Spherically symmetric volume elements as basis functions for image reconstructions in computed laminography
In Journal of X-Ray Science and Technology, IOS Press, volume 25, number 4, pages o.A., 2017.
textcopyright 2017 - IOS Press and the authors. All rights reserved. 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 funct ions, 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.
Computed laminography,Kaiser-Bessel window,SART,blob basis function,simultaneous algebraic reconstruction technique