Expectation maximization (EM) algorithms using polar symmetriesfor computed tomography(CT) image reconstruction

We suggest a symmetric-polar pixellation scheme which makes possible a reduction of the computational cost for expectation maximization (EM) iterative algorithms. The proposed symmetric-polar pixellation allows us to deal with 3D images as a whole problem without dividing the 3D problem into 2D slices approach. Performance evaluation of each approach in terms of stability and image quality is presented. Exhaustive comparisons between all approaches were conducted in a 2D based image reconstruction model. From these 2D approaches, that showing the best performances were finally implemented and evaluated in a 3D based image reconstruction model. Comparison to 3D images reconstructed with FBP is also presented. Although the algorithm is presented in the context of computed tomography (CT) image reconstruction, it can be applied to any other tomographic technique as well, due to the fact that the only requirement is a scanning geometry involving measurements of an object under different projection angles. Real data have been acquired with a small animal (CT) scanner to verify the proposed mathematical description of the CT system.This work was supported by the Spanish Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica (I+D+I) under Grant, FIS2010-21216-CO2-01, Valencian Local Government under Grant Nos. PROMETEO 2008/114 and APOSTD/2010/012. The authors would like to thank Brennan Holt for checking and correcting the text.Rodríguez Álvarez, MJ.; Soriano Asensi, A.; Iborra Carreres, A.; Sánchez Martínez, F.; González Martínez, AJ.; Conde, P.; Hernández Hernández, L.... (2013). Expectation maximization (EM) algorithms using polar symmetriesfor computed tomography(CT) image reconstruction. Computers in Biology and Medicine. 43(8):1053-1061. https://doi.org/10.1016/j.compbiomed.2013.04.015S1053106143

Accelerating Neutron Tomography experiments through Artificial Neural Network based reconstruction

Neutron Tomography (NT) is a non-destructive technique to investigate the inner structure of a wide range of objects and, in some cases, provides valuable results in comparison to the more common X-ray imaging techniques. However, NT is time consuming and scanning a set of similar objects during a beamtime leads to data redundancy and long acquisition times. Nowadays NT is unfeasible for quality checking study of large quantities of similar objects. One way to decrease the total scan time is to reduce the number of projections. Analytical reconstruction methods are very fast but under this condition generate streaking artifacts in the reconstructed images. Iterative algorithms generally provide better reconstruction for limited data problems, but at the expense of longer reconstruction time. In this study, we propose the recently introduced Neural Network Filtered Back-Projection (NN-FBP) method to optimize the time usage in NT experiments. Simulated and real neutron data were used to assess the performance of the NN-FBP method as a function of the number of projections. For the first time a machine learning based algorithm is applied and tested for NT image reconstruction problem. We demonstrate that the NN-FBP method can reliably reduce acquisition and reconstruction times and it outperforms conventional reconstruction methods used in NT, providing high image quality for limited datasets

Phase relations in Ga₂X₃-GaY₃ systems (X=Se,Te; Y=Cl,Br,I) — Crystal growth, structural relations and optical absorption of intermediate compounds GaXY

The systems Ga2X3-GaY3 (X=Se,Te; Y=Cl,Br,I) are quasibinary and include the intermediate compounds GaXY with incongruent melting behaviour. Crystals for structural and optical investigations were obtained by annealing. GaTeBr (orth., Pnnm; a=607, b=1518, c=413 pm; dx=4.48 g/cm3; Z=4) is an isotype of GaTeCl, with a tetrahedral layer structure and Ga-Te-linking of the black phosphorous type; the remaining compounds are expected to form an isotypic series, with a crystal structure not yet determined. Optical absorption edges range from 2.55 eV (GaTeI) to 4.20 eV (GaSeCl)