Caroline; Charrier, Jean-Philippe; Giremus, Audrey; Grangeat, Pierre; Mercier, Catherine

2018-04-05

Thanks to a reasonable cost and simple sample preparation procedure, linear MALDI-ToF spectrometry is a growing technology for clinical microbiology. With appropriate spectrum databases, this technology can be used for early identification of pathogens in body fluids. However, due to the low resolution of linear MALDI-ToF instruments, robust and accurate peak picking remains a challenging task. In this context we propose a new peak extraction algorithm from raw spectrum. With this method the spectrum baseline and spectrum peaks are processed jointly. The approach relies on an additive model constituted by a smooth baseline part plus a sparse peak list convolved with a known peak shape. The model is then fitted under a Gaussian noise model. The proposed method is well suited to process low resolution spectra with important baseline and unresolved peaks. We developed a new peak deconvolution procedure. The paper describes the method derivation and discusses some of its interpretations. The algorithm is then described in a pseudo-code form where the required optimization procedure is detailed. For synthetic data the method is compared to a more conventional approach. The new method reduces artifacts caused by the usual two-steps procedure, baseline removal then peak extraction. Finally some results on real linear MALDI-ToF spectra are provided. We introduced a new method for peak picking, where peak deconvolution and baseline computation are performed jointly. On simulated data we showed that this global approach performs better than a classical one where baseline and peaks are processed sequentially. A dedicated experiment has been conducted on real spectra. In this study a collection of spectra of spiked proteins were acquired and then analyzed. Better performances of the proposed method, in term of accuracy and reproductibility, have been observed and validated by an extended statistical analysis.

Deconvoluting Post-Transplant Immunity: Cell Subset-Specific Mapping Reveals Pathways for Activation and Expansion of Memory T, Monocytes and B Cells

PubMed Central

Grigoryev, Yevgeniy A.; Kurian, Sunil M.; Avnur, Zafi; Borie, Dominic; Deng, Jun; Campbell, Daniel; Sung, Joanna; Nikolcheva, Tania; Quinn, Anthony; Schulman, Howard; Peng, Stanford L.; Schaffer, Randolph; Fisher, Jonathan; Mondala, Tony; Head, Steven; Flechner, Stuart M.; Kantor, Aaron B.; Marsh, Christopher; Salomon, Daniel R.

2010-01-01

A major challenge for the field of transplantation is the lack of understanding of genomic and molecular drivers of early post-transplant immunity. The early immune response creates a complex milieu that determines the course of ensuing immune events and the ultimate outcome of the transplant. The objective of the current study was to mechanistically deconvolute the early immune response by purifying and profiling the constituent cell subsets of the peripheral blood. We employed genome-wide profiling of whole blood and purified CD4, CD8, B cells and monocytes in tandem with high-throughput laser-scanning cytometry in 10 kidney transplants sampled serially pre-transplant, 1, 2, 4, 8 and 12 weeks. Cytometry confirmed early cell subset depletion by antibody induction and immunosuppression. Multiple markers revealed the activation and proliferative expansion of CD45RO+CD62L− effector memory CD4/CD8 T cells as well as progressive activation of monocytes and B cells. Next, we mechanistically deconvoluted early post-transplant immunity by serial monitoring of whole blood using DNA microarrays. Parallel analysis of cell subset-specific gene expression revealed a unique spectrum of time-dependent changes and functional pathways. Gene expression profiling results were validated with 157 different probesets matching all 65 antigens detected by cytometry. Thus, serial blood cell monitoring reflects the profound changes in blood cell composition and immune activation early post-transplant. Each cell subset reveals distinct pathways and functional programs. These changes illuminate a complex, early phase of immunity and inflammation that includes activation and proliferative expansion of the memory effector and regulatory cells that may determine the phenotype and outcome of the kidney transplant. PMID:20976225

Deconvoluting post-transplant immunity: cell subset-specific mapping reveals pathways for activation and expansion of memory T, monocytes and B cells.

PubMed

Grigoryev, Yevgeniy A; Kurian, Sunil M; Avnur, Zafi; Borie, Dominic; Deng, Jun; Campbell, Daniel; Sung, Joanna; Nikolcheva, Tania; Quinn, Anthony; Schulman, Howard; Peng, Stanford L; Schaffer, Randolph; Fisher, Jonathan; Mondala, Tony; Head, Steven; Flechner, Stuart M; Kantor, Aaron B; Marsh, Christopher; Salomon, Daniel R

2010-10-14

A major challenge for the field of transplantation is the lack of understanding of genomic and molecular drivers of early post-transplant immunity. The early immune response creates a complex milieu that determines the course of ensuing immune events and the ultimate outcome of the transplant. The objective of the current study was to mechanistically deconvolute the early immune response by purifying and profiling the constituent cell subsets of the peripheral blood. We employed genome-wide profiling of whole blood and purified CD4, CD8, B cells and monocytes in tandem with high-throughput laser-scanning cytometry in 10 kidney transplants sampled serially pre-transplant, 1, 2, 4, 8 and 12 weeks. Cytometry confirmed early cell subset depletion by antibody induction and immunosuppression. Multiple markers revealed the activation and proliferative expansion of CD45RO(+)CD62L(-) effector memory CD4/CD8 T cells as well as progressive activation of monocytes and B cells. Next, we mechanistically deconvoluted early post-transplant immunity by serial monitoring of whole blood using DNA microarrays. Parallel analysis of cell subset-specific gene expression revealed a unique spectrum of time-dependent changes and functional pathways. Gene expression profiling results were validated with 157 different probesets matching all 65 antigens detected by cytometry. Thus, serial blood cell monitoring reflects the profound changes in blood cell composition and immune activation early post-transplant. Each cell subset reveals distinct pathways and functional programs. These changes illuminate a complex, early phase of immunity and inflammation that includes activation and proliferative expansion of the memory effector and regulatory cells that may determine the phenotype and outcome of the kidney transplant.

Soot Oxidation in Laminar Hydrocarbon/Air Diffusion Flames at Atmospheric Pressure. Appendix D

NASA Technical Reports Server (NTRS)

Xu, F.; El-Leathy, A. M.; Faeth, G. M.

2000-01-01

Soot oxidation was studied experimentally in laminar hydrocarbon/air diffusion flames at atmospheric pressure. Measurements were carried out along the axes of round jets burning in coflowing air considering acetylene, ethylene, proplyene and propane as fuels. Measurements were limited to the initial stages of soot oxidation (carbon consumption less than 70%) where soot oxidation mainly occurs at the surface of primary soot particles. The following properties were measured as a function of distance above the burner exit: soot concentrations by deconvoluted laser extinction, soot temperatures by deconvoluted multiline emission, soot structure by thermophoretic sampling and analysis using Transmission Electron Microscopy (TEM), concentrations of stable major gas species (N2, H2O, H2, 02, CO, CO2, CH4, C2H2, C2H4, C2H6, C3H6, and C3H8) by sampling and gas chromatography, concentrations of some radical species (H, OH, O) by the deconvoluted Li/LiOH atomic absorption technique and flow velocities by laser velocimetry. It was found that soot surface oxidation rates are not particularly affected by fuel type for laminar diffusion flames and are described reasonably well by the OH surface oxidation mechanism with a collision efficiency of 0.10, (standard deviation of 0.07) with no significant effect of fuel type in this behavior; these findings are in good agreement with the classical laminar premixed flame measurements of Neoh et al. Finally, direct rates of surface oxidation by O2 were small compared to OH oxidation for present conditions, based on estimated O2 oxidation rates due to Nagle and Strickland-Constable, because soot oxidation was completed near the flame sheet where O2 concentrations were less than 1.2% by volume.

Adaptive optics images restoration based on frame selection and multi-framd blind deconvolution

NASA Astrophysics Data System (ADS)

Tian, Y.; Rao, C. H.; Wei, K.

2008-10-01

The adaptive optics can only partially compensate the image blurred by atmospheric turbulent due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frame blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are picked out by frame selection technique is deconvolved. There is no priori knowledge except the positive constraint. The method has been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system in Yunnan Observatory. The results showed that the method can effectively improve the images partially corrected by adaptive optics.

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media

NASA Astrophysics Data System (ADS)

Edrei, Eitan; Scarcelli, Giuliano

2016-09-01

High-resolution imaging through turbid media is a fundamental challenge of optical sciences that has attracted a lot of attention in recent years for its wide range of potential applications. Here, we demonstrate that the resolution of imaging systems looking behind a highly scattering medium can be improved below the diffraction-limit. To achieve this, we demonstrate a novel microscopy technique enabled by the optical memory effect that uses a deconvolution image processing and thus it does not require iterative focusing, scanning or phase retrieval procedures. We show that this newly established ability of direct imaging through turbid media provides fundamental and practical advantages such as three-dimensional refocusing and unambiguous object reconstruction.

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media.

PubMed

Edrei, Eitan; Scarcelli, Giuliano

2016-09-16

High-resolution imaging through turbid media is a fundamental challenge of optical sciences that has attracted a lot of attention in recent years for its wide range of potential applications. Here, we demonstrate that the resolution of imaging systems looking behind a highly scattering medium can be improved below the diffraction-limit. To achieve this, we demonstrate a novel microscopy technique enabled by the optical memory effect that uses a deconvolution image processing and thus it does not require iterative focusing, scanning or phase retrieval procedures. We show that this newly established ability of direct imaging through turbid media provides fundamental and practical advantages such as three-dimensional refocusing and unambiguous object reconstruction.

Deconvolution of acoustic emissions for source localization using time reverse modeling

NASA Astrophysics Data System (ADS)

Kocur, Georg Karl

2017-01-01

Impact experiments on small-scale slabs made of concrete and aluminum were carried out. Wave motion radiated from the epicenter of the impact was recorded as voltage signals by resonant piezoelectric transducers. Numerical simulations of the elastic wave propagation are performed to simulate the physical experiments. The Hertz theory of contact is applied to estimate the force impulse, which is subsequently used for the numerical simulation. Displacements at the transducer positions are calculated numerically. A deconvolution function is obtained by comparing the physical (voltage signal) and the numerical (calculated displacement) experiments. Acoustic emission signals due to pencil-lead breaks are recorded, deconvolved and applied for localization using time reverse modeling.

Drug Delivery and Transport into the Central Circulation: An Example of Zero-Order In vivo Absorption of Rotigotine from a Transdermal Patch Formulation.

PubMed

Cawello, Willi; Braun, Marina; Andreas, Jens-Otto

2018-01-13

Pharmacokinetic studies using deconvolution methods and non-compartmental analysis to model clinical absorption of drugs are not well represented in the literature. The purpose of this research was (1) to define the system of equations for description of rotigotine (a dopamine receptor agonist delivered via a transdermal patch) absorption based on a pharmacokinetic model and (2) to describe the kinetics of rotigotine disposition after single and multiple dosing. The kinetics of drug disposition was evaluated based on rotigotine plasma concentration data from three phase 1 trials. In two trials, rotigotine was administered via a single patch over 24 h in healthy subjects. In a third trial, rotigotine was administered once daily over 1 month in subjects with early-stage Parkinson's disease (PD). A pharmacokinetic model utilizing deconvolution methods was developed to describe the relationship between drug release from the patch and plasma concentrations. Plasma-concentration over time profiles were modeled based on a one-compartment model with a time lag, a zero-order input (describing a constant absorption via skin into central circulation) and first-order elimination. Corresponding mathematical models for single- and multiple-dose administration were developed. After single-dose administration of rotigotine patches (using 2, 4 or 8 mg/day) in healthy subjects, a constant in vivo absorption was present after a minor time lag (2-3 h). On days 27 and 30 of the multiple-dose study in patients with PD, absorption was constant during patch-on periods and resembled zero-order kinetics. Deconvolution based on rotigotine pharmacokinetic profiles after single- or multiple-dose administration of the once-daily patch demonstrated that in vivo absorption of rotigotine showed constant input through the skin into the central circulation (resembling zero-order kinetics). Continuous absorption through the skin is a basis for stable drug exposure.

Quantification of β-cell insulin secretory function using a graded glucose infusion with C-peptide deconvolution in dysmetabolic, and diabetic cynomolgus monkeys.

PubMed

Wang, Xiaoli; Hansen, Barbara C; Shi, Da; Fang, Yupeng; Du, Fenglai; Wang, Bingdi; Chen, Yaxiong Michael; Gregoire, Francine M; Wang, Yi-Xin Jim

2013-07-25

Quantitation of β-cell function is critical in better understanding of the dynamic interactions of insulin secretion, clearance and action at different phases in the progression of diabetes. The present study aimed to quantify β-cell secretory function independently of insulin sensitivity in the context of differential metabolic clearance rates of insulin (MCRI) in nonhuman primates (NHPs). Insulin secretion rate (ISR) was derived from deconvolution of serial C-peptide concentrations measured during a 5 stage graded glucose infusion (GGI) in 12 nondiabetic (N), 8 prediabetic or dysmetabolic (DYS) and 4 overtly diabetic (DM) cynomolgus monkeys. The characterization of the monkeys was based on the fasting glucose and insulin concentrations, glucose clearance rate measured by intravenous glucose tolerance test, and insulin resistance indices measured in separate experiments. The molar ratio of C-peptide/insulin (C/I) was used as a surrogate index of hepatic MCRI. Compared to the N monkeys, the DYS with normal glycemia and hyperinsulinemia had significantly higher basal and GGI-induced elevation of insulin and C-peptide concentrations and lower C/I, however, each unit of glucose-stimulated ISR increment was not significantly different from that in the N monkeys. In contrast, the DM monkeys with β-cell failure and hyperglycemia had a depressed GGI-stimulated ISR response and elevated C/I. The present data demonstrated that in addition to β-cell hypersecretion of insulin, reduced hepatic MCRI may also contribute to the development of hyperinsulinemia in the DYS monkeys. On the other hand, hyperinsulinemia may cause the saturation of hepatic insulin extraction capacity, which in turn reduced MCRI in the DYS monkeys. The differential contribution of ISR and MCRI in causing hyperinsulinemia provides a new insight into the trajectory of β-cell dysfunction in the development of diabetes. The present study was the first to use the GGI and C-peptide deconvolution method to quantify the β-cell function in NHPs.

Mathematical enhancement of data from scientific measuring instruments

NASA Technical Reports Server (NTRS)

Ioup, J. W.

1982-01-01

The accuracy of any physical measurement is limited by the instruments performing it. The proposed activities of this grant are related to the study of and application of mathematical techniques of deconvolution. Two techniques are being investigated: an iterative method and a function continuation Fourier method. This final status report describes the work performed during the period July 1 to December 31, 1982.

A feasibility study for long-path multiple detection using a neural network

NASA Technical Reports Server (NTRS)

Feuerbacher, G. A.; Moebes, T. A.

1994-01-01

Least-squares inverse filters have found widespread use in the deconvolution of seismograms and the removal of multiples. The use of least-squares prediction filters with prediction distances greater than unity leads to the method of predictive deconvolution which can be used for the removal of long path multiples. The predictive technique allows one to control the length of the desired output wavelet by control of the predictive distance, and hence to specify the desired degree of resolution. Events which are periodic within given repetition ranges can be attenuated selectively. The method is thus effective in the suppression of rather complex reverberation patterns. A back propagation(BP) neural network is constructed to perform the detection of first arrivals of the multiples and therefore aid in the more accurate determination of the predictive distance of the multiples. The neural detector is applied to synthetic reflection coefficients and synthetic seismic traces. The processing results show that the neural detector is accurate and should lead to an automated fast method for determining predictive distances across vast amounts of data such as seismic field records. The neural network system used in this study was the NASA Software Technology Branch's NETS system.

Multichannel myopic deconvolution in underwater acoustic channels via low-rank recovery

PubMed Central

Tian, Ning; Byun, Sung-Hoon; Sabra, Karim; Romberg, Justin

2017-01-01

This paper presents a technique for solving the multichannel blind deconvolution problem. The authors observe the convolution of a single (unknown) source with K different (unknown) channel responses; from these channel outputs, the authors want to estimate both the source and the channel responses. The authors show how this classical signal processing problem can be viewed as solving a system of bilinear equations, and in turn can be recast as recovering a rank-1 matrix from a set of linear observations. Results of prior studies in the area of low-rank matrix recovery have identified effective convex relaxations for problems of this type and efficient, scalable heuristic solvers that enable these techniques to work with thousands of unknown variables. The authors show how a priori information about the channels can be used to build a linear model for the channels, which in turn makes solving these systems of equations well-posed. This study demonstrates the robustness of this methodology to measurement noises and parametrization errors of the channel impulse responses with several stylized and shallow water acoustic channel simulations. The performance of this methodology is also verified experimentally using shipping noise recorded on short bottom-mounted vertical line arrays. PMID:28599565

Monaural Sound Localization Based on Reflective Structure and Homomorphic Deconvolution

PubMed Central

Park, Yeonseok; Choi, Anthony

2017-01-01

The asymmetric structure around the receiver provides a particular time delay for the specific incoming propagation. This paper designs a monaural sound localization system based on the reflective structure around the microphone. The reflective plates are placed to present the direction-wise time delay, which is naturally processed by convolutional operation with a sound source. The received signal is separated for estimating the dominant time delay by using homomorphic deconvolution, which utilizes the real cepstrum and inverse cepstrum sequentially to derive the propagation response’s autocorrelation. Once the localization system accurately estimates the information, the time delay model computes the corresponding reflection for localization. Because of the structure limitation, two stages of the localization process perform the estimation procedure as range and angle. The software toolchain from propagation physics and algorithm simulation realizes the optimal 3D-printed structure. The acoustic experiments in the anechoic chamber denote that 79.0% of the study range data from the isotropic signal is properly detected by the response value, and 87.5% of the specific direction data from the study range signal is properly estimated by the response time. The product of both rates shows the overall hit rate to be 69.1%. PMID:28946625

Landcover Based Optimal Deconvolution of PALS L-band Microwave Brightness Temperature

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Crosson, William L.; Laymon, Charles A.; Njoku, Eni G.

2004-01-01

An optimal de-convolution (ODC) technique has been developed to estimate microwave brightness temperatures of agricultural fields using microwave radiometer observations. The technique is applied to airborne measurements taken by the Passive and Active L and S band (PALS) sensor in Iowa during Soil Moisture Experiments in 2002 (SMEX02). Agricultural fields in the study area were predominantly soybeans and corn. The brightness temperatures of corn and soybeans were observed to be significantly different because of large differences in vegetation biomass. PALS observations have significant over-sampling; observations were made about 100 m apart and the sensor footprint extends to about 400 m. Conventionally, observations of this type are averaged to produce smooth spatial data fields of brightness temperatures. However, the conventional approach is in contrast to reality in which the brightness temperatures are in fact strongly dependent on landcover, which is characterized by sharp boundaries. In this study, we mathematically de-convolve the observations into brightness temperature at the field scale (500-800m) using the sensor antenna response function. The result is more accurate spatial representation of field-scale brightness temperatures, which may in turn lead to more accurate soil moisture retrieval.

Continuous wavelet transform and Euler deconvolution method and their application to magnetic field data of Jharia coalfield, India

NASA Astrophysics Data System (ADS)

Singh, Arvind; Singh, Upendra Kumar

2017-02-01

This paper deals with the application of continuous wavelet transform (CWT) and Euler deconvolution methods to estimate the source depth using magnetic anomalies. These methods are utilized mainly to focus on the fundamental issue of mapping the major coal seam and locating tectonic lineaments. The main aim of the study is to locate and characterize the source of the magnetic field by transferring the data into an auxiliary space by CWT. The method has been tested on several synthetic source anomalies and finally applied to magnetic field data from Jharia coalfield, India. Using magnetic field data, the mean depth of causative sources points out the different lithospheric depth over the study region. Also, it is inferred that there are two faults, namely the northern boundary fault and the southern boundary fault, which have an orientation in the northeastern and southeastern direction respectively. Moreover, the central part of the region is more faulted and folded than the other parts and has sediment thickness of about 2.4 km. The methods give mean depth of the causative sources without any a priori information, which can be used as an initial model in any inversion algorithm.

