01429nas a2200157 4500008004100000245008400041210006900125260002900194300001200223490000600235520084300241100002701084700002001111700001601131856012401147 2015 eng d00aDiscrete tomographic reconstruction via adaptive weighting of gradient descents0 aDiscrete tomographic reconstruction via adaptive weighting of gr bTaylor&FranciscFeb 2014 a101-1090 v33 a
Discrete tomography (DT) is a set of tools for reconstructing the inner structure of objects consisting of only few different homogeneous materials. We propose a new method for multivalued DT, which performs the reconstruction as an energy minimisation task. For this algorithm, we define an energy function that can mathematically formulate the reconstruction task, and design a novel optimisation process for approximating the minima of this energy function. We validate the algorithm by comparing its performance with other cutting-edge reconstruction algorithms from the literature. We show that our method can compete with the currently used reconstruction techniques and under certain circumstances (e.g. with a low number of projections, or when the projection data are affected by random noise) it can even outperform them.
1 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal uhttps://www.inf.u-szeged.hu/publication/discrete-tomographic-reconstruction-via-adaptive-weighting-of-gradient-descents00771nas a2200181 4500008003900000245010000039210007500139260008600214300001100300100002700311700002000338700001900358700001900377700002000396700001800416700002300434856013200457 2015 d00aIdőskori makula degeneráció kvantitatív jellemzése SD-OCT képek automatikus elemzésével0 aIdőskori makula degeneráció kvantitatív jellemzése SDOCT képek a aVeszprém, HungarybNeumann János Számítógép-tudományi TársaságcNov 2015 a43-48.1 aVarga, László Gábor1 aKatona, Melinda1 aGrósz, Tamás1 aDombi, József1 aKovács, Attila1 aDégi, Rózsa1 aNyúl, László, G uhttps://www.inf.u-szeged.hu/publication/idoskori-makula-degeneracio-kvantitativ-jellemzese-sd-oct-kepek-automatikus-elemzesevel00833nas a2200253 4500008004100000022002200041245005600063210005500119260005200174300001200226100002000238700001800258700001700276700001600293700002000309700002800329700002300357700001900380700002700399700001900426700001800445700002400463856009200487 2014 hun d a978-963-473-712-400aKépfeldolgozás a szegedi informatikus-képzésben0 aKépfeldolgozás a szegedi informatikusképzésben aDebrecen, HungarybUniversity of Debrecenc2014 a667-6751 aBalázs, Péter1 aKatona, Endre1 aKato, Zoltan1 aNagy, Antal1 aNémeth, Gábor1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aTanacs, Attila1 aVarga, László Gábor1 aKunkli, Roland1 aPapp, Ildikó1 aRutkovszky, Edéné uhttps://www.inf.u-szeged.hu/publication/kepfeldolgozas-a-szegedi-informatikus-kepzesben01716nas a2200157 4500008004100000020001400041245007000055210006900125260000900194520115400203100002701357700002801384700001601412700002001428856011001448 2014 eng d a1077-314200aLocal and global uncertainty in binary tomographic reconstruction0 aLocal and global uncertainty in binary tomographic reconstructio c20143 aIn binary tomography the goal is to reconstruct the innerstructure of homogeneous objects from their projections. This is usually required from a low number of projections, which are also likely to be affected by noise and measurement errors. In general, the distorted and incomplete projection data holds insufficient information for the correct reconstruction of the original object. In this paper, we describe two methods for approximating the local uncertainty of the reconstructions, i.e., identifying how the information stored in the projections determine each part of the reconstructed image. These methods can measure the uncertainty of the reconstruction without any knowledge from the original object itself. Moreover, we provide a global uncertainty measure that can assess the information content of a projection set and predict the error to be expected in the reconstruction of a homogeneous object. We also give an experimental evaluation of our proposed methods, mention some of their possible applications, and describe how the uncertainty measure can be used to improve the performance of the DART reconstruction algorithm.
1 aVarga, László Gábor1 aNyúl, László, Gábor1 aNagy, Antal1 aBalázs, Péter uhttps://www.inf.u-szeged.hu/publication/local-and-global-uncertainty-in-binary-tomographic-reconstruction00613nas a2200145 4500008004100000245009200041210007500133260003800208300001400246100002700260700002000287700001600307700002100323856012300344 2013 eng d00aGradiens módszerek automatikus súlyozásán alapuló diszkrét tomográfiai eljárás0 aGradiens módszerek automatikus súlyozásán alapuló diszkrét tomog aVeszprémbNJSZT-KÉPAFcJan 2013 a210 - 2231 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal1 aCzúni, László uhttps://www.inf.u-szeged.hu/publication/gradiens-modszerek-automatikus-sulyozasan-alapulo-diszkret-tomografiai-eljaras01266nas a2200169 4500008004100000245005900041210005900100260004300159300001400202520067100216100002700887700002800914700001600942700002000958700001900978856009900997 2013 eng d00aLocal uncertainty in binary tomographic reconstruction0 aLocal uncertainty in binary tomographic reconstruction aCalgarybIASTED - Acta PresscFeb 2013 a490 - 4963 aWe describe a new approach for the uncertainty problem arisingin the field of discrete tomography, when the low number of projections does not hold enough information for an accurate, and reliable reconstruction. In this case the lack of information results in uncertain parts on the reconstructed image which are not determined by the projections and cannot be reliably reconstructed without additional information. We provide a method that can approximate this local uncertainty of reconstructions, and show how each pixel of the reconstructed image is determined by a set of given projections. We also give experimental results for validating our approach.
