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reconstruction algorithms for grain mapping by laboratory X-ray diffraction contrast tomography

JOURNAL OF APPLIED CRYSTALLOGRAPHY 2022年第6期55卷 1652-1663页

作者： Fang, Haixing Ludwig, Wolfgang Lhuissier, Pierre Univ Grenoble Alpes Grenoble INP CNRS SIMaP F-38402 Grenoble France European Synchrotron Radiat Facil ESRF 71 Ave Martyrs F-380000 Grenoble France Univ Lyon CNRS MATEIS INSA Lyon F-69621 Villeurbanne France

X-ray-based non-destructive 3D grain mapping techniques are well established at synchrotron facilities. To facilitate everyday access to grain mapping instruments, laboratory diffraction contrast tomography (LabDCT), using a laboratory-based conical polychromatic X-ray beam, has been developed and commercialized. Yet the currently available LabDCT grain reconstruction methods are either ill-suited for handling a large number of grains or require a commercial licence bound to a specific instrument. To promote the availability of LabDCT, grain reconstruction methods have been developed with multiple reconstruction algorithms based on both forward and back calculations. The different algorithms are presented in detail and their efficient implementation using parallel computing is described. The performance of different reconstruction methods is assessed on synthetic data. The code to implement all the described algorithms has been made publicly accessible with the intention of fostering the development of grain mapping techniques on widely available laboratory instruments.

关键词： diffraction contrast tomography grain mapping reconstruction algorithms 3D imaging forward calculations back calculations

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reconstruction algorithms - TRANSFORM METHODS

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PROCEEDINGS OF THE IEEE 1983年第3期71卷 390-408页

作者： LEWITT, RM Medical Image Processing Group Department of Radiology Hospital of University of Pennsylvania Philadelphia PA USA

Transform methods for image reconstruction from projections are based on analytic inversion formulas. In this tutorial paper, the inversion formula for the case of two-dimensional (2-D) reconstruction from line integrals is manipulated into a number of different forms, each of which may be discretized to obtain different algorithms for reconstruction from sampled data. For the convolution-backprojection algorithm and the direct Fourier algorithm the emphasis is placed on understanding the relationship between the discrete operations specified by the algorithm and the functional operations expressed by the inversion formula. The performance of the Fourier algorithm may be improved, with negligible extra computation, by interleaving two polar sampling grids in Fourier space. The convolution-backprojection formulas are adapted for the fan-beam geometry, and other reconstruction methods are summarized, including the rho-filtered layergram method, and methods involving expansions in angular harmonics. A standard mathematical process leads to a known formula for iterative reconstruction from projections at a finite number of angles. A new iterative reconstruction algorithm is obtained from this formula by introducing one-dimensional (1-D) and 2-D interpolating functions, applied to sampled projections and images, respectively. These interpolating functions are derived by the same Fourier approach which aids in the development and understanding of the more conventional transform methods.

关键词： reconstruction algorithms Image reconstruction Computed tomography Two dimensional displays Sampling methods Data visualization Iterative algorithms Image analysis Grid computing Interleaved codes

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reconstruction algorithms FOR GEOPHYSICAL APPLICATIONS IN NOISY ENVIRONMENTS

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PROCEEDINGS OF THE IEEE 1979年第7期67卷 1060-1064页

作者： RADCLIFF, RD BALANIS, CA Department of Electrical Engineering West Virginia University Morgantown WV USA

Remote determination of underground geophysical structures is a matter of considerable interest. Detecting such structures by scanning the area of interest with electromagnetic radiation is shown to reduce to the problem of solving an inconsistent system of equations for a spatial attenuation distribution. This paper examines the employment of reconstruction algorithms to solve such systems of equations, and it presents significant modifications to a standard algorithm that vastly improves its performance in the presence of noisy data. The process of in situ coal gasification is taken as an example to illustrate the superior performance of the modified algorithm.

关键词： reconstruction algorithms Working environment noise Conductivity Equations Monitoring Electromagnetic scattering Linear systems Background noise Attenuation Petroleum

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reconstruction algorithms and experiments with a prototype of holographic subsurface radar 4

Reconstruction algorithms and experiments with a prototype o...