Charge reconstruction in large-area photomultipliers

NASA Astrophysics Data System (ADS)

Grassi, M.; Montuschi, M.; Baldoncini, M.; Mantovani, F.; Ricci, B.; Andronico, G.; Antonelli, V.; Bellato, M.; Bernieri, E.; Brigatti, A.; Brugnera, R.; Budano, A.; Buscemi, M.; Bussino, S.; Caruso, R.; Chiesa, D.; Corti, D.; Dal Corso, F.; Ding, X. F.; Dusini, S.; Fabbri, A.; Fiorentini, G.; Ford, R.; Formozov, A.; Galet, G.; Garfagnini, A.; Giammarchi, M.; Giaz, A.; Insolia, A.; Isocrate, R.; Lippi, I.; Longhitano, F.; Lo Presti, D.; Lombardi, P.; Marini, F.; Mari, S. M.; Martellini, C.; Meroni, E.; Mezzetto, M.; Miramonti, L.; Monforte, S.; Nastasi, M.; Ortica, F.; Paoloni, A.; Parmeggiano, S.; Pedretti, D.; Pelliccia, N.; Pompilio, R.; Previtali, E.; Ranucci, G.; Re, A. C.; Romani, A.; Saggese, P.; Salamanna, G.; Sawy, F. H.; Settanta, G.; Sisti, M.; Sirignano, C.; Spinetti, M.; Stanco, L.; Strati, V.; Verde, G.; Votano, L.

2018-02-01

Large-area PhotoMultiplier Tubes (PMT) allow to efficiently instrument Liquid Scintillator (LS) neutrino detectors, where large target masses are pivotal to compensate for neutrinos' extremely elusive nature. Depending on the detector light yield, several scintillation photons stemming from the same neutrino interaction are likely to hit a single PMT in a few tens/hundreds of nanoseconds, resulting in several photoelectrons (PEs) to pile-up at the PMT anode. In such scenario, the signal generated by each PE is entangled to the others, and an accurate PMT charge reconstruction becomes challenging. This manuscript describes an experimental method able to address the PMT charge reconstruction in the case of large PE pile-up, providing an unbiased charge estimator at the permille level up to 15 detected PEs. The method is based on a signal filtering technique (Wiener filter) which suppresses the noise due to both PMT and readout electronics, and on a Fourier-based deconvolution able to minimize the influence of signal distortions—such as an overshoot. The analysis of simulated PMT waveforms shows that the slope of a linear regression modeling the relation between reconstructed and true charge values improves from 0.769 ± 0.001 (without deconvolution) to 0.989 ± 0.001 (with deconvolution), where unitary slope implies perfect reconstruction. A C++ implementation of the charge reconstruction algorithm is available online at [1].

Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics.

PubMed

Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

2017-04-06

An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

Facilitating high resolution mass spectrometry data processing for screening of environmental water samples: An evaluation of two deconvolution tools.

PubMed

Bade, Richard; Causanilles, Ana; Emke, Erik; Bijlsma, Lubertus; Sancho, Juan V; Hernandez, Felix; de Voogt, Pim

2016-11-01

A screening approach was applied to influent and effluent wastewater samples. After injection in a LC-LTQ-Orbitrap, data analysis was performed using two deconvolution tools, MsXelerator (modules MPeaks and MS Compare) and Sieve 2.1. The outputs were searched incorporating an in-house database of >200 pharmaceuticals and illicit drugs or ChemSpider. This hidden target screening approach led to the detection of numerous compounds including the illicit drug cocaine and its metabolite benzoylecgonine and the pharmaceuticals carbamazepine, gemfibrozil and losartan. The compounds found using both approaches were combined, and isotopic pattern and retention time prediction were used to filter out false positives. The remaining potential positives were reanalysed in MS/MS mode and their product ions were compared with literature and/or mass spectral libraries. The inclusion of the chemical database ChemSpider led to the tentative identification of several metabolites, including paraxanthine, theobromine, theophylline and carboxylosartan, as well as the pharmaceutical phenazone. The first three of these compounds are isomers and they were subsequently distinguished based on their product ions and predicted retention times. This work has shown that the use deconvolution tools facilitates non-target screening and enables the identification of a higher number of compounds. Copyright © 2016 Elsevier B.V. All rights reserved.

Pre-processing liquid chromatography/high-resolution mass spectrometry data: extracting pure mass spectra by deconvolution from the invariance of isotopic distribution.

PubMed

Krishnan, Shaji; Verheij, Elwin E R; Bas, Richard C; Hendriks, Margriet W B; Hankemeier, Thomas; Thissen, Uwe; Coulier, Leon

2013-05-15

Mass spectra obtained by deconvolution of liquid chromatography/high-resolution mass spectrometry (LC/HRMS) data can be impaired by non-informative mass-over-charge (m/z) channels. This impairment of mass spectra can have significant negative influence on further post-processing, like quantification and identification. A metric derived from the knowledge of errors in isotopic distribution patterns, and quality of the signal within a pre-defined mass chromatogram block, has been developed to pre-select all informative m/z channels. This procedure results in the clean-up of deconvoluted mass spectra by maintaining the intensity counts from m/z channels that originate from a specific compound/molecular ion, for example, molecular ion, adducts, (13) C-isotopes, multiply charged ions and removing all m/z channels that are not related to the specific peak. The methodology has been successfully demonstrated for two sets of high-resolution LC/MS data. The approach described is therefore thought to be a useful tool in the automatic processing of LC/HRMS data. It clearly shows the advantages compared to other approaches like peak picking and de-isotoping in the sense that all information is retained while non-informative data is removed automatically. Copyright © 2013 John Wiley & Sons, Ltd.

Plenoptic Image Motion Deblurring.

PubMed

Chandramouli, Paramanand; Jin, Meiguang; Perrone, Daniele; Favaro, Paolo

2018-04-01

We propose a method to remove motion blur in a single light field captured with a moving plenoptic camera. Since motion is unknown, we resort to a blind deconvolution formulation, where one aims to identify both the blur point spread function and the latent sharp image. Even in the absence of motion, light field images captured by a plenoptic camera are affected by a non-trivial combination of both aliasing and defocus, which depends on the 3D geometry of the scene. Therefore, motion deblurring algorithms designed for standard cameras are not directly applicable. Moreover, many state of the art blind deconvolution algorithms are based on iterative schemes, where blurry images are synthesized through the imaging model. However, current imaging models for plenoptic images are impractical due to their high dimensionality. We observe that plenoptic cameras introduce periodic patterns that can be exploited to obtain highly parallelizable numerical schemes to synthesize images. These schemes allow extremely efficient GPU implementations that enable the use of iterative methods. We can then cast blind deconvolution of a blurry light field image as a regularized energy minimization to recover a sharp high-resolution scene texture and the camera motion. Furthermore, the proposed formulation can handle non-uniform motion blur due to camera shake as demonstrated on both synthetic and real light field data.

Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI.

PubMed

Kratochvíla, Jiří; Jiřík, Radovan; Bartoš, Michal; Standara, Michal; Starčuk, Zenon; Taxt, Torfinn

2016-03-01

One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup. © 2015 Wiley Periodicals, Inc.

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics

PubMed Central

Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

2017-01-01

An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods. PMID:28383503

An integrated analysis-synthesis array system for spatial sound fields.

PubMed

Bai, Mingsian R; Hua, Yi-Hsin; Kuo, Chia-Hao; Hsieh, Yu-Hao

2015-03-01

An integrated recording and reproduction array system for spatial audio is presented within a generic framework akin to the analysis-synthesis filterbanks in discrete time signal processing. In the analysis stage, a microphone array "encodes" the sound field by using the plane-wave decomposition. Direction of arrival of plane-wave components that comprise the sound field of interest are estimated by multiple signal classification. Next, the source signals are extracted by using a deconvolution procedure. In the synthesis stage, a loudspeaker array "decodes" the sound field by reconstructing the plane-wave components obtained in the analysis stage. This synthesis stage is carried out by pressure matching in the interior domain of the loudspeaker array. The deconvolution problem is solved by truncated singular value decomposition or convex optimization algorithms. For high-frequency reproduction that suffers from the spatial aliasing problem, vector panning is utilized. Listening tests are undertaken to evaluate the deconvolution method, vector panning, and a hybrid approach that combines both methods to cover frequency ranges below and above the spatial aliasing frequency. Localization and timbral attributes are considered in the subjective evaluation. The results show that the hybrid approach performs the best in overall preference. In addition, there is a trade-off between reproduction performance and the external radiation.

Investigation of the lithosphere of the Texas Gulf Coast using phase-specific Ps receiver functions produced by wavefield iterative deconvolution

NASA Astrophysics Data System (ADS)

Gurrola, H.; Berdine, A.; Pulliam, J.

2017-12-01

Interference between Ps phases and reverberations (PPs, PSs phases and reverberations thereof) make it difficult to use Ps receiver functions (RF) in regions with thick sediments. Crustal reverberations typically interfere with Ps phases from the lithosphere-asthenosphere boundary (LAB). We have developed a method to separate Ps phases from reverberations by deconvolution of all the data recorded at a seismic station by removing phases from a single wavefront at each iteration of the deconvolution (wavefield iterative deconvolution or WID). We applied WID to data collected in the Gulf Coast and Llano Front regions of Texas by the EarthScope Transportable array and by a temporary deployment of 23 broadband seismometers (deployed by Texas Tech and Baylor Universities). The 23 station temporary deployment was 300 km long; crossing from Matagorda Island onto the Llano uplift. 3-D imaging using these data shows that the deepest part of the sedimentary basin may be inboard of the coastline. The Moho beneath the Gulf Coast plain does not appear in many of the images. This could be due to interference from reverberations from shallower layers or it may indicate the lack of a strong velocity contrast at the Moho perhaps due to serpentinization of the uppermost mantle. The Moho appears to be flat, at 40 km) beneath most of the Llano uplift but may thicken to the south and thin beneath the Coastal plain. After application of WID, we were able to identify a negatively polarized Ps phase consistent with LAB depths identified in Sp RF images. The LAB appears to be 80-100 km deep beneath most of the coast but is 100 to 120 km deep beneath the Llano uplift. There are other negatively polarized phases between 160 and 200 km depths beneath the Gulf Coast and the Llano Uplift. These deeper phases may indicate that, in this region, the LAB is transitional in nature and rather than a discrete boundary.

SU-E-T-236: Deconvolution of the Total Nuclear Cross-Sections of Therapeutic Protons and the Characterization of the Reaction Channels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ulmer, W.

2015-06-15

Purpose: The knowledge of the total nuclear cross-section Qtot(E) of therapeutic protons Qtot(E) provides important information in advanced radiotherapy with protons, such as the decrease of fluence of primary protons, the release of secondary particles (neutrons, protons, deuterons, etc.), and the production of nuclear fragments (heavy recoils), which usually undergo β+/− decay by emission of γ-quanta. Therefore determination of Qtot(E) is an important tool for sophisticated calculation algorithms of dose distributions. This cross-section can be determined by a linear combination of shifted Gaussian kernels and an error-function. The resonances resulting from deconvolutions in the energy space can be associated withmore » typical nuclear reactions. Methods: The described method of the determination of Qtot(E) results from an extension of the Breit-Wigner formula and a rather extended version of the nuclear shell theory to include nuclear correlation effects, clusters and highly excited/virtually excited nuclear states. The elastic energy transfer of protons to nucleons (the quantum numbers of the target nucleus remain constant) can be removed by the mentioned deconvolution. Results: The deconvolution of the term related to the error-function of the type cerf*er((E-ETh)/σerf] is the main contribution to obtain various nuclear reactions as resonances, since the elastic part of energy transfer is removed. The nuclear products of various elements of therapeutic interest like oxygen, calcium are classified and calculated. Conclusions: The release of neutrons is completely underrated, in particular, for low-energy protons. The transport of seconary particles, e.g. cluster formation by deuterium, tritium and α-particles, show an essential contribution to secondary particles, and the heavy recoils, which create γ-quanta by decay reactions, lead to broadening of the scatter profiles. These contributions cannot be accounted for by one single Gaussian kernel for the description of lateral scatter.« less

High-resolution monochromated electron energy-loss spectroscopy of organic photovoltaic materials.

PubMed

Alexander, Jessica A; Scheltens, Frank J; Drummy, Lawrence F; Durstock, Michael F; Hage, Fredrik S; Ramasse, Quentin M; McComb, David W

2017-09-01

Advances in electron monochromator technology are providing opportunities for high energy resolution (10 - 200meV) electron energy-loss spectroscopy (EELS) to be performed in the scanning transmission electron microscope (STEM). The energy-loss near-edge structure in core-loss spectroscopy is often limited by core-hole lifetimes rather than the energy spread of the incident illumination. However, in the valence-loss region, the reduced width of the zero loss peak makes it possible to resolve clearly and unambiguously spectral features at very low energy-losses (<3eV). In this contribution, high-resolution EELS was used to investigate four materials commonly used in organic photovoltaics (OPVs): poly(3-hexlythiophene) (P3HT), [6,6] phenyl-C 61 butyric acid methyl ester (PCBM), copper phthalocyanine (CuPc), and fullerene (C 60 ). Data was collected on two different monochromated instruments - a Nion UltraSTEM 100 MC 'HERMES' and a FEI Titan 3 60-300 Image-Corrected S/TEM - using energy resolutions (as defined by the zero loss peak full-width at half-maximum) of 35meV and 175meV, respectively. The data was acquired to allow deconvolution of plural scattering, and Kramers-Kronig analysis was utilized to extract the complex dielectric functions. The real and imaginary parts of the complex dielectric functions obtained from the two instruments were compared to evaluate if the enhanced resolution in the Nion provides new opto-electronic information for these organic materials. The differences between the spectra are discussed, and the implications for STEM-EELS studies of advanced materials are considered. Copyright © 2017 Elsevier B.V. All rights reserved.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions.

PubMed

Jo, Javier A; Fang, Qiyin; Papaioannou, Thanassis; Baker, J Dennis; Dorafshar, Amir H; Reil, Todd; Qiao, Jian-Hua; Fishbein, Michael C; Freischlag, Julie A; Marcu, Laura

2006-01-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

Application of the laguerre deconvolution method for time-resolved fluorescence spectroscopy to the characterization of atherosclerotic plaques.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J; Marcu, L

2005-01-01

This study investigates the ability of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) to detect inflammation in atherosclerotic lesion, a key feature of plaque vulnerability. A total of 348 TR-LIFS measurements were taken from carotid plaques of 30 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as Early, Fibrotic/Calcified or Inflamed lesions. A stepwise linear discriminant analysis algorithm was developed using spectral and TR features (normalized intensity values and Laguerre expansion coefficients at discrete emission wavelengths, respectively). Features from only three emission wavelengths (390, 450 and 500 nm) were used in the classifier. The Inflamed lesions were discriminated with sensitivity > 80% and specificity > 90 %, when the Laguerre expansion coefficients were included in the feature space. These results indicate that TR-LIFS information derived from the Laguerre expansion coefficients at few selected emission wavelengths can discriminate inflammation in atherosclerotic plaques. We believe that TR-LIFS derived Laguerre expansion coefficients can provide a valuable additional dimension for the detection of vulnerable plaques.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

NASA Astrophysics Data System (ADS)

Jo, Javier A.; Fang, Qiyin; Papaioannou, Thanassis; Baker, J. Dennis; Dorafshar, Amir; Reil, Todd; Qiao, Jianhua; Fishbein, Michael C.; Freischlag, Julie A.; Marcu, Laura

2006-03-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

PubMed Central

Jo, Javier A.; Fang, Qiyin; Papaioannou, Thanassis; Baker, J. Dennis; Dorafshar, Amir H.; Reil, Todd; Qiao, Jian-Hua; Fishbein, Michael C.; Freischlag, Julie A.; Marcu, Laura

2007-01-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability. PMID:16674179

Uncertainty of High Intensity Therapeutic Ultrasound (HITU) Field Characterization with Hydrophones: Effects of Nonlinearity, Spatial Averaging, and Complex Sensitivity

PubMed Central

Liu, Yunbo; Wear, Keith A.; Harris, Gerald R.

2017-01-01

Reliable acoustic characterization is fundamental for patient safety and clinical efficacy during high intensity therapeutic ultrasound (HITU) treatment. Technical challenges, such as measurement uncertainty and signal analysis still exist for HITU exposimetry using ultrasound hydrophones. In this work, four hydrophones were compared for pressure measurement: a robust needle hydrophone, a small PVDF capsule hydrophone and two different fiber-optic hydrophones. The focal waveform and beam distribution of a single element HITU transducer (1.05 MHz and 3.3 MHz) were evaluated. Complex deconvolution between the hydrophone voltage signal and frequency-dependent complex sensitivity was performed to obtain pressure waveform. Compressional pressure, rarefactional pressure, and focal beam distribution were compared up to 10.6/−6.0 MPa (p+ and p−) (1.05 MHz) and 20.65/−7.20 MPa (3.3 MHz). In particular, the effects of spatial averaging, local nonlinear distortion, complex deconvolution and hydrophone damage thresholds were investigated. This study showed an uncertainty of no better than 10–15% on hydrophone-based HITU pressure characterization. PMID:28735734

Transplantation of epiphytic bioaccumulators (Tillandsia capillaris) for high spatial resolution biomonitoring of trace elements and point sources deconvolution in a complex mining/smelting urban context

NASA Astrophysics Data System (ADS)

Goix, Sylvaine; Resongles, Eléonore; Point, David; Oliva, Priscia; Duprey, Jean Louis; de la Galvez, Erika; Ugarte, Lincy; Huayta, Carlos; Prunier, Jonathan; Zouiten, Cyril; Gardon, Jacques

2013-12-01

Monitoring atmospheric trace elements (TE) levels and tracing their source origin is essential for exposure assessment and human health studies. Epiphytic Tillandsia capillaris plants were used as bioaccumulator of TE in a complex polymetallic mining/smelting urban context (Oruro, Bolivia). Specimens collected from a pristine reference site were transplanted at a high spatial resolution (˜1 sample/km2) throughout the urban area. About twenty-seven elements were measured after a 4-month exposure, also providing new information values for reference material BCR482. Statistical power analysis for this biomonitoring mapping approach against classical aerosols surveys performed on the same site showed the better aptitude of T. Capillaris to detect geographical trend, and to deconvolute multiple contamination sources using geostatistical principal component analysis. Transplanted specimens in the vicinity of the mining and smelting areas were characterized by extreme TE accumulation (Sn > Ag > Sb > Pb > Cd > As > W > Cu > Zn). Three contamination sources were identified: mining (Ag, Pb, Sb), smelting (As, Sn) and road traffic (Zn) emissions, confirming results of previous aerosol survey.

Estimation of neutron energy distributions from prompt gamma emissions

NASA Astrophysics Data System (ADS)

Panikkath, Priyada; Udupi, Ashwini; Sarkar, P. K.

2017-11-01

A technique of estimating the incident neutron energy distribution from emitted prompt gamma intensities from a system exposed to neutrons is presented. The emitted prompt gamma intensities or the measured photo peaks in a gamma detector are related to the incident neutron energy distribution through a convolution of the response of the system generating the prompt gammas to mono-energetic neutrons. Presently, the system studied is a cylinder of high density polyethylene (HDPE) placed inside another cylinder of borated HDPE (BHDPE) having an outer Pb-cover and exposed to neutrons. The emitted five prompt gamma peaks from hydrogen, boron, carbon and lead can be utilized to unfold the incident neutron energy distribution as an under-determined deconvolution problem. Such an under-determined set of equations are solved using the genetic algorithm based Monte Carlo de-convolution code GAMCD. Feasibility of the proposed technique is demonstrated theoretically using the Monte Carlo calculated response matrix and intensities of emitted prompt gammas from the Pb-covered BHDPE-HDPE system in the case of several incident neutron spectra spanning different energy ranges.

