We propose a new algorithm for multivalued discrete tomography, that reconstructs images from few projections by approximating the minimum of a suitably constructed energy function with a deterministic optimization method. We also compare the proposed algorithm to other reconstruction techniques on software phantom images, in order to prove its applicability.

1 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal1 aDi Giamberardino, Paolo1 aIacoviello, Daniela1 aJorge, Renato M Natal1 aTaveres, Joao, Manuel R S uhttps://www.inf.u-szeged.hu/en/publication/an-energy-minimization-reconstruction-algorithm-for-multivalued-discrete-tomography01376nas a2200193 4500008004100000020002200041245010000063210006900163260005500232300001200287520059000299100001900889700002300908700002800931700002400959700002600983700003001009856014301039 2012 eng d a978-0-415-62134-200aHexagonal parallel thinning algorithms based on sufficient conditions for topology preservation0 aHexagonal parallel thinning algorithms based on sufficient condi aLondonbCRC Press - Taylor and Frances Groupc2012 a63 - 683 aThinning is a well-known technique for producing skeleton-like shape features from digital

binary objects in a topology preserving way. Most of the existing thinning algorithms presuppose that the input

images are sampled on orthogonal grids.This paper presents new sufficient conditions for topology preserving

reductions working on hexagonal grids (or triangular lattices) and eight new 2D hexagonal parallel thinning

algorithms that are based on our conditions.The proposed algorithms are capable of producing both medial lines

and topological kernels as well.

We study how the quality of an image reconstructed by a binary tomographic algorithm depends on the direction of the observed object in the scanner, if only a few projections are available. To do so we conduct experiments on a set of software phantoms by reconstructing them form different projection sets using an algorithm based on D.C. programming (a method for minimizing the difference of convex functions), and compare the accuracy of the corresponding reconstructions by two suitable approaches. Based on the experiments, we discuss consequences on applications arising from the field of non-destructive testing, as well.

1 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal1 aBarneva, Reneta, P1 aBrimkov, Valentin, E1 aHauptman, Herbert, A1 aJorge, Renato M Natal1 aTavares, João, Manuel R S uhttps://www.inf.u-szeged.hu/en/publication/direction-dependency-of-a-binary-tomographic-reconstruction-algorithm01336nas a2200217 4500008004100000245006400041210006400105260004400169300001400213490000900227520058400236100002000820700001900840700002300859700002300882700002400905700002500929700002600954700003100980856010701011 2010 eng d00aTopology Preserving Parallel Smoothing for 3D Binary Images0 aTopology Preserving Parallel Smoothing for 3D Binary Images aBuffalo, USAbSpringer VerlagcMay 2010 a287 - 2980 v60263 a

This paper presents a new algorithm for smoothing 3D binary images in a topology preserving way. Our algorithm is a reduction operator: some border points that are considered as extremities are removed. The proposed method is composed of two parallel reduction operators. We are to apply our smoothing algorithm as an iteration-by-iteration pruning for reducing the noise sensitivity of 3D parallel surface-thinning algorithms. An efficient implementation of our algorithm is sketched and its topological correctness for (26,6) pictures is proved. © 2010 Springer-Verlag.

1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aHauptman, Herbert, A1 aJorge, Renato M Natal1 aTavares, João, Manuel R S uhttps://www.inf.u-szeged.hu/en/publication/topology-preserving-parallel-smoothing-for-3d-binary-images