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4th International Conference on Antenna Theory and Techniques

作者： Popov, AV Kopeikyn, VV Vinogradov, VA Zapunidi, SA Ionosphere & Radiowave Propagat RAS Inst Terrestrial Magnetism Troitsk 142092 Moscow Region Russia

Mathematical basis and numerical implementation of the wave front conversion method of the scattering object reconstruction are presented. We also describe a prototype of holographic microwave radar and first experime... 详细信息

ISBN: (纸本)0780378814

关键词： microwave holography wave front conversion reconstruction algorithms

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reconstruction algorithms in electrical imaging

Reconstruction algorithms in electrical imaging

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Science and Engineering of Medical Imaging 1989

作者： Bourret, R. Marsili, P.M. Mounie, G. Soulere, S. Deluze, U. Grrnie, M. Morucci, J.P. INSERM Unité 305 Hôtel Dleu Toulouse Cédex31052 France

The first part of this article is a brief presentation of the models selected to represent the current-voltage relationships in biological tissue with a view to their application in impedance tomography. The second and third parts develop the principal resolution methods for these models: - The analytical methods (above all the Barber and Brown method (7-14)). - The digital methods (Kim (1), Wexler (20), Alessandrini (17). Some remarks and comments concerning implementation of these reconstruction algorithms will be made in conclusion to this presentation.

关键词： Medical imaging reconstruction algorithms Electrodes Mathematical modeling Fourier transforms Bismuth Tomography Chemical elements Cerium Tissues

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ON COMPLETE-DATA SPACES FOR PET reconstruction algorithms

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 1993年第4期40卷 1055-1061页

作者： FESSLER, JA CLINTHORNE, NH ROGERS, WL University of Michigan USA

As investigators consider more' comprehensive measurement models for emission tomography, there will be more choices for the complete-data spaces of the associated expectation-maximization (EM) algorithms for maximum-likelihood (ML) estimation. In this paper, we show that EM algorithms based on smaller complete-data spaces will typically converge faster. We discuss two practical applications of these concepts: (i) the ML-IA and ML-IB image reconstruction algorithms of Politte and Snyder [1] which are based on measurement models that account for attenuation and accidental coincidences in positron-emission tomography (PET), and (ii) the problem of simultaneous estimation of emission and transmission parameters. Although the PET applications may often violate the necessary regularity conditions, our analysis predicts heuristically that the ML-IB algorithm, which has a smaller complete-data space, should converge faster than ML-IA. This is corroborated by the empirical findings in [1].

关键词： Positron emission tomography reconstruction algorithms Maximum likelihood estimation Attenuation measurement Probability Image converters US Department of Energy Convergence Algorithm design and analysis Biomedical imaging

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Spatial Resolution and Precision Properties of Scatterometer reconstruction algorithms

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2017年第5期10卷 2372-2382页

作者： Liu, Liling Dong, Xiaolong Lin, Wenming Zhu, Jintai Zhu, Di Chinese Acad Sci Natl Space Sci Ctr Key Lab Microwave Remote Sensing Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Inst Marine Sci Barcelona 08003 Spain DFH Satellite Co Ltd Beijing 100094 Peoples R China

Various reconstruction methods have been used to enhance the spatial resolution of scatterometer data. Most of the image reconstructions are two-dimensional problems, which combine multiple passes of overlapping data over the temporally homogeneous surface, and thus are only suitable for land and ice applications. This paper attempts to address the one-dimensional reconstruction to enhance the azimuth resolution of scatterometer data using a single pass of observations. Since the range resolution determined by the on-board dechirping technique is generally up to several hundred meters, the one-dimensional reconstruction is adequate for certain near real-time ocean applications, such as the development of coastal scatterometer winds. Three well-known reconstruction algorithms, including additive algebraic reconstruction technique (AART), multiplicative algebraic reconstruction technique (MART), and scatterometer image reconstruction (SIR), are evaluated. The spatial resolution and the reconstruction precision resolved by each algorithm are separately analyzed using the local impulse response and Monte Carlo methods. The dependence of the spatial resolution and the reconstruction precision on a variety of parameters, such as the mean backscatter coefficient and its variance, the beamwidth of spatial response function (SRF), and the SRF function type, is evaluated using a simulation framework. In particular, the tradeoff between the spatial resolution and the reconstruction precision is examined for three algorithms. The results show that SIR offers the quickest convergence and lowest noise.