Thermoluminescence glow curve deconvolution and trapping parameters determination of dysprosium doped magnesium borate glass

NASA Astrophysics Data System (ADS)

Salama, E.; Soliman, H. A.

2018-07-01

In this paper, thermoluminescence glow curves of gamma irradiated magnesium borate glass doped with dysprosium were studied. The number of interfering peaks and in turn the number of electron trap levels are determined using the Repeated Initial Rise (RIR) method. At different heating rates (β), the glow curves were deconvoluted into two interfering peaks based on the results of RIR method. Kinetic parameters such as trap depth, kinetic order (b) and frequency factor (s) for each electron trap level is determined using the Peak Shape (PS) method. The obtained results indicated that, the magnesium borate glass doped with dysprosium has two electron trap levels with the average depth energies of 0.63 and 0.79 eV respectively. These two traps have second order kinetic and are formed at low temperature region. The obtained results due to the glow curve analysis could be used to explain some observed properties such as, high thermal fading and light sensitivity for such thermoluminescence material. In this work, systematic procedures to determine the kinetic parameters of any thermoluminescence material are successfully introduced.

Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution.

PubMed

Perez, Victor; Chang, Bo-Jui; Stelzer, Ernst Hans Karl

2016-11-16

Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodization function and a Wiener filter. Empirically tuning the parameters in these functions can minimize artifacts, but such an approach is subjective and produces volatile results. We present a robust and objective method that yields optimal results by two straightforward filtering steps with Richardson-Lucy-based deconvolutions. We provide a resource to identify artifacts in 2D-SIM images by analyzing two main reasons for artifacts, out-of-focus background and a fluctuating reconstruction spectrum. We show how the filtering steps improve images of test specimens, microtubules, yeast and mammalian cells.

A joint Richardson-Lucy deconvolution algorithm for the reconstruction of multifocal structured illumination microscopy data.

PubMed

Ströhl, Florian; Kaminski, Clemens F

2015-01-16

We demonstrate the reconstruction of images obtained by multifocal structured illumination microscopy, MSIM, using a joint Richardson-Lucy, jRL-MSIM, deconvolution algorithm, which is based on an underlying widefield image-formation model. The method is efficient in the suppression of out-of-focus light and greatly improves image contrast and resolution. Furthermore, it is particularly well suited for the processing of noise corrupted data. The principle is verified on simulated as well as experimental data and a comparison of the jRL-MSIM approach with the standard reconstruction procedure, which is based on image scanning microscopy, ISM, is made. Our algorithm is efficient and freely available in a user friendly software package.

A joint Richardson—Lucy deconvolution algorithm for the reconstruction of multifocal structured illumination microscopy data

NASA Astrophysics Data System (ADS)

Ströhl, Florian; Kaminski, Clemens F.

2015-03-01

We demonstrate the reconstruction of images obtained by multifocal structured illumination microscopy, MSIM, using a joint Richardson-Lucy, jRL-MSIM, deconvolution algorithm, which is based on an underlying widefield image-formation model. The method is efficient in the suppression of out-of-focus light and greatly improves image contrast and resolution. Furthermore, it is particularly well suited for the processing of noise corrupted data. The principle is verified on simulated as well as experimental data and a comparison of the jRL-MSIM approach with the standard reconstruction procedure, which is based on image scanning microscopy, ISM, is made. Our algorithm is efficient and freely available in a user friendly software package.

Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution

NASA Astrophysics Data System (ADS)

Perez, Victor; Chang, Bo-Jui; Stelzer, Ernst Hans Karl

2016-11-01

Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodization function and a Wiener filter. Empirically tuning the parameters in these functions can minimize artifacts, but such an approach is subjective and produces volatile results. We present a robust and objective method that yields optimal results by two straightforward filtering steps with Richardson-Lucy-based deconvolutions. We provide a resource to identify artifacts in 2D-SIM images by analyzing two main reasons for artifacts, out-of-focus background and a fluctuating reconstruction spectrum. We show how the filtering steps improve images of test specimens, microtubules, yeast and mammalian cells.

Data matching for free-surface multiple attenuation by multidimensional deconvolution

NASA Astrophysics Data System (ADS)

van der Neut, Joost; Frijlink, Martijn; van Borselen, Roald

2012-09-01

A common strategy for surface-related multiple elimination of seismic data is to predict multiples by a convolutional model and subtract these adaptively from the input gathers. Problems can be posed by interfering multiples and primaries. Removing multiples by multidimensional deconvolution (MDD) (inversion) does not suffer from these problems. However, this approach requires data to be consistent, which is often not the case, especially not at interpolated near-offsets. A novel method is proposed to improve data consistency prior to inversion. This is done by backpropagating first-order multiples with a time-gated reference primary event and matching these with early primaries in the input gather. After data matching, multiple elimination by MDD can be applied with a deterministic inversion scheme.

Two-Stage, In Silico Deconvolution of the Lymphocyte Compartment of the Peripheral Whole Blood Transcriptome in the Context of Acute Kidney Allograft Rejection

PubMed Central

Shannon, Casey P.; Balshaw, Robert; Ng, Raymond T.; Wilson-McManus, Janet E.; Keown, Paul; McMaster, Robert; McManus, Bruce M.; Landsberg, David; Isbel, Nicole M.; Knoll, Greg; Tebbutt, Scott J.

2014-01-01

Acute rejection is a major complication of solid organ transplantation that prevents the long-term assimilation of the allograft. Various populations of lymphocytes are principal mediators of this process, infiltrating graft tissues and driving cell-mediated cytotoxicity. Understanding the lymphocyte-specific biology associated with rejection is therefore critical. Measuring genome-wide changes in transcript abundance in peripheral whole blood cells can deliver a comprehensive view of the status of the immune system. The heterogeneous nature of the tissue significantly affects the sensitivity and interpretability of traditional analyses, however. Experimental separation of cell types is an obvious solution, but is often impractical and, more worrying, may affect expression, leading to spurious results. Statistical deconvolution of the cell type-specific signal is an attractive alternative, but existing approaches still present some challenges, particularly in a clinical research setting. Obtaining time-matched sample composition to biologically interesting, phenotypically homogeneous cell sub-populations is costly and adds significant complexity to study design. We used a two-stage, in silico deconvolution approach that first predicts sample composition to biologically meaningful and homogeneous leukocyte sub-populations, and then performs cell type-specific differential expression analysis in these same sub-populations, from peripheral whole blood expression data. We applied this approach to a peripheral whole blood expression study of kidney allograft rejection. The patterns of differential composition uncovered are consistent with previous studies carried out using flow cytometry and provide a relevant biological context when interpreting cell type-specific differential expression results. We identified cell type-specific differential expression in a variety of leukocyte sub-populations at the time of rejection. The tissue-specificity of these differentially expressed probe-set lists is consistent with the originating tissue and their functional enrichment consistent with allograft rejection. Finally, we demonstrate that the strategy described here can be used to derive useful hypotheses by validating a cell type-specific ratio in an independent cohort using the nanoString nCounter assay. PMID:24733377

Deconvolution enhanced direction of arrival estimation using one- and three-component seismic arrays applied to ocean induced microseisms

NASA Astrophysics Data System (ADS)

Gal, M.; Reading, A. M.; Ellingsen, S. P.; Koper, K. D.; Burlacu, R.; Gibbons, S. J.

2016-07-01

Microseisms in the period of 2-10 s are generated in deep oceans and near coastal regions. It is common for microseisms from multiple sources to arrive at the same time at a given seismometer. It is therefore desirable to be able to measure multiple slowness vectors accurately. Popular ways to estimate the direction of arrival of ocean induced microseisms are the conventional (fk) or adaptive (Capon) beamformer. These techniques give robust estimates, but are limited in their resolution capabilities and hence do not always detect all arrivals. One of the limiting factors in determining direction of arrival with seismic arrays is the array response, which can strongly influence the estimation of weaker sources. In this work, we aim to improve the resolution for weaker sources and evaluate the performance of two deconvolution algorithms, Richardson-Lucy deconvolution and a new implementation of CLEAN-PSF. The algorithms are tested with three arrays of different aperture (ASAR, WRA and NORSAR) using 1 month of real data each and compared with the conventional approaches. We find an improvement over conventional methods from both algorithms and the best performance with CLEAN-PSF. We then extend the CLEAN-PSF framework to three components (3C) and evaluate 1 yr of data from the Pilbara Seismic Array in northwest Australia. The 3C CLEAN-PSF analysis is capable in resolving a previously undetected Sn phase.

Wellskins and slug tests: where's the bias?

NASA Astrophysics Data System (ADS)

Rovey, C. W.; Niemann, W. L.

2001-03-01

Pumping tests in an outwash sand at the Camp Dodge Site give hydraulic conductivities ( K) approximately seven times greater than conventional slug tests in the same wells. To determine if this difference is caused by skin bias, we slug tested three sets of wells, each in a progressively greater stage of development. Results were analyzed with both the conventional Bouwer-Rice method and the deconvolution method, which quantifies the skin and eliminates its effects. In 12 undeveloped wells the average skin is +4.0, causing underestimation of conventional slug-test K (Bouwer-Rice method) by approximately a factor of 2 relative to the deconvolution method. In seven nominally developed wells the skin averages just +0.34, and the Bouwer-Rice method gives K within 10% of that calculated with the deconvolution method. The Bouwer-Rice K in this group is also within 5% of that measured by natural-gradient tracer tests at the same site. In 12 intensely developed wells the average skin is <-0.82, consistent with an average skin of -1.7 measured during single-well pumping tests. At this site the maximum possible skin bias is much smaller than the difference between slug and pumping-test Ks. Moreover, the difference in K persists even in intensely developed wells with negative skins. Therefore, positive wellskins do not cause the difference in K between pumping and slug tests at this site.

Microscopic analysis of cell death by metabolic stress-induced autophagy in prostate cancer

NASA Astrophysics Data System (ADS)

Changou, Chun; Cheng, R. Holland; Bold, Richard; Kung, Hsing-Jien; Chuang, Frank Y. S.

2013-02-01

Autophagy is an intracellular recycling mechanism that helps cells to survive against environmental stress and nutritional starvation. We have recently shown that prostate cancers undergo metabolic stress and caspase-independent cell death following exposure to arginine deiminase (ADI, an enzyme that degrades arginine in tissue). The aims of our current investigation into the application of ADI as a novel cancer therapy are to identify the components mediating tumor cell death, and to determine the role of autophagy (stimulated by ADI and/or rapamycin) on cell death. Using advanced fluorescence microscopy techniques including 3D deconvolution and superresolution structured-illumination microscopy (SIM), we show that prostate tumor cells that are killed after exposure to ADI for extended periods, exhibit a morphology that is distinct from caspase-dependent apoptosis; and that autophagosomes forming as a result of ADI stimulation contain DAPI-stained nuclear material. Fluorescence imaging (as well as cryo-electron microscopy) show a breakdown of both the inner and outer nuclear membranes at the interface between the cell nucleus and aggregated autophagolysosomes. Finally, the addition of N-acetyl cysteine (or NAC, a scavenger for reactive oxygen species) effectively abolishes the appearance of autophagolysosomes containing nuclear material. We hope to continue this research to understand the processes that govern the survival or death of these tumor cells, in order to develop methods to improve the efficacy of cancer pharmacotherapy.

Proteomic Prediction of Breast Cancer Risk: A Cohort Study

DTIC Science & Technology

2007-03-01

Total 1728 1189 68.81 (c) Data processing. Data analysis was performed using in-house software (Du P , Angeletti RH. Automatic deconvolution of...isotope-resolved mass spectra using variable selection and quantized peptide mass distribution. Anal Chem., 78:3385-92, 2006; P Du, R Sudha, MB...control. Reportable Outcomes So far our publications have been on the development of algorithms for signal processing: 1. Du P , Angeletti RH

Two-photon speckle illumination for super-resolution microscopy.

PubMed

Negash, Awoke; Labouesse, Simon; Chaumet, Patrick C; Belkebir, Kamal; Giovannini, Hugues; Allain, Marc; Idier, Jérôme; Sentenac, Anne

2018-06-01

We present a numerical study of a microscopy setup in which the sample is illuminated with uncontrolled speckle patterns and the two-photon excitation fluorescence is collected on a camera. We show that, using a simple deconvolution algorithm for processing the speckle low-resolution images, this wide-field imaging technique exhibits resolution significantly better than that of two-photon excitation scanning microscopy or one-photon excitation bright-field microscopy.

Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN.

PubMed

Hao, Jie; Liebeke, Manuel; Astle, William; De Iorio, Maria; Bundy, Jacob G; Ebbels, Timothy M D

2014-01-01

Data processing for 1D NMR spectra is a key bottleneck for metabolomic and other complex-mixture studies, particularly where quantitative data on individual metabolites are required. We present a protocol for automated metabolite deconvolution and quantification from complex NMR spectra by using the Bayesian automated metabolite analyzer for NMR (BATMAN) R package. BATMAN models resonances on the basis of a user-controllable set of templates, each of which specifies the chemical shifts, J-couplings and relative peak intensities for a single metabolite. Peaks are allowed to shift position slightly between spectra, and peak widths are allowed to vary by user-specified amounts. NMR signals not captured by the templates are modeled non-parametrically by using wavelets. The protocol covers setting up user template libraries, optimizing algorithmic input parameters, improving prior information on peak positions, quality control and evaluation of outputs. The outputs include relative concentration estimates for named metabolites together with associated Bayesian uncertainty estimates, as well as the fit of the remainder of the spectrum using wavelets. Graphical diagnostics allow the user to examine the quality of the fit for multiple spectra simultaneously. This approach offers a workflow to analyze large numbers of spectra and is expected to be useful in a wide range of metabolomics studies.

A Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) Determined from Phased Microphone Arrays

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.; Humphreys, William M.

2006-01-01

Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics.

An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray.

PubMed

Salas, Lucas A; Koestler, Devin C; Butler, Rondi A; Hansen, Helen M; Wiencke, John K; Kelsey, Karl T; Christensen, Brock C

2018-05-29

Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R 2  = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.

Strehl-constrained reconstruction of post-adaptive optics data and the Software Package AIRY, v. 6.1

NASA Astrophysics Data System (ADS)

Carbillet, Marcel; La Camera, Andrea; Deguignet, Jérémy; Prato, Marco; Bertero, Mario; Aristidi, Éric; Boccacci, Patrizia

2014-08-01

We first briefly present the last version of the Software Package AIRY, version 6.1, a CAOS-based tool which includes various deconvolution methods, accelerations, regularizations, super-resolution, boundary effects reduction, point-spread function extraction/extrapolation, stopping rules, and constraints in the case of iterative blind deconvolution (IBD). Then, we focus on a new formulation of our Strehl-constrained IBD, here quantitatively compared to the original formulation for simulated near-infrared data of an 8-m class telescope equipped with adaptive optics (AO), showing their equivalence. Next, we extend the application of the original method to the visible domain with simulated data of an AO-equipped 1.5-m telescope, testing also the robustness of the method with respect to the Strehl ratio estimation.

Lightfield super-resolution through turbulence

NASA Astrophysics Data System (ADS)

Trujillo-Sevilla, Juan M.; Fernández-Valdivia, Juan J.; Rodríguez-Ramos, Luis F.; Cárdenes, Óscar G.; Marichal-Hernández, José G.; Javidi, Bahram; Rodríguez-Ramos, José M.

2015-05-01

In this paper, we use information from the light field to obtain a distribution map of the wavefront phase. This distribution is associated with changes in refractive index which are relevant in the propagation of light through a heterogeneous or turbulent medium. Through the measurement of the wavefront phase from a single shot, it is possible to make the deconvolution of blurred images affected by the turbulence. If this deconvolution is applied to light fields obtained by plenoptic acquisition, the original optical resolution associated to the objective lens is restored, it means we are using a kind of superresolution technique that works properly even in the presence of turbulence. The wavefront phase can also be estimated from the defocused images associated to the light field: we present here preliminary results using this approach.

The mathematics of a successful deconvolution: a quantitative assessment of mixture-based combinatorial libraries screened against two formylpeptide receptors.

PubMed

Santos, Radleigh G; Appel, Jon R; Giulianotti, Marc A; Edwards, Bruce S; Sklar, Larry A; Houghten, Richard A; Pinilla, Clemencia

2013-05-30

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays.

Semi-blind sparse image reconstruction with application to MRFM.

PubMed

Park, Se Un; Dobigeon, Nicolas; Hero, Alfred O

2012-09-01

We propose a solution to the image deconvolution problem where the convolution kernel or point spread function (PSF) is assumed to be only partially known. Small perturbations generated from the model are exploited to produce a few principal components explaining the PSF uncertainty in a high-dimensional space. Unlike recent developments on blind deconvolution of natural images, we assume the image is sparse in the pixel basis, a natural sparsity arising in magnetic resonance force microscopy (MRFM). Our approach adopts a Bayesian Metropolis-within-Gibbs sampling framework. The performance of our Bayesian semi-blind algorithm for sparse images is superior to previously proposed semi-blind algorithms such as the alternating minimization algorithm and blind algorithms developed for natural images. We illustrate our myopic algorithm on real MRFM tobacco virus data.

Advanced Source Deconvolution Methods for Compton Telescopes

NASA Astrophysics Data System (ADS)

Zoglauer, Andreas

The next generation of space telescopes utilizing Compton scattering for astrophysical observations is destined to one day unravel the mysteries behind Galactic nucleosynthesis, to determine the origin of the positron annihilation excess near the Galactic center, and to uncover the hidden emission mechanisms behind gamma-ray bursts. Besides astrophysics, Compton telescopes are establishing themselves in heliophysics, planetary sciences, medical imaging, accelerator physics, and environmental monitoring. Since the COMPTEL days, great advances in the achievable energy and position resolution were possible, creating an extremely vast, but also extremely sparsely sampled data space. Unfortunately, the optimum way to analyze the data from the next generation of Compton telescopes has not yet been found, which can retrieve all source parameters (location, spectrum, polarization, flux) and achieves the best possible resolution and sensitivity at the same time. This is especially important for all sciences objectives looking at the inner Galaxy: the large amount of expected sources, the high background (internal and Galactic diffuse emission), and the limited angular resolution, make it the most taxing case for data analysis. In general, two key challenges exist: First, what are the best data space representations to answer the specific science questions? Second, what is the best way to deconvolve the data to fully retrieve the source parameters? For modern Compton telescopes, the existing data space representations can either correctly reconstruct the absolute flux (binned mode) or achieve the best possible resolution (list-mode), both together were not possible up to now. Here we propose to develop a two-stage hybrid reconstruction method which combines the best aspects of both. Using a proof-of-concept implementation we can for the first time show that it is possible to alternate during each deconvolution step between a binned-mode approach to get the flux right and a list-mode approach to get the best angular resolution, to get achieve both at the same time! The second open question concerns the best deconvolution algorithm. For example, several algorithms have been investigated for the famous COMPTEL 26Al map which resulted in significantly different images. There is no clear answer as to which approach provides the most accurate result, largely due to the fact that detailed simulations to test and verify the approaches and their limitations were not possible at that time. This has changed, and therefore we propose to evaluate several deconvolution algorithms (e.g. Richardson-Lucy, Maximum-Entropy, MREM, and stochastic origin ensembles) with simulations of typical observations to find the best algorithm for each application and for each stage of the hybrid reconstruction approach. We will adapt, implement, and fully evaluate the hybrid source reconstruction approach as well as the various deconvolution algorithms with simulations of synthetic benchmarks and simulations of key science objectives such as diffuse nuclear line science and continuum science of point sources, as well as with calibrations/observations of the COSI balloon telescope. This proposal for "development of new data analysis methods for future satellite missions" will significantly improve the source deconvolution techniques for modern Compton telescopes and will allow unlocking the full potential of envisioned satellite missions using Compton-scatter technology in astrophysics, heliophysics and planetary sciences, and ultimately help them to "discover how the universe works" and to better "understand the sun". Ultimately it will also benefit ground based applications such as nuclear medicine and environmental monitoring as all developed algorithms will be made publicly available within the open-source Compton telescope analysis framework MEGAlib.

