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Title: Accurate stochastic reconstruction of heterogeneous microstructures by limited x-ray tomographic projections

Authors:
 [1];  [2];  [2];  [2];  [2]
  1. Mechanical Engineering, Arizona State University, Tempe Arizona U.S.A.
  2. Materials Science and Engineering, Arizona State University, Tempe Arizona U.S.A.
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
Sponsoring Org.:
National Science Foundation (NSF)
OSTI Identifier:
1349113
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Microscopy; Journal Volume: 264; Journal Issue: 3
Country of Publication:
United States
Language:
ENGLISH

Citation Formats

LI, HECHAO, KAIRA, SHASHANK, MERTENS, JAMES, CHAWLA, NIKHILESH, and JIAO, YANG. Accurate stochastic reconstruction of heterogeneous microstructures by limited x-ray tomographic projections. United States: N. p., 2016. Web. doi:10.1111/jmi.12449.
LI, HECHAO, KAIRA, SHASHANK, MERTENS, JAMES, CHAWLA, NIKHILESH, & JIAO, YANG. Accurate stochastic reconstruction of heterogeneous microstructures by limited x-ray tomographic projections. United States. doi:10.1111/jmi.12449.
LI, HECHAO, KAIRA, SHASHANK, MERTENS, JAMES, CHAWLA, NIKHILESH, and JIAO, YANG. 2016. "Accurate stochastic reconstruction of heterogeneous microstructures by limited x-ray tomographic projections". United States. doi:10.1111/jmi.12449.
@article{osti_1349113,
title = {Accurate stochastic reconstruction of heterogeneous microstructures by limited x-ray tomographic projections},
author = {LI, HECHAO and KAIRA, SHASHANK and MERTENS, JAMES and CHAWLA, NIKHILESH and JIAO, YANG},
abstractNote = {},
doi = {10.1111/jmi.12449},
journal = {Journal of Microscopy},
number = 3,
volume = 264,
place = {United States},
year = 2016,
month = 7
}
  • Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods:more » In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial–temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial–temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial–temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240{sup ∘} short scan angular span was divided into four consecutive 60{sup ∘} angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200{sup ∘}, three 66{sup ∘} angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. Conclusions: In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60{sup ∘} angular subsectors.« less
  • Four algorithms are adapted to perform direct three-dimensional reconstruction from projections. The algorithms considered are summation, the Algebraic Reconstruction Technique (ART), the Simultaneous Iterative Reconstruction Technique (SIRT), and the Iterative Least Squares Technique (ILST). The concept of tomographic projections is introduced and shown to greatly simplify the calculations. This work represents the first time that these iterative algorithms have been applied to projections other than coaxial. The methods developed can be of benefit in electron microscopy, holographic interferometry, and nuclear medicine. To evaluate these methods an experimental investigation is carried out using computer-generated synthetic images. Using SIRT, direct 3-D reconstructionmore » is shown to be superior to serial 2-D reconstruction from coaxial projections when the range of viewing angles is limited. The number of projections required for adequate reconstruction is also considered. Finally, the performance of the algorithms is compared with respect to overall similarity of the reconstruction to the original test object, effects of noise, and computer time and memory requirements.« less
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  • Usually tomographic procedure requires a set of projections around the object under study and a mathematical processing of such projections through reconstruction algorithms. An accurate reconstruction requires a proper number of projections (angular sampling) and a proper number of elements in each projection (linear sampling). However in several practical cases it is not possible to fulfill these conditions leading to the so-called problem of few projections. In this case, iterative reconstruction algorithms are more suitable than analytic ones. In this work we present a program written in C++ that provides an environment for two iterative algorithm implementations, one algebraic andmore » the other statistical. The software allows the user a full definition of the acquisition and reconstruction geometries used for the reconstruction algorithms but also to perform projection and backprojection operations. A set of analysis tools was implemented for the characterization of the convergence process. We analyze the performance of the algorithms on numerical phantoms and present the reconstruction of experimental data with few projections coming from transmission X-ray and micro PIXE (Particle-Induced X-Ray Emission) images.« less
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