关键词： Local impulse response reconstruction algorithms resolution scatterometer spatial response function (SRF)

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Slab-by-slab blurring model for geometric point response correction and attenuation correction using iterative reconstruction algorithms

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 1998年第4期45卷 2168-2173页

作者： Bai, CY Zeng, GL Gullberg, GT DiFilippo, F Miller, S Univ Utah Dept Radiol Salt Lake City UT 84132 USA Picker Int Cleveland OH USA

The distance-dependent geometric point response of a single photon emission computed tomography (SPECT) system and the attenuation effect of photons passing through the object are modeled in an iterative OS-EM reconstruction algorithm to improve both the resolution and quantitative accuracy of the reconstructed images. A specified number of neighboring vertical slices are grouped into a slab, and an efficient incremental slab-by-slab blurring model is introduced to accelerate the reconstruction. The advantage of the slab-by-slab blurring model over the slice-by-slice model is that the computational time is reduced, while still maintaining the spatial resolution and quantitative accuracy of the reconstructed images. The application of this incremental slab-by-slab blurring model with a slice-by-slice attenuation model to the image reconstruction of phantom, Monte Carlo simulated SPECT data, and patient data shows improved resolution and contrast over the images reconstructed without the corrections. The reconstruction is accelerated by a factor of about 1.4, and the projection/backprojection operation is accelerated by a factor of about 5, using the slab-by-slab convolution implementation with 8 slices in a slab compared with the slice-by-slice convolution implementation.

关键词： Solid modeling Image reconstruction Acceleration Single photon emission computed tomography Attenuation Image resolution Slabs Spatial resolution Convolution reconstruction algorithms

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CONVERGENCE OF EM IMAGE-reconstruction algorithms WITH GIBBS SMOOTHING

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IEEE TRANSACTIONS ON MEDICAL IMAGING 1990年第4期9卷 439-446页

作者： LANGE, K Department of Biomathematics University of California Los Angeles School of Medicine Los Angeles CA USA

Recent modifications of the EM emission reconstruction algorithm to include a Gibbs prior promise smoother, more appealing images. These priors incorporate nearest neighbor interactions that penalize large deviations in parameter estimates for adjacent pixels. In this context, Green has defined an OSL (one step late) algorithm that retains the E-step of the EM algorithm, but provides an approximate solution to the M-step. Further modifications of the OSL algorithm guarantee convergence to the unique maximum of the log posterior function. The present paper proves convergence under a specific set of sufficient conditions. Several of these conditions concern the potential functions of the Gibbs prior, and a number of new, candidate potential functions are identified. Generalization of the OSL algorithm to transmission tomography is also considered.

关键词： Convergence Image reconstruction Smoothing methods Tomography Nearest neighbor searches Parameter estimation Vectors reconstruction algorithms Sufficient conditions Image converters

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Noise histogram regularization for iterative image reconstruction algorithms

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION 2007年第3期24卷 608-617页

作者： Thurman, Samuel T. Fienup, James R. Univ Rochester Inst Opt Rochester NY 14627 USA

We derive a regularization term for iterative image reconstruction algorithms based on the histogram of the residual difference between a forward-model image of a given object estimate and noisy image data. The term can be used to constrain this residual histogram to be statistically equivalent to the expected noise histogram, preventing overfitting of noise in a reconstruction. reconstruction results from simulated imagery are presented for the cases of Gaussian and quantization noise. (c) 2007 Optical Society of America.

关键词： Image metrics Image quality Image reconstruction Photon counting reconstruction algorithms Statistics

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