Early disrupted neurovascular coupling and changed event level hemodynamic response function in type 2 diabetes: an fMRI study.

PubMed

Duarte, João V; Pereira, João M S; Quendera, Bruno; Raimundo, Miguel; Moreno, Carolina; Gomes, Leonor; Carrilho, Francisco; Castelo-Branco, Miguel

2015-10-01

Type 2 diabetes (T2DM) patients develop vascular complications and have increased risk for neurophysiological impairment. Vascular pathophysiology may alter the blood flow regulation in cerebral microvasculature, affecting neurovascular coupling. Reduced fMRI signal can result from decreased neuronal activation or disrupted neurovascular coupling. The uncertainty about pathophysiological mechanisms (neurodegenerative, vascular, or both) underlying brain function impairments remains. In this cross-sectional study, we investigated if the hemodynamic response function (HRF) in lesion-free brains of patients is altered by measuring BOLD (Blood Oxygenation Level-Dependent) response to visual motion stimuli. We used a standard block design to examine the BOLD response and an event-related deconvolution approach. Importantly, the latter allowed for the first time to directly extract the true shape of HRF without any assumption and probe neurovascular coupling, using performance-matched stimuli. We discovered a change in HRF in early stages of diabetes. T2DM patients show significantly different fMRI response profiles. Our visual paradigm therefore demonstrated impaired neurovascular coupling in intact brain tissue. This implies that functional studies in T2DM require the definition of HRF, only achievable with deconvolution in event-related experiments. Further investigation of the mechanisms underlying impaired neurovascular coupling is needed to understand and potentially prevent the progression of brain function decrements in diabetes.

Deconvolution of Thermal Emissivity Spectra of Mercury to their Endmember Counterparts measured in Simulated Mercury Surface Conditions

NASA Astrophysics Data System (ADS)

Varatharajan, I.; D'Amore, M.; Maturilli, A.; Helbert, J.; Hiesinger, H.

2017-12-01

The Mercury Radiometer and Thermal Imaging Spectrometer (MERTIS) payload of ESA/JAXA Bepicolombo mission to Mercury will map the thermal emissivity at wavelength range of 7-14 μm and spatial resolution of 500 m/pixel [1]. Mercury was also imaged at the same wavelength range using the Boston University's Mid-Infrared Spectrometer and Imager (MIRSI) mounted on the NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii with the minimum spatial coverage of 400-600km/spectra which blends all rocks, minerals, and soil types [2]. Therefore, the study [2] used quantitative deconvolution algorithm developed by [3] for spectral unmixing of this composite thermal emissivity spectrum from telescope to their respective areal fractions of endmember spectra; however, the thermal emissivity of endmembers used in [2] is the inverted reflectance measurements (Kirchhoff's law) of various samples measured at room temperature and pressure. Over a decade, the Planetary Spectroscopy Laboratory (PSL) at the Institute of Planetary Research (PF) at the German Aerospace Center (DLR) facilitates the thermal emissivity measurements under controlled and simulated surface conditions of Mercury by taking emissivity measurements at varying temperatures from 100-500°C under vacuum conditions supporting MERTIS payload. The measured thermal emissivity endmember spectral library therefore includes major silicates such as bytownite, anorthoclase, synthetic glass, olivine, enstatite, nepheline basanite, rocks like komatiite, tektite, Johnson Space Center lunar simulant (1A), and synthetic powdered sulfides which includes MgS, FeS, CaS, CrS, TiS, NaS, and MnS. Using such specialized endmember spectral library created under Mercury's conditions significantly increases the accuracy of the deconvolution model results. In this study, we revisited the available telescope spectra and redeveloped the algorithm by [3] by only choosing the endmember spectral library created at PSL for unbiased model accuracy with the RMS value of 0.03-0.04. Currently, the telescope spectra are investigated for its calibrations and the results will be presented at AGU. References: [1] Hiesinger, H. and J. Helbert (2010) PSS, 58(1-2): 144-165. [2] Sprague, A.L. et al (2009) PSS, 57, 364-383. [3] Ramsey and Christiansen (1998) JGR, 103, 577-596

SU-E-T-299: Small Fields Profiles Correction Through Detectors Spatial Response Functions and Field Size Dependence Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Filipuzzi, M; Garrigo, E; Venencia, C

2014-06-01

Purpose: To calculate the spatial response function of various radiation detectors, to evaluate the dependence on the field size and to analyze the small fields profiles corrections by deconvolution techniques. Methods: Crossline profiles were measured on a Novalis Tx 6MV beam with a HDMLC. The configuration setup was SSD=100cm and depth=5cm. Five fields were studied (200×200mm2,100×100mm2, 20×20mm2, 10×10mm2and 5×5mm2) and measured were made with passive detectors (EBT3 radiochromic films and TLD700 thermoluminescent detectors), ionization chambers (PTW30013, PTW31003, CC04 and PTW31016) and diodes (PTW60012 and IBA SFD). The results of passive detectors were adopted as the actual beam profile. To calculatemore » the detectors kernels, modeled by Gaussian functions, an iterative process based on a least squares criterion was used. The deconvolutions of the measured profiles were calculated with the Richardson-Lucy method. Results: The profiles of the passive detectors corresponded with a difference in the penumbra less than 0.1mm. Both diodes resolve the profiles with an overestimation of the penumbra smaller than 0.2mm. For the other detectors, response functions were calculated and resulted in Gaussian functions with a standard deviation approximate to the radius of the detector in study (with a variation less than 3%). The corrected profiles resolve the penumbra with less than 1% error. Major discrepancies were observed for cases in extreme conditions (PTW31003 and 5×5mm2 field size). Conclusion: This work concludes that the response function of a radiation detector is independent on the field size, even for small radiation beams. The profiles correction, using deconvolution techniques and response functions of standard deviation equal to the radius of the detector, gives penumbra values with less than 1% difference to the real profile. The implementation of this technique allows estimating the real profile, freeing from the effects of the detector used for the acquisition.« less

Deep Deconvolutional Neural Network for Target Segmentation of Nasopharyngeal Cancer in Planning Computed Tomography Images.

PubMed

Men, Kuo; Chen, Xinyuan; Zhang, Ye; Zhang, Tao; Dai, Jianrong; Yi, Junlin; Li, Yexiong

2017-01-01

Radiotherapy is one of the main treatment methods for nasopharyngeal carcinoma (NPC). It requires exact delineation of the nasopharynx gross tumor volume (GTVnx), the metastatic lymph node gross tumor volume (GTVnd), the clinical target volume (CTV), and organs at risk in the planning computed tomography images. However, this task is time-consuming and operator dependent. In the present study, we developed an end-to-end deep deconvolutional neural network (DDNN) for segmentation of these targets. The proposed DDNN is an end-to-end architecture enabling fast training and testing. It consists of two important components: an encoder network and a decoder network. The encoder network was used to extract the visual features of a medical image and the decoder network was used to recover the original resolution by deploying deconvolution. A total of 230 patients diagnosed with NPC stage I or stage II were included in this study. Data from 184 patients were chosen randomly as a training set to adjust the parameters of DDNN, and the remaining 46 patients were the test set to assess the performance of the model. The Dice similarity coefficient (DSC) was used to quantify the segmentation results of the GTVnx, GTVnd, and CTV. In addition, the performance of DDNN was compared with the VGG-16 model. The proposed DDNN method outperformed the VGG-16 in all the segmentation. The mean DSC values of DDNN were 80.9% for GTVnx, 62.3% for the GTVnd, and 82.6% for CTV, whereas VGG-16 obtained 72.3, 33.7, and 73.7% for the DSC values, respectively. DDNN can be used to segment the GTVnx and CTV accurately. The accuracy for the GTVnd segmentation was relatively low due to the considerable differences in its shape, volume, and location among patients. The accuracy is expected to increase with more training data and combination of MR images. In conclusion, DDNN has the potential to improve the consistency of contouring and streamline radiotherapy workflows, but careful human review and a considerable amount of editing will be required.

Detecting the Spectrum of the Atlantic's Thermo-haline Circulation: Deconvolved Climate Proxies Show How Polar Climates Communicate

NASA Astrophysics Data System (ADS)

Reischmann, Elizabeth; Yang, Xiao; Rial, José

2014-05-01

Deconvolution is widely used in a wide variety of scientific fields, including its significant use in seismology, as a tool to recover real input from a system's impulse response and output. Our research uses spectral division deconvolution in the context of studying the impulse response of the possible relationship between the nonlinear climates of the Polar Regions by using select δ18O ice cores from both poles. This is feasible in spite of the fact that the records may be the result of nonlinear processes because the two polar climates are synchronized for the period studied, forming a Hilbert transform pair. In order to perform this analysis, the age models of three Greenland and four Antarctica records have been matched using a Monte Carlo method with the methane-matched pair GRIP and BYRD as a basis of calculations. For all of the twelve resulting pairs, various deconvolutions schemes (Weiner, Damped Least Squares, Tikhonov, Truncated Singular Value Decomposition) give consistent, quasi-periodic, impulse responses of the system. Multitaper analysis then demonstrates strong, millennia scale, quasi-periodic oscillations in these system responses with a range of 2,500 to 1,000 years. However, these results are directionally dependent, with the transfer function from north to south differing from that of south north. High amplitude power peaks at 5,000 to 1,7000 years characterize the former, while the latter contains peaks at 2,500 to 1,700 years. These predominant periodicities are also found in the data, some of which have been identified as solar forcing, but others of which may indicate internal oscillations of the climate system (1.6-1.4ky). The approximately 1,500 year period transfer function, which does not have a corresponding solar forcing, may indicate one of these internal periodicities of the system, perhaps even indicating the long-term presence of the Deep Water circulation, also known as the thermo-haline circulation (THC). Simplified models of the polar climate fluctuations are shown to support these findings.

Soot Surface Oxidation in Laminar Hydrocarbon/Air Diffusion Flames at Atmospheric Pressure. Appendix I

NASA Technical Reports Server (NTRS)

Xu, F.; El-Leathy, A. M.; Kim, C. H.; Faeth, G. M.; Yuan, Z.-G. (Technical Monitor); Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)

2003-01-01

Soot surface oxidation was studied experimentally in laminar hydrocarbon/air diffusion flames at atmospheric pressure. Measurements were carried out along the axes of round fuel jets burning in coflowing dry air considering acetylene-nitrogen, ethylene, propyiene-nitrogen, propane and acetylene-benzene-nitrogen in the fuel stream. Measurements were limited to the initial stages of soot oxidation (carbon consumption less than 70%) where soot oxidation occurs at the surface of primary soot particles. The following properties were measured as a function of distance above the burner exit: soot concentrations by deconvoluted laser extinction, soot temperatures by deconvoluted multiline emission, soot structure by thermophoretic sampling and analysis using Transmission Electron Microscopy (TEM), concentrations of major stable gas species (N2, H2O, H2, O2, CO, CO2, CH4, C2H2, C2H6, C3H6, C3H8, and C6H6) by sampling and gas chromatography, concentrations of some radical species (H, OH, O) by deconvoluted Li/LiOH atomic absorption and flow velocities by laser velocimetry. For present test conditions, it was found that soot surface oxidation rates were not affected by fuel type, that direct rates of soot surface oxidation by O2 estimated from Nagle and Strickland-Constable (1962) were small compared to observed soot surface oxidation rates because soot surface oxidation was completed near the flame sheet where O2 concentrations were less than 3% by volume, and that soot surface oxidation rates were described by the OH soot surface oxidation mechanism with a collision efficiency of 0.14 and an uncertainty (95% confidence) of +/- 0.04 when allowing for direct soot surface oxidation by O2, which is in reasonably good agreement with earlier observations of soot surface oxidation rates in both premixed and diffusion flames at atmospheric pressure.

PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures.

PubMed

Marciano, Michael A; Adelman, Jonathan D

2017-03-01

The deconvolution of DNA mixtures remains one of the most critical challenges in the field of forensic DNA analysis. In addition, of all the data features required to perform such deconvolution, the number of contributors in the sample is widely considered the most important, and, if incorrectly chosen, the most likely to negatively influence the mixture interpretation of a DNA profile. Unfortunately, most current approaches to mixture deconvolution require the assumption that the number of contributors is known by the analyst, an assumption that can prove to be especially faulty when faced with increasingly complex mixtures of 3 or more contributors. In this study, we propose a probabilistic approach for estimating the number of contributors in a DNA mixture that leverages the strengths of machine learning. To assess this approach, we compare classification performances of six machine learning algorithms and evaluate the model from the top-performing algorithm against the current state of the art in the field of contributor number classification. Overall results show over 98% accuracy in identifying the number of contributors in a DNA mixture of up to 4 contributors. Comparative results showed 3-person mixtures had a classification accuracy improvement of over 6% compared to the current best-in-field methodology, and that 4-person mixtures had a classification accuracy improvement of over 20%. The Probabilistic Assessment for Contributor Estimation (PACE) also accomplishes classification of mixtures of up to 4 contributors in less than 1s using a standard laptop or desktop computer. Considering the high classification accuracy rates, as well as the significant time commitment required by the current state of the art model versus seconds required by a machine learning-derived model, the approach described herein provides a promising means of estimating the number of contributors and, subsequently, will lead to improved DNA mixture interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Experimental pencil beam kernels derivation for 3D dose calculation in flattening filter free modulated fields

NASA Astrophysics Data System (ADS)

Diego Azcona, Juan; Barbés, Benigno; Wang, Lilie; Burguete, Javier

2016-01-01

This paper presents a method to obtain the pencil-beam kernels that characterize a megavoltage photon beam generated in a flattening filter free (FFF) linear accelerator (linac) by deconvolution from experimental measurements at different depths. The formalism is applied to perform independent dose calculations in modulated fields. In our previous work a formalism was developed for ideal flat fluences exiting the linac’s head. That framework could not deal with spatially varying energy fluences, so any deviation from the ideal flat fluence was treated as a perturbation. The present work addresses the necessity of implementing an exact analysis where any spatially varying fluence can be used such as those encountered in FFF beams. A major improvement introduced here is to handle the actual fluence in the deconvolution procedure. We studied the uncertainties associated to the kernel derivation with this method. Several Kodak EDR2 radiographic films were irradiated with a 10 MV FFF photon beam from two linacs from different vendors, at the depths of 5, 10, 15, and 20cm in polystyrene (RW3 water-equivalent phantom, PTW Freiburg, Germany). The irradiation field was a 50mm diameter circular field, collimated with a lead block. The 3D kernel for a FFF beam was obtained by deconvolution using the Hankel transform. A correction on the low dose part of the kernel was performed to reproduce accurately the experimental output factors. Error uncertainty in the kernel derivation procedure was estimated to be within 0.2%. Eighteen modulated fields used clinically in different treatment localizations were irradiated at four measurement depths (total of fifty-four film measurements). Comparison through the gamma-index to their corresponding calculated absolute dose distributions showed a number of passing points (3%, 3mm) mostly above 99%. This new procedure is more reliable and robust than the previous one. Its ability to perform accurate independent dose calculations was demonstrated.

Suspected-target pesticide screening using gas chromatography-quadrupole time-of-flight mass spectrometry with high resolution deconvolution and retention index/mass spectrum library.

PubMed

Zhang, Fang; Wang, Haoyang; Zhang, Li; Zhang, Jing; Fan, Ruojing; Yu, Chongtian; Wang, Wenwen; Guo, Yinlong

2014-10-01

A strategy for suspected-target screening of pesticide residues in complicated matrices was exploited using gas chromatography in combination with hybrid quadrupole time-of-flight mass spectrometry (GC-QTOF MS). The screening workflow followed three key steps of, initial detection, preliminary identification, and final confirmation. The initial detection of components in a matrix was done by a high resolution mass spectrum deconvolution; the preliminary identification of suspected pesticides was based on a special retention index/mass spectrum (RI/MS) library that contained both the first-stage mass spectra (MS(1) spectra) and retention indices; and the final confirmation was accomplished by accurate mass measurements of representative ions with their response ratios from the MS(1) spectra or representative product ions from the second-stage mass spectra (MS(2) spectra). To evaluate the applicability of the workflow in real samples, three matrices of apple, spinach, and scallion, each spiked with 165 test pesticides in a set of concentrations, were selected as the models. The results showed that the use of high-resolution TOF enabled effective extractions of spectra from noisy chromatograms, which was based on a narrow mass window (5 mDa) and suspected-target compounds identified by the similarity match of deconvoluted full mass spectra and filtering of linear RIs. On average, over 74% of pesticides at 50 ng/mL could be identified using deconvolution and the RI/MS library. Over 80% of pesticides at 5 ng/mL or lower concentrations could be confirmed in each matrix using at least two representative ions with their response ratios from the MS(1) spectra. In addition, the application of product ion spectra was capable of confirming suspected pesticides with specificity for some pesticides in complicated matrices. In conclusion, GC-QTOF MS combined with the RI/MS library seems to be one of the most efficient tools for the analysis of suspected-target pesticide residues in complicated matrices. Copyright © 2014 Elsevier B.V. All rights reserved.

A Geophysical Inversion Model Enhancement Technique Based on the Blind Deconvolution

NASA Astrophysics Data System (ADS)

Zuo, B.; Hu, X.; Li, H.

2011-12-01

A model-enhancement technique is proposed to enhance the geophysical inversion model edges and details without introducing any additional information. Firstly, the theoretic correctness of the proposed geophysical inversion model-enhancement technique is discussed. An inversion MRM (model resolution matrix) convolution approximating PSF (Point Spread Function) method is designed to demonstrate the correctness of the deconvolution model enhancement method. Then, a total-variation regularization blind deconvolution geophysical inversion model-enhancement algorithm is proposed. In previous research, Oldenburg et al. demonstrate the connection between the PSF and the geophysical inverse solution. Alumbaugh et al. propose that more information could be provided by the PSF if we return to the idea of it behaving as an averaging or low pass filter. We consider the PSF as a low pass filter to enhance the inversion model basis on the theory of the PSF convolution approximation. Both the 1D linear and the 2D magnetotelluric inversion examples are used to analyze the validity of the theory and the algorithm. To prove the proposed PSF convolution approximation theory, the 1D linear inversion problem is considered. It shows the ratio of convolution approximation error is only 0.15%. The 2D synthetic model enhancement experiment is presented. After the deconvolution enhancement, the edges of the conductive prism and the resistive host become sharper, and the enhancement result is closer to the actual model than the original inversion model according the numerical statistic analysis. Moreover, the artifacts in the inversion model are suppressed. The overall precision of model increases 75%. All of the experiments show that the structure details and the numerical precision of inversion model are significantly improved, especially in the anomalous region. The correlation coefficient between the enhanced inversion model and the actual model are shown in Fig. 1. The figure illustrates that more information and details structure of the actual model are enhanced through the proposed enhancement algorithm. Using the proposed enhancement method can help us gain a clearer insight into the results of the inversions and help make better informed decisions.

DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data.

