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Ultra high resolution soft x-ray tomography

Description: Ultra high resolution three dimensional images of a microscopic test object were made with soft x-rays using a scanning transmission x-ray microscope. The test object consisted of two different patterns of gold bars on silicon nitride windows that were separated by {approximately}5{mu}m. A series of nine 2-D images of the object were recorded at angles between {minus}50 to +55 degrees with respect to the beam axis. The projections were then combined tomographically to form a 3-D image by means of an algebraic reconstruction technique (ART) algorithm. A transverse resolution of {approximately}1000 {Angstrom} was observed. Artifacts in the reconstruction limited the overall depth resolution to {approximately}6000 {Angstrom}, however some features were clearly reconstructed with a depth resolution of {approximately}1000 {Angstrom}. A specially modified ART algorithm and a constrained conjugate gradient (CCG) code were also developed as improvements over the standard ART algorithm. Both of these methods made significant improvements in the overall depth resolution bringing it down to {approximately}1200 {Angstrom} overall. Preliminary projection data sets were also recorded with both dry and re-hydrated human sperm cells over a similar angular range.
Date: July 19, 1995
Creator: Haddad, W.S.; Trebes, J.E. & Goodman, D.M.
Partner: UNT Libraries Government Documents Department

Deconvolution/identification techniques for 1-D transient signals

Description: This paper discusses a variety of nonparametric deconvolution and identification techniques that we have developed for application to 1-D transient signal problems. These methods are time-domain techniques that use direct methods for matrix inversion. Therefore, they are not appropriate for large data'' problems. These techniques involve various regularization methods and permit the use of certain kinds of a priori information in estimating the unknown. These techniques have been implemented in a package using standard FORTRAN that should make the package readily transportable to most computers. This paper is also meant to be an instruction manual for the package. 25 refs., 17 figs., 1 tab.
Date: October 1, 1990
Creator: Goodman, D.M.
Partner: UNT Libraries Government Documents Department

Image recovery techniques for x-ray computed tomography in limited data environments

Description: There is an increasing requirement throughout LLNL for nondestructive evaluation using X-ray computed tomography (CT). In many cases, restrictions on data acquisition time, imaging geometry, and budgets make it unfeasible to acquire projection data over enough views to achieve desired spatial resolution using conventional CT methods. In particular, conventional CT methods are non-iterative algorithms that have the advantage of low computational effort, but they are not sufficiently adaptable to incorporate prior information or non-Gaussian statistics. Most currently existing iterative tomography algorithms are based on methods that are time consuming because they converge very flowingly, if at all. The goal of the work was to develop a set of limited data CT reconstruction tools and then demonstrate their usefulness by applying them to a variety of problems of interest to LLNL. In this project they continued their development of reconstruction tools and they have demonstrated their effectiveness on several important problems.
Date: March 1, 1999
Creator: Aufderheide, M B; Goodman, D M; Jackson, J A & Johansson, E M
Partner: UNT Libraries Government Documents Department

Concluding Report: Quantitative Tomography Simulations and Reconstruction Algorithms

Description: In this report we describe the original goals and final achievements of this Laboratory Directed Research and Development project. The Quantitative was Tomography Simulations and Reconstruction Algorithms project (99-ERD-015) funded as a multi-directorate, three-year effort to advance the state of the art in radiographic simulation and tomographic reconstruction by improving simulation and including this simulation in the tomographic reconstruction process. Goals were to improve the accuracy of radiographic simulation, and to couple advanced radiographic simulation tools with a robust, many-variable optimization algorithm. In this project, we were able to demonstrate accuracy in X-Ray simulation at the 2% level, which is an improvement of roughly a factor of 5 in accuracy, and we have successfully coupled our simulation tools with the CCG (Constrained Conjugate Gradient) optimization algorithm, allowing reconstructions that include spectral effects and blurring in the reconstructions. Another result of the project was the assembly of a low-scatter X-Ray imaging facility for use in nondestructive evaluation applications. We conclude with a discussion of future work.
Date: February 1, 2002
Creator: Aufderheide, M B; Martz, H E; Slone, D M; Jackson, J A; Schach von Wittenau, A E; Goodman, D M et al.
Partner: UNT Libraries Government Documents Department