Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Spherically symmetric volume elements as basis functions for image reconstructions in computed laminography

Spherically symmetric volume elements as basis functions for image reconstructions in computed... BACKGROUND:Laminography is a tomographic technique that allows three-dimensional imaging of flat, elongated objects that stretch beyond the extent of a reconstruction volume. Laminography datasets can be reconstructed using iterative algorithms based on the Kaczmarz method.OBJECTIVE:The goal of this study is to develop a reconstruction algorithm that provides superior reconstruction quality for a challenging class of problems.METHODS:Images are represented in computer memory using coefficients over basis functions, typically piecewise constant functions (voxels). By replacing voxels with spherically symmetric volume elements (blobs) based on generalized Kaiser-Bessel window functions, we obtained an adapted version of the algebraic reconstruction technique.RESULTS:Band-limiting properties of blob functions are beneficial particular in the case of noisy projections and if only a limited number of projections is available. In this case, using blob basis functions improved the full-width-at-half-maximum resolution from 10.2±1.0 to 9.9±0.9 (p value = 2.3·10-4). For the same dataset, the signal-to-noise ratio improved from 16.1 to 31.0. The increased computational demand per iteration is compensated for by a faster convergence rate, such that the overall performance is approximately identical for blobs and voxels.CONCLUSIONS:Despite the higher complexity, tomographic reconstruction from computed laminography data should be implemented using blob basis functions, especially if noisy data is expected. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of X-Ray Science and Technology IOS Press

Spherically symmetric volume elements as basis functions for image reconstructions in computed laminography

Download PDF
14 pages

Loading next page...
 
/lp/ios-press/spherically-symmetric-volume-elements-as-basis-functions-for-image-QXBoJAmEWa

References (29)

Publisher
IOS Press
Copyright
Copyright © 2017 © 2017 – IOS Press and the authors. All rights reserved
ISSN
0895-3996
eISSN
1095-9114
DOI
10.3233/XST-16230
Publisher site
See Article on Publisher Site

Abstract

BACKGROUND:Laminography is a tomographic technique that allows three-dimensional imaging of flat, elongated objects that stretch beyond the extent of a reconstruction volume. Laminography datasets can be reconstructed using iterative algorithms based on the Kaczmarz method.OBJECTIVE:The goal of this study is to develop a reconstruction algorithm that provides superior reconstruction quality for a challenging class of problems.METHODS:Images are represented in computer memory using coefficients over basis functions, typically piecewise constant functions (voxels). By replacing voxels with spherically symmetric volume elements (blobs) based on generalized Kaiser-Bessel window functions, we obtained an adapted version of the algebraic reconstruction technique.RESULTS:Band-limiting properties of blob functions are beneficial particular in the case of noisy projections and if only a limited number of projections is available. In this case, using blob basis functions improved the full-width-at-half-maximum resolution from 10.2±1.0 to 9.9±0.9 (p value = 2.3·10-4). For the same dataset, the signal-to-noise ratio improved from 16.1 to 31.0. The increased computational demand per iteration is compensated for by a faster convergence rate, such that the overall performance is approximately identical for blobs and voxels.CONCLUSIONS:Despite the higher complexity, tomographic reconstruction from computed laminography data should be implemented using blob basis functions, especially if noisy data is expected.

Journal

Journal of X-Ray Science and Technology – IOS Press

Published: Jan 1, 2017

There are no references for this article.