PubMed

Gong, Ting; Szustakowski, Joseph D

2013-04-15

For heterogeneous tissues, measurements of gene expression through mRNA-Seq data are confounded by relative proportions of cell types involved. In this note, we introduce an efficient pipeline: DeconRNASeq, an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It adopts a globally optimized non-negative decomposition algorithm through quadratic programming for estimating the mixing proportions of distinctive tissue types in next-generation sequencing data. We demonstrated the feasibility and validity of DeconRNASeq across a range of mixing levels and sources using mRNA-Seq data mixed in silico at known concentrations. We validated our computational approach for various benchmark data, with high correlation between our predicted cell proportions and the real fractions of tissues. Our study provides a rigorous, quantitative and high-resolution tool as a prerequisite to use mRNA-Seq data. The modularity of package design allows an easy deployment of custom analytical pipelines for data from other high-throughput platforms. DeconRNASeq is written in R, and is freely available at http://bioconductor.org/packages. Supplementary data are available at Bioinformatics online.

Improving Calculation Accuracies of Accumulation-Mode Fractions Based on Spectral of Aerosol Optical Depths

NASA Astrophysics Data System (ADS)

Ying, Zhang; Zhengqiang, Li; Yan, Wang

2014-03-01

Anthropogenic aerosols are released into the atmosphere, which cause scattering and absorption of incoming solar radiation, thus exerting a direct radiative forcing on the climate system. Anthropogenic Aerosol Optical Depth (AOD) calculations are important in the research of climate changes. Accumulation-Mode Fractions (AMFs) as an anthropogenic aerosol parameter, which are the fractions of AODs between the particulates with diameters smaller than 1μm and total particulates, could be calculated by AOD spectral deconvolution algorithm, and then the anthropogenic AODs are obtained using AMFs. In this study, we present a parameterization method coupled with an AOD spectral deconvolution algorithm to calculate AMFs in Beijing over 2011. All of data are derived from AErosol RObotic NETwork (AERONET) website. The parameterization method is used to improve the accuracies of AMFs compared with constant truncation radius method. We find a good correlation using parameterization method with the square relation coefficient of 0.96, and mean deviation of AMFs is 0.028. The parameterization method could also effectively solve AMF underestimate in winter. It is suggested that the variations of Angstrom indexes in coarse mode have significant impacts on AMF inversions.

Comparative genomic de-convolution of the cotton genome revealed a decaploid ancestor and widespread chromosomal fractionation.

PubMed

Wang, Xiyin; Guo, Hui; Wang, Jinpeng; Lei, Tianyu; Liu, Tao; Wang, Zhenyi; Li, Yuxian; Lee, Tae-Ho; Li, Jingping; Tang, Haibao; Jin, Dianchuan; Paterson, Andrew H

2016-02-01

The 'apparently' simple genomes of many angiosperms mask complex evolutionary histories. The reference genome sequence for cotton (Gossypium spp.) revealed a ploidy change of a complexity unprecedented to date, indeed that could not be distinguished as to its exact dosage. Herein, by developing several comparative, computational and statistical approaches, we revealed a 5× multiplication in the cotton lineage of an ancestral genome common to cotton and cacao, and proposed evolutionary models to show how such a decaploid ancestor formed. The c. 70% gene loss necessary to bring the ancestral decaploid to its current gene count appears to fit an approximate geometrical model; that is, although many genes may be lost by single-gene deletion events, some may be lost in groups of consecutive genes. Gene loss following cotton decaploidy has largely just reduced gene copy numbers of some homologous groups. We designed a novel approach to deconvolute layers of chromosome homology, providing definitive information on gene orthology and paralogy across broad evolutionary distances, both of fundamental value and serving as an important platform to support further studies in and beyond cotton and genomics communities. No claim to original US government works. New Phytologist © 2015 New Phytologist Trust.

Broadband Studies of Semsmic Sources at Regional and Teleseismic Distances Using Advanced Time Series Analysis Methods. Volume 1.

DTIC Science & Technology

1991-03-21

discussion of spectral factorability and motivations for broadband analysis, the report is subdivided into four main sections. In Section 1.0, we...estimates. The motivation for developing our multi-channel deconvolution method was to gain information about seismic sources, most notably, nuclear...with complex constraints for estimating the rupture history. Such methods (applied mostly to data sets that also include strong rmotion data), were

Pulse analysis of acoustic emission signals. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Houghton, J. R.

1976-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio are examined in the frequency domain analysis, and pulse shape deconvolution is developed for use in the time domain analysis. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameters values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emissions associated with: (1) crack propagation, (2) ball dropping on a plate, (3) spark discharge and (4) defective and good ball bearings.

LES-Modeling of a Partially Premixed Flame using a Deconvolution Turbulence Closure

NASA Astrophysics Data System (ADS)

Wang, Qing; Wu, Hao; Ihme, Matthias

2015-11-01

The modeling of the turbulence/chemistry interaction in partially premixed and multi-stream combustion remains an outstanding issue. By extending a recently developed constrained minimum mean-square error deconvolution (CMMSED) method, to objective of this work is to develop a source-term closure for turbulent multi-stream combustion. In this method, the chemical source term is obtained from a three-stream flamelet model, and CMMSED is used as closure model, thereby eliminating the need for presumed PDF-modeling. The model is applied to LES of a piloted turbulent jet flame with inhomogeneous inlets, and simulation results are compared with experiments. Comparisons with presumed PDF-methods are performed, and issues regarding resolution and conservation of the CMMSED method are examined. The author would like to acknowledge the support of funding from Stanford Graduate Fellowship.

Image quality improvement in optical coherence tomography using Lucy-Richardson deconvolution algorithm.

PubMed

Hojjatoleslami, S A; Avanaki, M R N; Podoleanu, A Gh

2013-08-10

Optical coherence tomography (OCT) has the potential for skin tissue characterization due to its high axial and transverse resolution and its acceptable depth penetration. In practice, OCT cannot reach the theoretical resolutions due to imperfections of some of the components used. One way to improve the quality of the images is to estimate the point spread function (PSF) of the OCT system and deconvolve it from the output images. In this paper, we investigate the use of solid phantoms to estimate the PSF of the imaging system. We then utilize iterative Lucy-Richardson deconvolution algorithm to improve the quality of the images. The performance of the proposed algorithm is demonstrated on OCT images acquired from a variety of samples, such as epoxy-resin phantoms, fingertip skin and basaloid larynx and eyelid tissues.

Streaming Multiframe Deconvolutions on GPUs

NASA Astrophysics Data System (ADS)

Lee, M. A.; Budavári, T.

2015-09-01

Atmospheric turbulence distorts all ground-based observations, which is especially detrimental to faint detections. The point spread function (PSF) defining this blur is unknown for each exposure and varies significantly over time, making image analysis difficult. Lucky imaging and traditional co-adding throws away lots of information. We developed blind deconvolution algorithms that can simultaneously obtain robust solutions for the background image and all the PSFs. It is done in a streaming setting, which makes it practical for large number of big images. We implemented a new tool that runs of GPUs and achieves exceptional running times that can scale to the new time-domain surveys. Our code can quickly and effectively recover high-resolution images exceeding the quality of traditional co-adds. We demonstrate the power of the method on the repeated exposures in the Sloan Digital Sky Survey's Stripe 82.

Investigating the Capability to Extract Impulse Response Functions From Ambient Seismic Noise Using a Mine Collapse Event

NASA Astrophysics Data System (ADS)

Kwak, Sangmin; Song, Seok Goo; Kim, Geunyoung; Cho, Chang Soo; Shin, Jin Soo

2017-10-01

Using recordings of a mine collapse event (Mw 4.2) in South Korea in January 2015, we demonstrated that the phase and amplitude information of impulse response functions (IRFs) can be effectively retrieved using seismic interferometry. This event is equivalent to a single downward force at shallow depth. Using quantitative metrics, we compared three different seismic interferometry techniques—deconvolution, coherency, and cross correlation—to extract the IRFs between two distant stations with ambient seismic noise data. The azimuthal dependency of the source distribution of the ambient noise was also evaluated. We found that deconvolution is the best method for extracting IRFs from ambient seismic noise within the period band of 2-10 s. The coherency method is also effective if appropriate spectral normalization or whitening schemes are applied during the data processing.

The Mathematics of a Successful Deconvolution: A Quantitative Assessment of Mixture-Based Combinatorial Libraries Screened Against Two Formylpeptide Receptors

PubMed Central

Santos, Radleigh G.; Appel, Jon R.; Giulianotti, Marc A.; Edwards, Bruce S.; Sklar, Larry A.; Houghten, Richard A.; Pinilla, Clemencia

2014-01-01

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays. PMID:23722730

Deblurring of Class-Averaged Images in Single-Particle Electron Microscopy.

PubMed

Park, Wooram; Madden, Dean R; Rockmore, Daniel N; Chirikjian, Gregory S

2010-03-01

This paper proposes a method for deblurring of class-averaged images in single-particle electron microscopy (EM). Since EM images of biological samples are very noisy, the images which are nominally identical projection images are often grouped, aligned and averaged in order to cancel or reduce the background noise. However, the noise in the individual EM images generates errors in the alignment process, which creates an inherent limit on the accuracy of the resulting class averages. This inaccurate class average due to the alignment errors can be viewed as the result of a convolution of an underlying clear image with a blurring function. In this work, we develop a deconvolution method that gives an estimate for the underlying clear image from a blurred class-averaged image using precomputed statistics of misalignment. Since this convolution is over the group of rigid body motions of the plane, SE(2), we use the Fourier transform for SE(2) in order to convert the convolution into a matrix multiplication in the corresponding Fourier space. For practical implementation we use a Hermite-function-based image modeling technique, because Hermite expansions enable lossless Cartesian-polar coordinate conversion using the Laguerre-Fourier expansions, and Hermite expansion and Laguerre-Fourier expansion retain their structures under the Fourier transform. Based on these mathematical properties, we can obtain the deconvolution of the blurred class average using simple matrix multiplication. Tests of the proposed deconvolution method using synthetic and experimental EM images confirm the performance of our method.

A blind deconvolution method based on L1/L2 regularization prior in the gradient space

NASA Astrophysics Data System (ADS)

Cai, Ying; Shi, Yu; Hua, Xia

2018-02-01

In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.

Raman spectroscopy of oral tissues: correlation of spectral and biochemical markers

NASA Astrophysics Data System (ADS)

Singh, S. P.; Krishna, C. Murali

2014-03-01

Introduction Optical spectroscopic methods are being explored as novel tools for early and non-invasive cancer diagnosis. Both ex vivo and in vivo Raman spectroscopic studies carried out in oral cancer over the past decade have demonstrated that spectra of normal tissues are rich in lipids while tumor spectra show predominance of proteins. An accurate understanding of spectral features with respect to the biochemical composition is a pre-requisite before transferring these technologies for routine clinical usage. Therefore, in the present study, we have carried out Raman and biochemical studies on same tissues to correlate spectral markers and biochemical composition of normal and tumor oral tissues. Materials and Methods Spectra of 20 pairs of normal and tumor oral tissues were acquired using fiber-optic probe coupled HE-785 Raman spectrometer. Intensity associated with lipid (1440 cm-1) and protein (1450 and 1660 cm-1) bands were computed using curve-deconvolution method. Same tissues were then subjected to biochemical estimations of major biomolecules i.e., protein, lipid and phospholipids. Results and Discussion The intensity of the lipid band was found to be higher in normal tissues with respect to tumors, and the protein band was higher in tumors compared to normal tissues. Biochemical estimation yielded similar results i.e. high protein to lipid or phospholipid ratio in tumors with-respect to normal tissues. These differences were found to be statistically significant. Conclusion Findings of curve-deconvolution and biochemical estimation correlate very well and corroborate the spectral profile noted in earlier studies.

Three-dimensional imaging of nucleolin trafficking in normal cells, transfectants, and heterokaryons

NASA Astrophysics Data System (ADS)

Ballou, Byron T.; Fisher, Gregory W.; Deng, Jau-Shyong; Hakala, Thomas R.; Srivastava, Meera; Farkas, Daniel L.

1996-04-01

The study of intracellular trafficking using labeled molecules has been aided by the development of the cyanine fluorochromes, which are easily coupled, very soluble, resist photobleaching, and fluoresce at far-red wavelengths where background fluorescence is minimal. We have used Cy3-, Cy5-, and Cy5.5-labeled antibodies, antigen-binding fragments, and specifically binding single-stranded oligonucleotides to follow expression and trafficking of nucleolin, the most abundant protein of the nucleolus. Nucleolin shuttles between the nucleolus and the cytoplasm, and is also expressed on the cell surface, allowing us to test our techniques at all three cellular sites. Differentially cyanine-labeled non-specific antibodies were used to control for non-specific binding. Similarly, the differentially labeled non-binding strand of the cloned oligonucleotide served as a control. The multimode microscope allowed us to follow both rapid and slow redistributions of labeled ligands in the same study. We also performed 3-D reconstructions of nucleolin distribution in cells using rapid acquisition and deconvolution. Microinjection of labeled ligands was used to follow intracellular distribution, while incubation of whole cells with antibody and antigen-binding fragments was used to study uptake. To unambiguously define trafficking, and eliminate the possibility of interference by cross-reactive proteins, we transfected mouse renal cell carcinoma cells that express cell surface nucleolin with human nucleolin. We used microinjection and cell surface staining with Cy3- or Cy5- labeled monoclonal antibody D3 (specific for human nucleolin) to assess the cellular distribution of the human protein. Several clones expressed human nucleolin on their surfaces and showed high levels of transport of the human protein into the mouse nucleus and nucleolus. This distribution roughly parallels that of mouse nucleolin as determined by labeled polyclonal antibody. We have used these engineered transfectants to determine whether the cell surface-expressed xenogeneic nucleolin can serve as a target for antibodies in vivo.

Three Channel Polarimetric Based Data Deconvolution

DTIC Science & Technology

2011-03-01

which have been degraded by atmospheric turbulence and noise . This thesis explains in entirety the process used for deblurring and de- noising images...10 3.1.2 Noise Model...Blur and Noise .............................................................................................................. 34 5.3 Laboratory Results

NREL Scientist Maria Ghirardi Named AAAS Fellow | News | NREL

Science.gov Websites

extreme sensitivity of the hydrogenase enzyme to oxygen, one of the byproducts of photosynthesis. Ghirardi pathways in photosynthesis, and in deconvoluting the metabolic partners of a crucial redox enzyme

Data consistency-driven scatter kernel optimization for x-ray cone-beam CT

NASA Astrophysics Data System (ADS)

Kim, Changhwan; Park, Miran; Sung, Younghun; Lee, Jaehak; Choi, Jiyoung; Cho, Seungryong

2015-08-01

Accurate and efficient scatter correction is essential for acquisition of high-quality x-ray cone-beam CT (CBCT) images for various applications. This study was conducted to demonstrate the feasibility of using the data consistency condition (DCC) as a criterion for scatter kernel optimization in scatter deconvolution methods in CBCT. As in CBCT, data consistency in the mid-plane is primarily challenged by scatter, we utilized data consistency to confirm the degree of scatter correction and to steer the update in iterative kernel optimization. By means of the parallel-beam DCC via fan-parallel rebinning, we iteratively optimized the scatter kernel parameters, using a particle swarm optimization algorithm for its computational efficiency and excellent convergence. The proposed method was validated by a simulation study using the XCAT numerical phantom and also by experimental studies using the ACS head phantom and the pelvic part of the Rando phantom. The results showed that the proposed method can effectively improve the accuracy of deconvolution-based scatter correction. Quantitative assessments of image quality parameters such as contrast and structure similarity (SSIM) revealed that the optimally selected scatter kernel improves the contrast of scatter-free images by up to 99.5%, 94.4%, and 84.4%, and of the SSIM in an XCAT study, an ACS head phantom study, and a pelvis phantom study by up to 96.7%, 90.5%, and 87.8%, respectively. The proposed method can achieve accurate and efficient scatter correction from a single cone-beam scan without need of any auxiliary hardware or additional experimentation.

Archaeometric Prospection Using Electrical Survey Predictive Deconvolution (ESPD)

NASA Astrophysics Data System (ADS)

Glover, P. W.

2009-05-01

Once upon a time archaeological prospection was carried out mainly using electrical techniques. These days magnetic techniques and GPR are used by preference. However, we have shown that electrical surveying combined with the technique of predictive deconvolution is very effective at finding buried features where the shape of the feature can be predicted in advance. One such type of feature is the Grubenhaus (or sunken-featured, sunken-floored building, or SFB). Grubenhaüser exist in the archaeological record as individual well-defined oblong pits that have been filled and buried with other material. Aerial photographs at New Bewick in Northumberland, northern England (UK Grid reference NU061206) showed quasi-rectangular features similar to those on aerial photographs at the nearby Anglo-Saxon palace of Milfield (NT941339) which had been confirmed by excavation to be Grubenhaüser. Several electrical resistivity surveys were carried out over the area with an ABEM Mk II Terrameter and a multiplexing box serving 31 electrodes in line at any given time. Both double-dipole and Wenner configurations were used with an electrode spacing of 1 m. Data was acquired in blocks of 30 m by 30 m during a period of dry summer weather while the field was under young winter wheat. The Wenner array produces a characteristic 'M' or 'W' shaped response over filled in excavations such as those expected to represent a Grubenhaus. While this seems a disadvantage in the first instance, it can be used to improve the data. Such anomalies were present in the raw New Bewick data. The resulting data were analysed using 1D and 2D predictive deconvolution in order to remove the Wenner response. The deconvolution was carried out using an inverse matrix element method. The filtered results indicated the presence of an anomaly that is consistent with a Grubenhaus measuring about 5 m by 4 m and with a pit depth of 0.6 m below 0.5 m of topsoil. The results also showed broader areas of increased resistivity which have been attributed to compaction resulting from human and animal movement. Following the geophysical study the site was excavated (T. Gates and C. O'Brien "Cropmarks at Milfield and New Bewick and the Recognition of Grubenhaüser in Northumberland." Archaeologia Aeliana 5th series, Vol XVI, 1988, 1-9) and a Grubenhaus was discovered at the site. The excavated Grubenhaus measured 4.7 m by 3.9 m with a pit depth of 0.5 m below the base of the topsoil. The deconvolved Wenner data performed better than the double-dipole resistivity survey but was marginally slower.

Enhancing the accuracy of subcutaneous glucose sensors: a real-time deconvolution-based approach.

PubMed

Guerra, Stefania; Facchinetti, Andrea; Sparacino, Giovanni; Nicolao, Giuseppe De; Cobelli, Claudio

2012-06-01

Minimally invasive continuous glucose monitoring (CGM) sensors can greatly help diabetes management. Most of these sensors consist of a needle electrode, placed in the subcutaneous tissue, which measures an electrical current exploiting the glucose-oxidase principle. This current is then transformed to glucose levels after calibrating the sensor on the basis of one, or more, self-monitoring blood glucose (SMBG) samples. In this study, we design and test a real-time signal-enhancement module that, cascaded to the CGM device, improves the quality of its output by a proper postprocessing of the CGM signal. In fact, CGM sensors measure glucose in the interstitium rather than in the blood compartment. We show that this distortion can be compensated by means of a regularized deconvolution procedure relying on a linear regression model that can be updated whenever a pair of suitably sampled SMBG references is collected. Tests performed both on simulated and real data demonstrate a significant accuracy improvement of the CGM signal. Simulation studies also demonstrate the robustness of the method against departures from nominal conditions, such as temporal misplacement of the SMBG samples and uncertainty in the blood-to-interstitium glucose kinetic model. Thanks to its online capabilities, the proposed signal-enhancement algorithm can be used to improve the performance of CGM-based real-time systems such as the hypo/hyper glycemic alert generators or the artificial pancreas.

1H NMR Metabolomics Study of Spleen from C57BL/6 Mice Exposed to Gamma Radiation

PubMed Central

Xiao, X; Hu, M; Liu, M; Hu, JZ

2016-01-01

Due to the potential risk of accidental exposure to gamma radiation, it’s critical to identify the biomarkers of radiation exposed creatures. In the present study, NMR based metabolomics combined with multivariate data analysis to evaluate the metabolites changed in the C57BL/6 mouse spleen after 4 days whole body exposure to 3.0 Gy and 7.8 Gy gamma radiations. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification potential biomarkers associated with gamma irradiation. Two different strategies for NMR spectral data reduction (i.e., spectral binning and spectral deconvolution) are combined with normalize to constant sum and unit weight before multivariate data analysis, respectively. The combination of spectral deconvolution and normalization to unit weight is the best way for identifying discriminatory metabolites between the irradiation and control groups. Normalized to the constant sum may achieve some pseudo biomarkers. PCA and OPLS results shown that the exposed groups can be well separated from the control group. Leucine, 2-aminobutyrate, valine, lactate, arginine, glutathione, 2-oxoglutarate, creatine, tyrosine, phenylalanine, π-methylhistidine, taurine, myoinositol, glycerol and uracil are significantly elevated while ADP is decreased significantly. These significantly changed metabolites are associated with multiple metabolic pathways and may be potential biomarkers in the spleen exposed to gamma irradiation. PMID:27019763

Development and use of Fourier self deconvolution and curve-fitting in the study of coal oxidation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, J.A.

1986-01-01

Techniques have been developed for modeling highly overlapped band multiplets. The method is based on a least-squares fit of spectra by a series of bands of known shape. Using synthetic spectra, it was shown that when bands are separated by less than their full width at half height (FWHH), valid analytical data can only be obtained after the width of each component band is narrowed by Fourier self deconvolution (FSD). The optimum method of spectral fitting determined from the study of synthetic spectra was then applied to the characterization of oxidized coals. A medium volatile bituminous coal which was airmore » oxidized at 200/sup 0/C for different lengths of time, was extracted with chloroform. A comparison of the infrared spectra of the whole coal and the extract indicated that the extracted material contains a smaller amount of carbonyl, ether, and ester groups, while the aromatic content is much higher. Oxidation does not significantly affect the aromatic content of the whole cola. Most of the aromatic groups in the CHCl/sub 3/ extract show evidence of reaction, however. The production of relatively large amounts of intramolecular aromatic anhydrides is seen in the spectrum of the extract of coals which have undergone extensive oxidation,while there is only a slight indication of this anhydride in the whole coal.« less

New metric for optimizing Continuous Loop Averaging Deconvolution (CLAD) sequences under the 1/f noise model

PubMed Central

Peng, Xian; Yuan, Han; Chen, Wufan; Ding, Lei

2017-01-01

Continuous loop averaging deconvolution (CLAD) is one of the proven methods for recovering transient auditory evoked potentials (AEPs) in rapid stimulation paradigms, which requires an elaborated stimulus sequence design to attenuate impacts from noise in data. The present study aimed to develop a new metric in gauging a CLAD sequence in terms of noise gain factor (NGF), which has been proposed previously but with less effectiveness in the presence of pink (1/f) noise. We derived the new metric by explicitly introducing the 1/f model into the proposed time-continuous sequence. We selected several representative CLAD sequences to test their noise property on typical EEG recordings, as well as on five real CLAD electroencephalogram (EEG) recordings to retrieve the middle latency responses. We also demonstrated the merit of the new metric in generating and quantifying optimized sequences using a classic genetic algorithm. The new metric shows evident improvements in measuring actual noise gains at different frequencies, and better performance than the original NGF in various aspects. The new metric is a generalized NGF measurement that can better quantify the performance of a CLAD sequence, and provide a more efficient mean of generating CLAD sequences via the incorporation with optimization algorithms. The present study can facilitate the specific application of CLAD paradigm with desired sequences in the clinic. PMID:28414803

Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study.

PubMed

Rojkova, K; Volle, E; Urbanski, M; Humbert, F; Dell'Acqua, F; Thiebaut de Schotten, M

2016-04-01

In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22-71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.

1H NMR metabolomics study of spleen from C57BL/6 mice exposed to gamma radiation

DOE PAGES

Xiao, Xiongjie; Hu, M.; Liu, M.; ...

2016-01-27

Due to the potential risk of accidental exposure to gamma radiation, it’s critical to identify the biomarkers of radiation exposed creatures. In the present study, NMR based metabolomics combined with multivariate data analysis to evaluate the metabolites changed in the C57BL/6 mouse spleen after 4 days whole body exposure to 3.0 Gy and 7.8 Gy gamma radiations. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification potential biomarkers associated with gamma irradiation. Two different strategies for NMR spectral data reduction (i.e., spectral binning and spectral deconvolution) are combined with normalize tomore » constant sum and unit weight before multivariate data analysis, respectively. The combination of spectral deconvolution and normalization to unit weight is the best way for identifying discriminatory metabolites between the irradiation and control groups. Normalized to the constant sum may achieve some pseudo biomarkers. PCA and OPLS results shown that the exposed groups can be well separated from the control group. Leucine, 2-aminobutyrate, valine, lactate, arginine, glutathione, 2-oxoglutarate, creatine, tyrosine, phenylalanine, π-methylhistidine, taurine, myoinositol, glycerol and uracil are significantly elevated while ADP is decreased significantly. As a result, these significantly changed metabolites are associated with multiple metabolic pathways and may be potential biomarkers in the spleen exposed to gamma irradiation.« less

In vitro and in vivo evaluation of gastro-retentive carvedilol loaded chitosan beads using Gastroplus™.

PubMed

Praveen, Radhakrishnan; Prasad Verma, Priya Ranjan; Venkatesan, Jayachandran; Yoon, Dong-Han; Kim, Se-Kwon; Singh, Sandeep Kumar

2017-09-01

The objective of present investigation was to develop gastro-retentive controlled release system of carvedilol using biological macromolecule, chitosan. 3 2 full factorial design was adopted for optimization of tripolyphosphate (X 1 ) and curing time (X 2 ). Bead stability in 0.1N HCl, buoyancy duration, density, drug loading, dissolution efficiency and cumulative percentage release at 8th hour were evaluated as dependent variables. The levels of X 1 and X 2 of optimized formulation having maximum desirability was found to 2.0% w/v and 62.66min, respectively. The in silico predicted responses and observed response were found to be in good agreement (percent bias error: -13.295 to +13.269). SEM images showed numerous pores in the cross sectional image that renders buoyancy. AUC 0-∞ of optimized formulation was 1.47 times higher as compared to suspension corroborating enhanced extent of absorption. T max and mean residence time were significantly higher from optimized formulation vis a vis suspension. In silico study indicated maximum regional absorption from the duodenum (94.1%) followed by jejunum (5.6%). Wagner-Nelson and Loo-Reigelman method were the preferred deconvolution approach over numerical deconvolution to establish IVIVC. In conclusion, the study showed that gastro-retentive controlled release system prepared using chitosan could be a potential drug carrier of carvedilol with improved bioavailability. Copyright © 2017 Elsevier B.V. All rights reserved.

Iterative-Transform Phase Diversity: An Object and Wavefront Recovery Algorithm

NASA Technical Reports Server (NTRS)

Smith, J. Scott

2011-01-01

Presented is a solution for recovering the wavefront and an extended object. It builds upon the VSM architecture and deconvolution algorithms. Simulations are shown for recovering the wavefront and extended object from noisy data.

Improving the blind restoration of retinal images by means of point-spread-function estimation assessment

NASA Astrophysics Data System (ADS)

Marrugo, Andrés. G.; Millán, María. S.; Å orel, Michal; Kotera, Jan; Å roubek, Filip

2015-01-01

Retinal images often suffer from blurring which hinders disease diagnosis and progression assessment. The restoration of the images is carried out by means of blind deconvolution, but the success of the restoration depends on the correct estimation of the point-spread-function (PSF) that blurred the image. The restoration can be space-invariant or space-variant. Because a retinal image has regions without texture or sharp edges, the blind PSF estimation may fail. In this paper we propose a strategy for the correct assessment of PSF estimation in retinal images for restoration by means of space-invariant or space-invariant blind deconvolution. Our method is based on a decomposition in Zernike coefficients of the estimated PSFs to identify valid PSFs. This significantly improves the quality of the image restoration revealed by the increased visibility of small details like small blood vessels and by the lack of restoration artifacts.

Application of constrained deconvolution technique for reconstruction of electron bunch profile with strongly non-Gaussian shape

NASA Astrophysics Data System (ADS)

Geloni, G.; Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

2004-08-01

An effective and practical technique based on the detection of the coherent synchrotron radiation (CSR) spectrum can be used to characterize the profile function of ultra-short bunches. The CSR spectrum measurement has an important limitation: no spectral phase information is available, and the complete profile function cannot be obtained in general. In this paper we propose to use constrained deconvolution method for bunch profile reconstruction based on a priori-known information about formation of the electron bunch. Application of the method is illustrated with practically important example of a bunch formed in a single bunch-compressor. Downstream of the bunch compressor the bunch charge distribution is strongly non-Gaussian with a narrow leading peak and a long tail. The longitudinal bunch distribution is derived by measuring the bunch tail constant with a streak camera and by using a priory available information about profile function.

Denoised Wigner distribution deconvolution via low-rank matrix completion

DOE PAGES

Lee, Justin; Barbastathis, George

2016-08-23

Wigner distribution deconvolution (WDD) is a decades-old method for recovering phase from intensity measurements. Although the technique offers an elegant linear solution to the quadratic phase retrieval problem, it has seen limited adoption due to its high computational/memory requirements and the fact that the technique often exhibits high noise sensitivity. Here, we propose a method for noise suppression in WDD via low-rank noisy matrix completion. Our technique exploits the redundancy of an object’s phase space to denoise its WDD reconstruction. We show in model calculations that our technique outperforms other WDD algorithms as well as modern iterative methods for phasemore » retrieval such as ptychography. Here, our results suggest that a class of phase retrieval techniques relying on regularized direct inversion of ptychographic datasets (instead of iterative reconstruction techniques) can provide accurate quantitative phase information in the presence of high levels of noise.« less

Denoised Wigner distribution deconvolution via low-rank matrix completion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Justin; Barbastathis, George

Wigner distribution deconvolution (WDD) is a decades-old method for recovering phase from intensity measurements. Although the technique offers an elegant linear solution to the quadratic phase retrieval problem, it has seen limited adoption due to its high computational/memory requirements and the fact that the technique often exhibits high noise sensitivity. Here, we propose a method for noise suppression in WDD via low-rank noisy matrix completion. Our technique exploits the redundancy of an object’s phase space to denoise its WDD reconstruction. We show in model calculations that our technique outperforms other WDD algorithms as well as modern iterative methods for phasemore » retrieval such as ptychography. Here, our results suggest that a class of phase retrieval techniques relying on regularized direct inversion of ptychographic datasets (instead of iterative reconstruction techniques) can provide accurate quantitative phase information in the presence of high levels of noise.« less

1975 Memorial Award Paper. Image generation and display techniques for CT scan data. Thin transverse and reconstructed coronal and sagittal planes.

PubMed

Glenn, W V; Johnston, R J; Morton, P E; Dwyer, S J

1975-01-01

The various limitations to computerized axial tomographic (CT) interpretation are due in part to the 8-13 mm standard tissue plane thickness and in part to the absence of alternative planes of view, such as coronal or sagittal images. This paper describes a method for gathering multiple overlapped 8 mm transverse sections, subjecting these data to a deconvolution process, and then displaying thin (1 mm) transverse as well as reconstructed coronal and sagittal CT images. Verification of the deconvolution technique with phantom experiments is described. Application of the phantom results to human post mortem CT scan data illustrates this method's faithful reconstruction of coronal and sagittal tissue densities when correlated with actual specimen photographs of a sectioned brain. A special CT procedure, limited basal overlap scanning, is proposed for use on current first generation CT scanners without hardware modification.

Evidence for radical anion formation during liquid secondary ion mass spectrometry analysis of oligonucleotides and synthetic oligomeric analogues: a deconvolution algorithm for molecular ion region clusters.

PubMed

Laramée, J A; Arbogast, B; Deinzer, M L

1989-10-01

It is shown that one-electron reduction is a common process that occurs in negative ion liquid secondary ion mass spectrometry (LSIMS) of oligonucleotides and synthetic oligonucleosides and that this process is in competition with proton loss. Deconvolution of the molecular anion cluster reveals contributions from (M-2H).-, (M-H)-, M.-, and (M + H)-. A model based on these ionic species gives excellent agreement with the experimental data. A correlation between the concentration of species arising via one-electron reduction [M.- and (M + H)-] and the electron affinity of the matrix has been demonstrated. The relative intensity of M.- is mass-dependent; this is rationalized on the basis of base-stacking. Base sequence ion formation is theorized to arise from M.- radical anion among other possible pathways.

Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data

PubMed Central

Pnevmatikakis, Eftychios A.; Soudry, Daniel; Gao, Yuanjun; Machado, Timothy A.; Merel, Josh; Pfau, David; Reardon, Thomas; Mu, Yu; Lacefield, Clay; Yang, Weijian; Ahrens, Misha; Bruno, Randy; Jessell, Thomas M.; Peterka, Darcy S.; Yuste, Rafael; Paninski, Liam

2016-01-01

SUMMARY We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multineuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data. PMID:26774160

Constrained maximum consistency multi-path mitigation

NASA Astrophysics Data System (ADS)

Smith, George B.

2003-10-01

Blind deconvolution algorithms can be useful as pre-processors for signal classification algorithms in shallow water. These algorithms remove the distortion of the signal caused by multipath propagation when no knowledge of the environment is available. A framework in which filters that produce signal estimates from each data channel that are as consistent with each other as possible in a least-squares sense has been presented [Smith, J. Acoust. Soc. Am. 107 (2000)]. This framework provides a solution to the blind deconvolution problem. One implementation of this framework yields the cross-relation on which EVAM [Gurelli and Nikias, IEEE Trans. Signal Process. 43 (1995)] and Rietsch [Rietsch, Geophysics 62(6) (1997)] processing are based. In this presentation, partially blind implementations that have good noise stability properties are compared using Classification Operating Characteristics (CLOC) analysis. [Work supported by ONR under Program Element 62747N and NRL, Stennis Space Center, MS.

Bayesian least squares deconvolution

NASA Astrophysics Data System (ADS)

Asensio Ramos, A.; Petit, P.

2015-11-01

Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.

Determination of element affinities by density fractionation of bulk coal samples

USGS Publications Warehouse

Querol, X.; Klika, Z.; Weiss, Z.; Finkelman, R.B.; Alastuey, A.; Juan, R.; Lopez-Soler, A.; Plana, F.; Kolker, A.; Chenery, S.R.N.

2001-01-01

A review has been made of the various methods of determining major and trace element affinities for different phases, both mineral and organic in coals, citing their various strengths and weaknesses. These include mathematical deconvolution of chemical analyses, direct microanalysis, sequential extraction procedures and density fractionation. A new methodology combining density fractionation with mathematical deconvolution of chemical analyses of whole coals and their density fractions has been evaluated. These coals formed part of the IEA-Coal Research project on the Modes of Occurrence of Trace Elements in Coal. Results were compared to a previously reported sequential extraction methodology and showed good agreement for most elements. For particular elements (Be, Mo, Cu, Se and REEs) in specific coals where disagreement was found, it was concluded that the occurrence of rare trace element bearing phases may account for the discrepancy, and modifications to the general procedure must be made to account for these.

Further optimization of SeDDaRA blind image deconvolution algorithm and its DSP implementation

NASA Astrophysics Data System (ADS)

Wen, Bo; Zhang, Qiheng; Zhang, Jianlin

2011-11-01

Efficient algorithm for blind image deconvolution and its high-speed implementation is of great value in practice. Further optimization of SeDDaRA is developed, from algorithm structure to numerical calculation methods. The main optimization covers that, the structure's modularization for good implementation feasibility, reducing the data computation and dependency of 2D-FFT/IFFT, and acceleration of power operation by segmented look-up table. Then the Fast SeDDaRA is proposed and specialized for low complexity. As the final implementation, a hardware system of image restoration is conducted by using the multi-DSP parallel processing. Experimental results show that, the processing time and memory demand of Fast SeDDaRA decreases 50% at least; the data throughput of image restoration system is over 7.8Msps. The optimization is proved efficient and feasible, and the Fast SeDDaRA is able to support the real-time application.

Correspondence regarding Zhong et al., BMC Bioinformatics 2013 Mar 7;14:89.

PubMed

Kuhn, Alexandre

2014-11-28

Computational expression deconvolution aims to estimate the contribution of individual cell populations to expression profiles measured in samples of heterogeneous composition. Zhong et al. recently proposed Digital Sorting Algorithm (BMC Bioinformatics 2013 Mar 7;14:89) and showed that they could accurately estimate population-specific expression levels and expression differences between two populations. They compared DSA with Population-Specific Expression Analysis (PSEA), a previous deconvolution method that we developed to detect expression changes occurring within the same population between two conditions (e.g. disease versus non-disease). However, Zhong et al. compared PSEA-derived specific expression levels across different cell populations. Specific expression levels obtained with PSEA cannot be directly compared across different populations as they are on a relative scale. They are accurate as we demonstrate by deconvolving the same dataset used by Zhong et al. and, importantly, allow for comparison of population-specific expression across conditions.

Simulation and analysis on ultrasonic testing for the cement grouting defects of the corrugated pipe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qingbang, Han; Ling, Chen; Changping, Zhu

2014-02-18

The defects exist in the cement grouting process of prestressed corrugated pipe may directly impair the bridge safety. In this paper, sound fields propagation in concrete structures with corrugated pipes and the influence of various different defects are simulated and analyzed using finite element method. The simulation results demonstrate a much complex propagation characteristic due to multiple reflection, refraction and scattering, where the scattering signals caused by metal are very strong, while the signals scattered by an air bubble are weaker. The influence of defect both in time and frequency domain are found through deconvolution treatment. In the time domain,more » the deconvolution signals correspond to larger defect display a larger head wave amplitude and shorter arrive time than those of smaller defects; in the frequency domain, larger defect also shows a stronger amplitude, lower center frequency and lower cutoff frequency.« less

ESO/ST-ECF Data Analysis Workshop, 5th, Garching, Germany, Apr. 26, 27, 1993, Proceedings

NASA Astrophysics Data System (ADS)

Grosbol, Preben; de Ruijsscher, Resy

1993-01-01

Various papers on astronomical data analysis are presented. Individual optics addressed include: surface photometry of early-type galaxies, wavelet transform and adaptive filtering, package for surface photometry of galaxies, calibration of large-field mosaics, surface photometry of galaxies with HST, wavefront-supported image deconvolution, seeing effects on elliptical galaxies, multiple algorithms deconvolution program, enhancement of Skylab X-ray images, MIDAS procedures for the image analysis of E-S0 galaxies, photometric data reductions under MIDAS, crowded field photometry with deconvolved images, the DENIS Deep Near Infrared Survey. Also discussed are: analysis of astronomical time series, detection of low-amplitude stellar pulsations, new SOT method for frequency analysis, chaotic attractor reconstruction and applications to variable stars, reconstructing a 1D signal from irregular samples, automatic analysis for time series with large gaps, prospects for content-based image retrieval, redshift survey in the South Galactic Pole Region.

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics.

PubMed

Peckner, Ryan; Myers, Samuel A; Jacome, Alvaro Sebastian Vaca; Egertson, Jarrett D; Abelin, Jennifer G; MacCoss, Michael J; Carr, Steven A; Jaffe, Jacob D

2018-05-01

Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

Blind channel estimation and deconvolution in colored noise using higher-order cumulants

NASA Astrophysics Data System (ADS)

Tugnait, Jitendra K.; Gummadavelli, Uma

1994-10-01

Existing approaches to blind channel estimation and deconvolution (equalization) focus exclusively on channel or inverse-channel impulse response estimation. It is well-known that the quality of the deconvolved output depends crucially upon the noise statistics also. Typically it is assumed that the noise is white and the signal-to-noise ratio is known. In this paper we remove these restrictions. Both the channel impulse response and the noise model are estimated from the higher-order (fourth, e.g.) cumulant function and the (second-order) correlation function of the received data via a least-squares cumulant/correlation matching criterion. It is assumed that the noise higher-order cumulant function vanishes (e.g., Gaussian noise, as is the case for digital communications). Consistency of the proposed approach is established under certain mild sufficient conditions. The approach is illustrated via simulation examples involving blind equalization of digital communications signals.

Ultrafast Method for the Analysis of Fluorescence Lifetime Imaging Microscopy Data Based on the Laguerre Expansion Technique

PubMed Central

Jo, Javier A.; Fang, Qiyin; Marcu, Laura

2007-01-01

We report a new deconvolution method for fluorescence lifetime imaging microscopy (FLIM) based on the Laguerre expansion technique. The performance of this method was tested on synthetic and real FLIM images. The following interesting properties of this technique were demonstrated. 1) The fluorescence intensity decay can be estimated simultaneously for all pixels, without a priori assumption of the decay functional form. 2) The computation speed is extremely fast, performing at least two orders of magnitude faster than current algorithms. 3) The estimated maps of Laguerre expansion coefficients provide a new domain for representing FLIM information. 4) The number of images required for the analysis is relatively small, allowing reduction of the acquisition time. These findings indicate that the developed Laguerre expansion technique for FLIM analysis represents a robust and extremely fast deconvolution method that enables practical applications of FLIM in medicine, biology, biochemistry, and chemistry. PMID:19444338

Software-based measurement of thin filament lengths: an open-source GUI for Distributed Deconvolution analysis of fluorescence images

PubMed Central

Gokhin, David S.; Fowler, Velia M.

2016-01-01

The periodically arranged thin filaments within the striated myofibrils of skeletal and cardiac muscle have precisely regulated lengths, which can change in response to developmental adaptations, pathophysiological states, and genetic perturbations. We have developed a user-friendly, open-source ImageJ plugin that provides a graphical user interface (GUI) for super-resolution measurement of thin filament lengths by applying Distributed Deconvolution (DDecon) analysis to periodic line scans collected from fluorescence images. In the workflow presented here, we demonstrate thin filament length measurement using a phalloidin-stained cryosection of mouse skeletal muscle. The DDecon plugin is also capable of measuring distances of any periodically localized fluorescent signal from the Z- or M-line, as well as distances between successive Z- or M-lines, providing a broadly applicable tool for quantitative analysis of muscle cytoarchitecture. These functionalities can also be used to analyze periodic fluorescence signals in nonmuscle cells. PMID:27644080

Holographic fluorescence microscopy with incoherent digital holographic adaptive optics

NASA Astrophysics Data System (ADS)

Jang, Changwon; Kim, Jonghyun; Clark, David C.; Lee, Seungjae; Lee, Byoungho; Kim, Myung K.

2015-11-01

Introduction of adaptive optics technology into astronomy and ophthalmology has made great contributions in these fields, allowing one to recover images blurred by atmospheric turbulence or aberrations of the eye. Similar adaptive optics improvement in microscopic imaging is also of interest to researchers using various techniques. Current technology of adaptive optics typically contains three key elements: a wavefront sensor, wavefront corrector, and controller. These hardware elements tend to be bulky, expensive, and limited in resolution, involving, for example, lenslet arrays for sensing or multiactuator deformable mirrors for correcting. We have previously introduced an alternate approach based on unique capabilities of digital holography, namely direct access to the phase profile of an optical field and the ability to numerically manipulate the phase profile. We have also demonstrated that direct access and compensation of the phase profile are possible not only with conventional coherent digital holography, but also with a new type of digital holography using incoherent light: self­interference incoherent digital holography (SIDH). The SIDH generates a complex-i.e., amplitude plus phase-hologram from one or several interferograms acquired with incoherent light, such as LEDs, lamps, sunlight, or fluorescence. The complex point spread function can be measured using guide star illumination and it allows deterministic deconvolution of the full-field image. We present experimental demonstration of aberration compensation in holographic fluorescence microscopy using SIDH. Adaptive optics by SIDH provides new tools for improved cellular fluorescence microscopy through intact tissue layers or other types of aberrant media.

Holographic fluorescence microscopy with incoherent digital holographic adaptive optics

NASA Astrophysics Data System (ADS)

Jang, Changwon; Kim, Jonghyun; Clark, David C.; Lee, Byoungho; Kim, Myung K.

2015-03-01

Introduction of adaptive optics technology into astronomy and ophthalmology has made great contributions in these fields, allowing one to recover images blurred by atmospheric turbulence or aberrations of the eye. Similar adaptive optics improvement in microscopic imaging is also of interest to researchers using various techniques. Current technology of adaptive optics typically contains three key elements: wavefront sensor, wavefront corrector and controller. These hardware elements tend to be bulky, expensive, and limited in resolution, involving, e.g., lenslet arrays for sensing or multi-acuator deformable mirrors for correcting. We have previously introduced an alternate approach to adaptive optics based on unique capabilities of digital holography, namely direct access to the phase profile of an optical field and the ability to numerically manipulate the phase profile. We have also demonstrated that direct access and compensation of the phase profile is possible not only with the conventional coherent type of digital holography, but also with a new type of digital holography using incoherent light: self-interference incoherent digital holography (SIDH). The SIDH generates complex - i.e. amplitude plus phase - hologram from one or several interferograms acquired with incoherent light, such as LEDs, lamps, sunlight, or fluorescence. The complex point spread function can be measured using a guide star illumination and it allows deterministic deconvolution of the full-field image. We present experimental demonstration of aberration compensation in holographic fluorescence microscopy using SIDH. The adaptive optics by SIDH provides new tools for improved cellular fluorescence microscopy through intact tissue layers or other types of aberrant media.

Wide-field Fourier ptychographic microscopy using laser illumination source

PubMed Central

Chung, Jaebum; Lu, Hangwen; Ou, Xiaoze; Zhou, Haojiang; Yang, Changhuei

2016-01-01

Fourier ptychographic (FP) microscopy is a coherent imaging method that can synthesize an image with a higher bandwidth using multiple low-bandwidth images captured at different spatial frequency regions. The method’s demand for multiple images drives the need for a brighter illumination scheme and a high-frame-rate camera for a faster acquisition. We report the use of a guided laser beam as an illumination source for an FP microscope. It uses a mirror array and a 2-dimensional scanning Galvo mirror system to provide a sample with plane-wave illuminations at diverse incidence angles. The use of a laser presents speckles in the image capturing process due to reflections between glass surfaces in the system. They appear as slowly varying background fluctuations in the final reconstructed image. We are able to mitigate these artifacts by including a phase image obtained by differential phase contrast (DPC) deconvolution in the FP algorithm. We use a 1-Watt laser configured to provide a collimated beam with 150 mW of power and beam diameter of 1 cm to allow for the total capturing time of 0.96 seconds for 96 raw FPM input images in our system, with the camera sensor’s frame rate being the bottleneck for speed. We demonstrate a factor of 4 resolution improvement using a 0.1 NA objective lens over the full camera field-of-view of 2.7 mm by 1.5 mm. PMID:27896016

Holographic fluorescence microscopy with incoherent digital holographic adaptive optics.

PubMed

Jang, Changwon; Kim, Jonghyun; Clark, David C; Lee, Seungjae; Lee, Byoungho; Kim, Myung K

2015-01-01

Introduction of adaptive optics technology into astronomy and ophthalmology has made great contributions in these fields, allowing one to recover images blurred by atmospheric turbulence or aberrations of the eye. Similar adaptive optics improvement in microscopic imaging is also of interest to researchers using various techniques. Current technology of adaptive optics typically contains three key elements: a wavefront sensor, wavefront corrector, and controller. These hardware elements tend to be bulky, expensive, and limited in resolution, involving, for example, lenslet arrays for sensing or multiactuator deformable mirrors for correcting. We have previously introduced an alternate approach based on unique capabilities of digital holography, namely direct access to the phase profile of an optical field and the ability to numerically manipulate the phase profile. We have also demonstrated that direct access and compensation of the phase profile are possible not only with conventional coherent digital holography, but also with a new type of digital holography using incoherent light: selfinterference incoherent digital holography (SIDH). The SIDH generates a complex—i.e., amplitude plus phase—hologram from one or several interferograms acquired with incoherent light, such as LEDs, lamps, sunlight, or fluorescence. The complex point spread function can be measured using guide star illumination and it allows deterministic deconvolution of the full-field image. We present experimental demonstration of aberration compensation in holographic fluorescence microscopy using SIDH. Adaptive optics by SIDH provides new tools for improved cellular fluorescence microscopy through intact tissue layers or other types of aberrant media.

Determining mineralogical variations of aeolian deposits using thermal infrared emissivity and linear deconvolution methods

USGS Publications Warehouse

Hubbard, Bernard E.; Hooper, Donald M.; Solano, Federico; Mars, John C.

2018-01-01

We apply linear deconvolution methods to derive mineral and glass proportions for eight field sample training sites at seven dune fields: (1) Algodones, California; (2) Big Dune, Nevada; (3) Bruneau, Idaho; (4) Great Kobuk Sand Dunes, Alaska; (5) Great Sand Dunes National Park and Preserve, Colorado; (6) Sunset Crater, Arizona; and (7) White Sands National Monument, New Mexico. These dune fields were chosen because they represent a wide range of mineral grain mixtures and allow us to gauge a better understanding of both compositional and sorting effects within terrestrial and extraterrestrial dune systems. We also use actual ASTER TIR emissivity imagery to map the spatial distribution of these minerals throughout the seven dune fields and evaluate the effects of degraded spectral resolution on the accuracy of mineral abundances retrieved. Our results show that hyperspectral data convolutions of our laboratory emissivity spectra outperformed multispectral data convolutions of the same data with respect to the mineral, glass and lithic abundances derived. Both the number and wavelength position of spectral bands greatly impacts the accuracy of linear deconvolution retrieval of feldspar proportions (e.g. K-feldspar vs. plagioclase) especially, as well as the detection of certain mafic and carbonate minerals. In particular, ASTER mapping results show that several of the dune sites display patterns such that less dense minerals typically have higher abundances near the center of the active and most evolved dunes in the field, while more dense minerals and glasses appear to be more abundant along the margins of the active dune fields.

Non-stationary blind deconvolution of medical ultrasound scans

NASA Astrophysics Data System (ADS)

Michailovich, Oleg V.

2017-03-01

In linear approximation, the formation of a radio-frequency (RF) ultrasound image can be described based on a standard convolution model in which the image is obtained as a result of convolution of the point spread function (PSF) of the ultrasound scanner in use with a tissue reflectivity function (TRF). Due to the band-limited nature of the PSF, the RF images can only be acquired at a finite spatial resolution, which is often insufficient for proper representation of the diagnostic information contained in the TRF. One particular way to alleviate this problem is by means of image deconvolution, which is usually performed in a "blind" mode, when both PSF and TRF are estimated at the same time. Despite its proven effectiveness, blind deconvolution (BD) still suffers from a number of drawbacks, chief among which stems from its dependence on a stationary convolution model, which is incapable of accounting for the spatial variability of the PSF. As a result, virtually all existing BD algorithms are applied to localized segments of RF images. In this work, we introduce a novel method for non-stationary BD, which is capable of recovering the TRF concurrently with the spatially variable PSF. Particularly, our approach is based on semigroup theory which allows one to describe the effect of such a PSF in terms of the action of a properly defined linear semigroup. The approach leads to a tractable optimization problem, which can be solved using standard numerical methods. The effectiveness of the proposed solution is supported by experiments with in vivo ultrasound data.

Determining mineralogical variations of aeolian deposits using thermal infrared emissivity and linear deconvolution methods

NASA Astrophysics Data System (ADS)

Hubbard, Bernard E.; Hooper, Donald M.; Solano, Federico; Mars, John C.

2018-02-01

We apply linear deconvolution methods to derive mineral and glass proportions for eight field sample training sites at seven dune fields: (1) Algodones, California; (2) Big Dune, Nevada; (3) Bruneau, Idaho; (4) Great Kobuk Sand Dunes, Alaska; (5) Great Sand Dunes National Park and Preserve, Colorado; (6) Sunset Crater, Arizona; and (7) White Sands National Monument, New Mexico. These dune fields were chosen because they represent a wide range of mineral grain mixtures and allow us to gauge a better understanding of both compositional and sorting effects within terrestrial and extraterrestrial dune systems. We also use actual ASTER TIR emissivity imagery to map the spatial distribution of these minerals throughout the seven dune fields and evaluate the effects of degraded spectral resolution on the accuracy of mineral abundances retrieved. Our results show that hyperspectral data convolutions of our laboratory emissivity spectra outperformed multispectral data convolutions of the same data with respect to the mineral, glass and lithic abundances derived. Both the number and wavelength position of spectral bands greatly impacts the accuracy of linear deconvolution retrieval of feldspar proportions (e.g. K-feldspar vs. plagioclase) especially, as well as the detection of certain mafic and carbonate minerals. In particular, ASTER mapping results show that several of the dune sites display patterns such that less dense minerals typically have higher abundances near the center of the active and most evolved dunes in the field, while more dense minerals and glasses appear to be more abundant along the margins of the active dune fields.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blum, Paul

Cellulosic ethanol is an emerging biofuel that will make strong contributions to American domestic energy needs. In the US midwest the standard method for pretreatment of biomass uses hot acid to deconstruct lignocellulose. While other methods work, they are not in common use. Therefore it is necessary to work within this context to achieve process improvements and reductions in biofuel cost. Technology underlying this process could supplement and even replace commodity enzymes with engineered microbes to convert biomass-derived lignocellulose feedstocks into biofuels and valueadded chemicals. The approach that was used here was based on consolidated bioprocessing. Thermoacidophilic microbes belonging tomore » the Domain Archaea were evaluated and modfied to promote deconvolution and saccharification of lignocellulose. Biomass pretreatment (hot acid) was combined with fermentation using an extremely thermoacidophilic microbial platform. The identity and fate of released sugars was controlled using metabolic blocks combined with added biochemical traits where needed. LC/MS analysis supported through the newly established Nebraska Bioenergy Facility provided general support for bioenergy researchers at the University of Nebraska. The primary project strategy was to use microbes that naturally flourish in hot acid (thermoacidophiles) with conventional biomass pretreatment that uses hot acid. The specific objectives were: to screen thermoacidophilic taxa for the ability to deconvolute lignocellulose and depolymerize associated carbohydrates; evaluate and respond to formation of “inhibitors” that arose during incubation of lignocellulose under heated acidic conditions; identify and engineer “sugar flux channeling and catabolic blocks” that redirect metabolic pathways to maximize sugar concentrations; expand the hydrolytic capacity of extremely thermoacidophilic microbes through the addition of deconvolution traits; and establish the Nebraska Bioenergy Facility (NBF) at the University of Nebraska-Lincoln.« less

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring.

PubMed

Xiong, Naixue; Liu, Ryan Wen; Liang, Maohan; Wu, Di; Liu, Zhao; Wu, Huisi

2017-01-18

Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.

Blind deconvolution of astronomical images with band limitation determined by optical system parameters

NASA Astrophysics Data System (ADS)

Luo, L.; Fan, M.; Shen, M. Z.

2007-07-01

Atmospheric turbulence greatly limits the spatial resolution of astronomical images acquired by the large ground-based telescope. The record image obtained from telescope was thought as a convolution result of the object function and the point spread function. The statistic relationship of the images measured data, the estimated object and point spread function was in accord with the Bayes conditional probability distribution, and the maximum-likelihood formulation was found. A blind deconvolution approach based on the maximum-likelihood estimation technique with real optical band limitation constraint is presented for removing the effect of atmospheric turbulence on this class images through the minimization of the convolution error function by use of the conjugation gradient optimization algorithm. As a result, the object function and the point spread function could be estimated from a few record images at the same time by the blind deconvolution algorithm. According to the principle of Fourier optics, the relationship between the telescope optical system parameters and the image band constraint in the frequency domain was formulated during the image processing transformation between the spatial domain and the frequency domain. The convergence of the algorithm was increased by use of having the estimated function variable (also is the object function and the point spread function) nonnegative and the point-spread function band limited. Avoiding Fourier transform frequency components beyond the cut off frequency lost during the image processing transformation when the size of the sampled image data, image spatial domain and frequency domain were the same respectively, the detector element (e.g. a pixels in the CCD) should be less than the quarter of the diffraction speckle diameter of the telescope for acquiring the images on the focal plane. The proposed method can easily be applied to the case of wide field-view turbulent-degraded images restoration because of no using the object support constraint in the algorithm. The performance validity of the method is examined by the computer simulation and the restoration of the real Alpha Psc astronomical image data. The results suggest that the blind deconvolution with the real optical band constraint can remove the effect of the atmospheric turbulence on the observed images and the spatial resolution of the object image can arrive at or exceed the diffraction-limited level.

Phylogenetic Copy-Number Factorization of Multiple Tumor Samples.

PubMed

Zaccaria, Simone; El-Kebir, Mohammed; Klau, Gunnar W; Raphael, Benjamin J

2018-04-16

Cancer is an evolutionary process driven by somatic mutations. This process can be represented as a phylogenetic tree. Constructing such a phylogenetic tree from genome sequencing data is a challenging task due to the many types of mutations in cancer and the fact that nearly all cancer sequencing is of a bulk tumor, measuring a superposition of somatic mutations present in different cells. We study the problem of reconstructing tumor phylogenies from copy-number aberrations (CNAs) measured in bulk-sequencing data. We introduce the Copy-Number Tree Mixture Deconvolution (CNTMD) problem, which aims to find the phylogenetic tree with the fewest number of CNAs that explain the copy-number data from multiple samples of a tumor. We design an algorithm for solving the CNTMD problem and apply the algorithm to both simulated and real data. On simulated data, we find that our algorithm outperforms existing approaches that either perform deconvolution/factorization of mixed tumor samples or build phylogenetic trees assuming homogeneous tumor samples. On real data, we analyze multiple samples from a prostate cancer patient, identifying clones within these samples and a phylogenetic tree that relates these clones and their differing proportions across samples. This phylogenetic tree provides a higher resolution view of copy-number evolution of this cancer than published analyses.

New methods for time-resolved fluorescence spectroscopy data analysis based on the Laguerre expansion technique--applications in tissue diagnosis.

PubMed

Jo, J A; Marcu, L; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J

2007-01-01

A new deconvolution method for the analysis of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data is introduced and applied for tissue diagnosis. The intrinsic TR-LIFS decays are expanded on a Laguerre basis, and the computed Laguerre expansion coefficients (LEC) are used to characterize the sample fluorescence emission. The method was applied for the diagnosis of atherosclerotic vulnerable plaques. At a first stage, using a rabbit atherosclerotic model, 73 TR-LIFS in-vivo measurements from the normal and atherosclerotic aorta segments of eight rabbits were taken. The Laguerre deconvolution technique was able to accurately deconvolve the TR-LIFS measurements. More interesting, the LEC reflected the changes in the arterial biochemical composition and provided discrimination of lesions rich in macrophages/foam-cells with high sensitivity (> 85%) and specificity (> 95%). At a second stage, 348 TR-LIFS measurements were obtained from the explanted carotid arteries of 30 patients. Lesions with significant inflammatory cells (macrophages/foam-cells and lymphocytes) were detected with high sensitivity (> 80%) and specificity (> 90%), using LEC-based classifiers. This study has demonstrated the potential of using TR-LIFS information by means of LEC for in vivo tissue diagnosis, and specifically for detecting inflammation in atherosclerotic lesions, a key marker of plaque vulnerability.

Application of a deconvolution method for identifying burst amplitudes and arrival times in Alcator C-Mod far SOL plasma fluctuations

NASA Astrophysics Data System (ADS)

Theodorsen, Audun; Garcia, Odd Erik; Kube, Ralph; Labombard, Brian; Terry, Jim

2017-10-01

In the far scrape-off layer (SOL), radial motion of filamentary structures leads to excess transport of particles and heat. Amplitudes and arrival times of these filaments have previously been studied by conditional averaging in single-point measurements from Langmuir Probes and Gas Puff Imaging (GPI). Conditional averaging can be problematic: the cutoff for large amplitudes is mostly chosen by convention; the conditional windows used may influence the arrival time distribution; and the amplitudes cannot be separated from a background. Previous work has shown that SOL fluctuations are well described by a stochastic model consisting of a super-position of pulses with fixed shape and randomly distributed amplitudes and arrival times. The model can be formulated as a pulse shape convolved with a train of delta pulses. By choosing a pulse shape consistent with the power spectrum of the fluctuation time series, Richardson-Lucy deconvolution can be used to recover the underlying amplitudes and arrival times of the delta pulses. We apply this technique to both L and H-mode GPI data from the Alcator C-Mod tokamak. The pulse arrival times are shown to be uncorrelated and uniformly distributed, consistent with a Poisson process, and the amplitude distribution has an exponential tail.

On an image reconstruction method for ECT

NASA Astrophysics Data System (ADS)

Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro

2007-04-01

An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.

New Details on Pluto

NASA Image and Video Library

2015-07-10

This image of Pluto was taken by New Horizons' Long Range Reconnaissance Imager (LORRI) at 4:18 UT on July 9, 2015, from a range of 3.9 million miles (6.3 million kilometers). It reveals new details on the surface of Pluto, including complex patterns in the transition between the very dark equatorial band (nicknamed "the whale"), which occupies the lower part of the image, and the brighter northern terrain. The bright arc at the bottom of the disk shows that there is more bright terrain beyond the southern margin of the "whale." The side of Pluto that will be studied in great detail during the close encounter on July 14 is now rotating off the visible disk on the right hand side, and will not be seen again until shortly before closest approach. Three consecutive images were combined and sharpened, using a process called deconvolution, to create this view. Deconvolution enhances real detail but can also generate spurious features, including the bright edge seen on the upper and left margins of the disk (though the bright margin on the bottom of the disk is real). The wireframe globe shows the orientation of Pluto in the image: thicker lines indicate the equator and the prime meridian (the direction facing Charon). Central longitude on Pluto is 86°. http://photojournal.jpl.nasa.gov/catalog/PIA19705

Comparison between deterministic and statistical wavelet estimation methods through predictive deconvolution: Seismic to well tie example from the North Sea

NASA Astrophysics Data System (ADS)

de Macedo, Isadora A. S.; da Silva, Carolina B.; de Figueiredo, J. J. S.; Omoboya, Bode

2017-01-01

Wavelet estimation as well as seismic-to-well tie procedures are at the core of every seismic interpretation workflow. In this paper we perform a comparative study of wavelet estimation methods for seismic-to-well tie. Two approaches to wavelet estimation are discussed: a deterministic estimation, based on both seismic and well log data, and a statistical estimation, based on predictive deconvolution and the classical assumptions of the convolutional model, which provides a minimum-phase wavelet. Our algorithms, for both wavelet estimation methods introduce a semi-automatic approach to determine the optimum parameters of deterministic wavelet estimation and statistical wavelet estimation and, further, to estimate the optimum seismic wavelets by searching for the highest correlation coefficient between the recorded trace and the synthetic trace, when the time-depth relationship is accurate. Tests with numerical data show some qualitative conclusions, which are probably useful for seismic inversion and interpretation of field data, by comparing deterministic wavelet estimation and statistical wavelet estimation in detail, especially for field data example. The feasibility of this approach is verified on real seismic and well data from Viking Graben field, North Sea, Norway. Our results also show the influence of the washout zones on well log data on the quality of the well to seismic tie.

HST observations of globular clusters in M 31. 1: Surface photometry of 13 objects

NASA Technical Reports Server (NTRS)

Pecci, F. Fusi; Battistini, P.; Bendinelli, O.; Bonoli, F.; Cacciari, C.; Djorgovski, S.; Federici, L.; Ferraro, F. R.; Parmeggiani, G.; Weir, N.

1994-01-01

We present the initial results of a study of globular clusters in M 31, using the Faint Object Camera (FOC) on the Hubble Space Telescope (HST). The sample of objects consists of 13 clusters spanning a range of properties. Three independent image deconvolution techniques were used in order to compensate for the optical problems of the HST, leading to mutually fully consistent results. We present detailed tests and comparisons to determine the reliability and limits of these deconvolution methods, and conclude that high-quality surface photometry of M 31 globulars is possible with the HST data. Surface brightness profiles have been extracted, and core radii, half-light radii, and central surface brightness values have been measured for all of the clusters in the sample. Their comparison with the values from ground-based observations indicates the later to be systematically and strongly biased by the seeing effects, as it may be expected. A comparison of the structural parameters with those of the Galactic globulars shows that the structural properties of the M 31 globulars are very similar to those of their Galactic counterparts. A candidate for a post-core-collapse cluster, Bo 343 = G 105, has been already identified from these data; this is the first such detection in the M 31 globular cluster system.

A Model-Based Approach for Microvasculature Structure Distortion Correction in Two-Photon Fluorescence Microscopy Images

PubMed Central

Dao, Lam; Glancy, Brian; Lucotte, Bertrand; Chang, Lin-Ching; Balaban, Robert S; Hsu, Li-Yueh

2015-01-01

SUMMARY This paper investigates a post-processing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modeling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to sub volumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images. PMID:26224257

Tectonics and crustal structure of the Saurashtra peninsula: based on Gravity and Magnetic data

NASA Astrophysics Data System (ADS)

Mishra, A. K.; Singh, A.; Singh, U. K.

2016-12-01

The Saurashtra peninsula is located at the North Western margin of the Indian shield which occurs as a horst block between the rifts namely as Kachchh, Cambay and Narmada. It is important because of occurrence of moderate earthquake and presence of mesozoic sediments below the Deccan trap. The maps of bouguer gravity anomaly and the total intensity magnetic anomalies of Saurashtra have delineated six circular gravity highs of magnitudes 40-60 mGal and 800-1000 nT respectively. In order to understand the location, structure and depth of the source body, methods like continuous wavelet transform (CWT), Euler deconvolution and power spectrum analysis have been implemented in the potential field data. The CWT and Euler deconvolution give 16-18 km average depth of volcanic plug in Junagadh and Rajula region. From the power spectrum analysis, it is found that average Moho depth in the Saurashtra is about 36-38 km. Keeping the constraints obtained from geophysical studies like borehole, deep seismic survey, receiver function analysis and geological information, combined gravity and magnetic modeling have been performed. Detailed crustal structure of the Saurashtra region has been delineated along two profiles which pass from prominent geological features Junagadh and Rajula volcanic plugs respectively.

Closed-form expressions of some stochastic adapting equations for nonlinear adaptive activation function neurons.

PubMed

Fiori, Simone

2003-12-01

In recent work, we introduced nonlinear adaptive activation function (FAN) artificial neuron models, which learn their activation functions in an unsupervised way by information-theoretic adapting rules. We also applied networks of these neurons to some blind signal processing problems, such as independent component analysis and blind deconvolution. The aim of this letter is to study some fundamental aspects of FAN units' learning by investigating the properties of the associated learning differential equation systems.

PEGylated substrates of NSP4 protease: A tool to study protease specificity

NASA Astrophysics Data System (ADS)

Wysocka, Magdalena; Gruba, Natalia; Grzywa, Renata; Giełdoń, Artur; Bąchor, Remigiusz; Brzozowski, Krzysztof; Sieńczyk, Marcin; Dieter, Jenne; Szewczuk, Zbigniew; Rolka, Krzysztof; Lesner, Adam

2016-03-01

Herein we present the synthesis of a novel type of peptidomimetics composed of repeating diaminopropionic acid residues modified with structurally diverse heterobifunctional polyethylene glycol chains (abbreviated as DAPEG). Based on the developed compounds, a library of fluorogenic substrates was synthesized. Further library deconvolution towards human neutrophil serine protease 4 (NSP4) yielded highly sensitive and selective internally quenched peptidomimetic substrates. In silico analysis of the obtained peptidomimetics revealed the presence of an interaction network with distant subsites located on the enzyme surface.

SU-F-R-34: Quantitative Perfusion Measurement in Rectal Cancer Using Three Different Pharmacokinetic Models: Implications for Prospective Study Design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nie, K; Yue, N; Jabbour, S

Purpose: To compare three different pharmacokinetic models for analysis of dynamic-contrast-enhanced (DCE)-CT data with respect to different acquisition times and location of region of interest. Methods: Eight rectal cancer patients with pre-treatment DCE-CTs were included. The dynamic sequence started 4–10seconds(s) after the injection of contrast agent. The scan included a 110s acquisition with intervals of 40×1s+15×3s+4×6s. An experienced oncologist outlined the tumor region. Hotspots with top-5%-enhancement were also identified. Pharmacokinetic analysis was performed using three different models: deconvolution method, Patlak model, and modified Toft’s model. Perfusion parameters as blood flow (BF), blood volume (BV), mean transit time (MTT), permeability-surface-area-product (PS),more » volume transfer constant (Ktrans), and flux rate constant (Kep), were compared with respect to different acquisition times of 45s, 65s, 85s and 105s. Both hotspot and whole-volume variances were also assessed. The differences were compared using the Wilcoxon matched-pairs test and Bland-Altman plots. Results: Moderate correlation was observed for various perfusion parameters (r=0.56–0.72, p<0.0001) but the Wilcoxon test revealed a significant difference among the three models (P < .001). Significant differences in PS were noted between acquisitions of 45s versus longer time of 85s or 105s (p<0.05) using Patlak but not with the deconvolution method. In addition, measurements varied substantially between whole-volume vs. hotspot analysis. Conclusion: The radiation dose of DCE-CT was on average 1.5 times of an abdomen/pelvic CT, which is not insubstantial. To take the DCE-CT forward as a biomarker in oncology, prospective studies should be carefully designed with the optimal image acquisition and analysis technique. Our study suggested that: (1) different kinetic models are not interchangeable; (2) a 45s acquisition might not be sufficient for reliable permeability measurement in rectal cancer using Patlak model, but might be achievable using deconvolution method; and (3) local variations existed inside the tumor, and both whole-volume-averaged and local-heterogeneity analysis is recommended for future quantitative studies. This work is supported by the National High-tech R&D program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917), Natural Science Foundation of China (NSFC Grant No. 81201091).« less

Deconvoluting the Complexity of Bone Metastatic Prostate Cancer via Computational Modeling

DTIC Science & Technology

2016-09-01

Fellowship (2015-2017) Consejo Nacional de Ciencia y Tecnologia (CONACYT) MRes/PhD scholarship (2007- 2011) CERN Teacher Programme scholarship (2007...UDLAP Apoyo a Ciencias BSc scholarship (2000-2005) Awards Society for Mathematical Biology (SMB) Travel Award (2015

Improved Scheme of Modified Gaussian Deconvolution for Reflectance Spectra of Lunar Soils

NASA Technical Reports Server (NTRS)

Hiroi, T.; Pieters, C. M.; Noble, S. K.

2000-01-01

In our continuing effort for deconvolving reflectance spectra of lunar soils using the modified Gaussian model, a new scheme has been developed, including a new form of continuum. All the parameters are optimized with certain constraints.

Large seismic source imaging from old analogue seismograms

NASA Astrophysics Data System (ADS)

Caldeira, Bento; Buforn, Elisa; Borges, José; Bezzeghoud, Mourad

2017-04-01

In this work we present a procedure to recover the ground motions by a proper digital structure, from old seismograms in analogue physical support (paper or microfilm) to study the source rupture process, by application of modern finite source inversion tools. Despite the quality that the analog data and the digitizing technologies available may have, recover the ground motions with the accurate metrics from old seismograms, is often an intricate procedure. Frequently the general parameters of the analogue instruments response that allow recover the shape of the ground motions (free periods and damping) are known, but the magnification that allow recover the metric of these motions is dubious. It is in these situations that the procedure applies. The procedure is based on assign of the moment magnitude value to the integral of the apparent Source Time Function (STF), estimated by deconvolution of a synthetic elementary seismogram from the related observed seismogram, corrected with an instrument response affected by improper magnification. Two delicate issues in the process are 1) the calculus of the synthetic elementary seismograms that must consider later phases if applied to large earthquakes (the portions of signal should be 3 or 4 times larger than the rupture time) and 2) the deconvolution to calculate the apparent STF. In present version of the procedure was used the Direct Solution Method to compute the elementary seismograms and the deconvolution was processed in time domain by an iterative algorithm that allow constrains the STF to stay positive and time limited. The method was examined using synthetic data to test the accuracy and robustness. Finally, a set of 17 real old analog seismograms from the Santa Maria (Azores) 1939 earthquake (Mw=7.1) was used in order to recover the waveforms in the required digital structure, from which by inversion allows compute the finite source rupture model (slip distribution). Acknowledgements: This work is co-financed by the European Union through the European Regional Development Fund under COMPETE 2020 (Operational Program for Competitiveness and Internationalization) through the ICT project (UID / GEO / 04683/2013) under the reference POCI-01-0145 -FEDER-007690.

Bilinear Inverse Problems: Theory, Algorithms, and Applications

NASA Astrophysics Data System (ADS)

Ling, Shuyang

We will discuss how several important real-world signal processing problems, such as self-calibration and blind deconvolution, can be modeled as bilinear inverse problems and solved by convex and nonconvex optimization approaches. In Chapter 2, we bring together three seemingly unrelated concepts, self-calibration, compressive sensing and biconvex optimization. We show how several self-calibration problems can be treated efficiently within the framework of biconvex compressive sensing via a new method called SparseLift. More specifically, we consider a linear system of equations y = DAx, where the diagonal matrix D (which models the calibration error) is unknown and x is an unknown sparse signal. By "lifting" this biconvex inverse problem and exploiting sparsity in this model, we derive explicit theoretical guarantees under which both x and D can be recovered exactly, robustly, and numerically efficiently. In Chapter 3, we study the question of the joint blind deconvolution and blind demixing, i.e., extracting a sequence of functions [special characters omitted] from observing only the sum of their convolutions [special characters omitted]. In particular, for the special case s = 1, it becomes the well-known blind deconvolution problem. We present a non-convex algorithm which guarantees exact recovery under conditions that are competitive with convex optimization methods, with the additional advantage of being computationally much more efficient. We discuss several applications of the proposed framework in image processing and wireless communications in connection with the Internet-of-Things. In Chapter 4, we consider three different self-calibration models of practical relevance. We show how their corresponding bilinear inverse problems can be solved by both the simple linear least squares approach and the SVD-based approach. As a consequence, the proposed algorithms are numerically extremely efficient, thus allowing for real-time deployment. Explicit theoretical guarantees and stability theory are derived and the number of sampling complexity is nearly optimal (up to a poly-log factor). Applications in imaging sciences and signal processing are discussed and numerical simulations are presented to demonstrate the effectiveness and efficiency of our approach.

Estimating the Earthquake Source Time Function by Markov Chain Monte Carlo Sampling

NASA Astrophysics Data System (ADS)

Dȩbski, Wojciech

2008-07-01

Many aspects of earthquake source dynamics like dynamic stress drop, rupture velocity and directivity, etc. are currently inferred from the source time functions obtained by a deconvolution of the propagation and recording effects from seismograms. The question of the accuracy of obtained results remains open. In this paper we address this issue by considering two aspects of the source time function deconvolution. First, we propose a new pseudo-spectral parameterization of the sought function which explicitly takes into account the physical constraints imposed on the sought functions. Such parameterization automatically excludes non-physical solutions and so improves the stability and uniqueness of the deconvolution. Secondly, we demonstrate that the Bayesian approach to the inverse problem at hand, combined with an efficient Markov Chain Monte Carlo sampling technique, is a method which allows efficient estimation of the source time function uncertainties. The key point of the approach is the description of the solution of the inverse problem by the a posteriori probability density function constructed according to the Bayesian (probabilistic) theory. Next, the Markov Chain Monte Carlo sampling technique is used to sample this function so the statistical estimator of a posteriori errors can be easily obtained with minimal additional computational effort with respect to modern inversion (optimization) algorithms. The methodological considerations are illustrated by a case study of the mining-induced seismic event of the magnitude M L ≈3.1 that occurred at Rudna (Poland) copper mine. The seismic P-wave records were inverted for the source time functions, using the proposed algorithm and the empirical Green function technique to approximate Green functions. The obtained solutions seem to suggest some complexity of the rupture process with double pulses of energy release. However, the error analysis shows that the hypothesis of source complexity is not justified at the 95% confidence level. On the basis of the analyzed event we also show that the separation of the source inversion into two steps introduces limitations on the completeness of the a posteriori error analysis.

Quantitation of the cellular content of saliva and buccal swab samples.

PubMed

Theda, Christiane; Hwang, Seo Hye; Czajko, Anna; Loke, Yuk Jing; Leong, Pamela; Craig, Jeffrey M

2018-05-02

Buccal swabs and saliva are the two most common oral sampling methods used for medical research. Often, these samples are used interchangeably, despite previous evidence that both contain buccal cells and blood leukocytes in different proportions. For some research, such as epigenetic studies, the cell types contributing to the analysis are highly relevant. We collected such samples from twelve children and twenty adults and, using Papanicolaou staining, measured the proportions of epithelial cells and leukocytes through microscopy. To our knowledge, no studies have compared cellular heterogeneity in buccal swab and saliva samples from adults and children. We confirmed that buccal swabs contained a higher proportion of epithelial cells than saliva and that children have a greater proportion of such cells in saliva compared to adults. At this level of resolution, buccal swabs and saliva contained similar epithelial cell subtypes. Gingivitis in children was associated with a higher proportion of leukocytes in saliva samples but not in buccal swabs. Compared to more detailed and costly methods such as flow cytometry or deconvolution methods used in epigenomic analysis, the procedure described here can serve as a simple and low-cost method to characterize buccal and saliva samples. Microscopy provides a low-cost tool to alert researchers to the presence of oral inflammation which may affect a subset of their samples. This knowledge might be highly relevant to their specific research questions, may assist with sample selection and thus might be crucial information despite the ability of data deconvolution methods to correct for cellular heterogeneity.

Spectroscopy of disordered low-field sites in Cr3+: Mullite glass ceramic

NASA Astrophysics Data System (ADS)

Knutson, Robert; Liu, Huimin; Yen, W. M.; Morgan, T. V.

1989-09-01

In this article we present results of optical and ESR studies that have allowed us to study the behavior of Cr3+ at disordered low-field sites within a mullite ceramic host. The results indicate that the existence of these low-field ions, which are likely at sites in regions of disorder, accounts for most of the spectroscopic anomalies previously noted in these materials. Furthermore, energy transfer from ordered high-field to disordered low-field ions is observed. The resulting complex spectra are deconvoluted by means of the recently developed technique of saturation-resolved fluorescence spectroscopy.

New Physical Constraints for Multi-Frame Blind Deconvolution

DTIC Science & Technology

2014-12-10

Laboratory) Dr. Julian Christou (Large Binocular Telescope Observatory) REAL ACADEMIA DE CIENCIAS Y ARTES DE BARCELONA RAMBLA DE LOS ESTUDIOS 115... CIENCIAS Y ARTES DE BARCELONA RAMBLA DE LOS ESTUDIOS 115 BARCELONA, 08002 SPAIN 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING

Depth from Optical Turbulence

DTIC Science & Technology

2012-01-01

Dagobert, and C. Franchis . Atmospheric tur- bulence restoration by diffeomorphic image registration and blind deconvolution. In ACIVS, 2008. 1 [4] S...20] V. Tatarskii. Wave Propagation in a Turbulent Medium. McGraw-Hill Books, 1961. 2 [21] Y. Tian and S. Narasimhan. A globally optimal data-driven

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivativesmore » of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.« less