1 aVarga, László Gábor1 aNyúl, László, Gábor1 aNagy, Antal1 aBalázs, Péter1 aKampel, Martin uhttps://www.inf.u-szeged.hu/publication/local-uncertainty-in-binary-tomographic-reconstruction01133nas a2200193 4500008004100000245008800041210006900129260005500198300001400253520037300267100002700640700002000667700001600687700002800703700002400731700002600755700003000781856012800811 2012 eng d00aAn energy minimization reconstruction algorithm for multivalued discrete tomography0 aenergy minimization reconstruction algorithm for multivalued dis aLondonbCRC Press - Taylor and Frances Groupc2012 a179 - 1853 aWe 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/publication/an-energy-minimization-reconstruction-algorithm-for-multivalued-discrete-tomography00608nas a2200133 4500008004100000245009200041210006900133260007000202300000700272100002700279700002000306700001600326856013200342 2012 eng d00aA novel optimization-based reconstruction algorithm for multivalued discrete tomography0 anovel optimizationbased reconstruction algorithm for multivalued aSzegedbUniversity of Szeged, Institute of InformaticscJune 2012 a571 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal uhttps://www.inf.u-szeged.hu/publication/a-novel-optimization-based-reconstruction-algorithm-for-multivalued-discrete-tomography00581nas a2200133 4500008004100000245008700041210006900128260004800197300001200245100002700257700002000284700001600304856012700320 2012 eng d00aAn optimization-based reconstruction algorithm for multivalued discrete tomography0 aoptimizationbased reconstruction algorithm for multivalued discr aVeszprémbUniversity of PannoniacDec 2012 a39 - 401 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal uhttps://www.inf.u-szeged.hu/publication/an-optimization-based-reconstruction-algorithm-for-multivalued-discrete-tomography01423nas a2200169 4500008004100000020001400041245007300055210006900128260001300197300001400210490000700224520084600231100002701077700002001104700001601124856011301140 2011 eng d a1524-070300aDirection-dependency of binary tomographic reconstruction algorithms0 aDirectiondependency of binary tomographic reconstruction algorit cNov 2011 a365 - 3750 v733 aIn this work we study the relation between the quality of a binary tomographic reconstruction and the choice of angles of the projections. We conduct experiments on a set of software phantoms by reconstructing them from different projection sets using three different discrete tomography reconstruction algorithms, and compare the accuracy of the corresponding reconstructions with suitable approaches. To validate our results for possible real-world applications, we conduct the experiments by adding random noise of different characteristics to the simulated projection data, and by applying small topological changes on the phantom images as well. In addition, we also discuss some consequences of the angle-selection dependency and possible practical applications arising from the field of non-destructive testing, too.
1 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal uhttps://www.inf.u-szeged.hu/publication/direction-dependency-of-binary-tomographic-reconstruction-algorithms01790nas a2200169 4500008004100000020001400041245005700055210005700112260006500169300001400234490000700248520120500255100002701460700002001487700001601507856009701523 2011 eng d a0324-721X00aProjection selection dependency in binary tomography0 aProjection selection dependency in binary tomography aSzegedbUniversity of Szeged, Institute of Informaticsc2011 a167 - 1870 v203 aIt has already been shown that the choice of projection angles can significantly influence the quality of reconstructions in discrete tomography. In this contribution we summarize and extend the previous results by explaining and demonstrating tile effects of projection selection dependency, in a set of experimental software tests. We perform reconstructions of software phantoms, by using different binary tomography reconstruction algorithms, from different equiangular and non-equiangular projections sets, under various conditions (i.e., when the objects to be reconstructed undergo slight topological changes, or the projection data is affected by noise) and compare the results with suitable approaches. Based on our observations, we reveal regularities in the resulting data and discuss possible consequences of such projection selection dependency in binary tomography.
1 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal uhttps://www.inf.u-szeged.hu/publication/projection-selection-dependency-in-binary-tomography00552nas a2200157 4500008004100000245005900041210005900100260002800159300001300187100002700200700002000227700001600247700001700263700002300280856009100303 2011 hun d00aVetületi irányfüggőség a bináris tomográfiában0 aVetületi irányfüggőség a bináris tomográfiában aSzegedbNJSZTcJan 2011 a92 - 1051 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal1 aKato, Zoltan1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/vetuleti-iranyfuggoseg-a-binaris-tomografiaban01535nas a2200217 4500008004100000020002200041245007400063210006900137260004800206300001400254520074200268100002701010700002001037700001601057700002301073700002501096700002501121700002601146700003101172856011401203 2010 eng d a978-3-642-12711-300aDirection-dependency of a binary tomographic reconstruction algorithm0 aDirectiondependency of a binary tomographic reconstruction algor aBuffalo, NY, USAbSpringer VerlagcMay 2010 a242 - 2533 a
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/publication/direction-dependency-of-a-binary-tomographic-reconstruction-algorithm00533nas a2200133 4500008004100000245006500041210006500106260005300171300000700224100002700231700002000258700001600278856010500294 2010 eng d00aObject rotation effects on binary tomographic reconstruction0 aObject rotation effects on binary tomographic reconstruction aSzeged, HungarybUniversity of SzegedcJune 2010 a761 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal uhttps://www.inf.u-szeged.hu/publication/object-rotation-effects-on-binary-tomographic-reconstruction00683nas a2200193 4500008004100000245006000041210006000101260005000161300001400211100002700225700002000252700001600272700002500288700001400313700002200327700001700349700002100366856010200387 2010 eng d00aProjection selection algorithms for discrete tomography0 aProjection selection algorithms for discrete tomography aSydney, Australia bSpringer VerlagcDec 2010 a390 - 4011 aVarga, László Gábor1 aBalázs, Péter1 aNagy, Antal1 aBlanc-Talon, Jacques1 aBone, Don1 aPhilips, Wilfried1 aPopescu, Dan1 aScheunders, Paul uhttps://www.inf.u-szeged.hu/publication/projection-selection-algorithms-for-discrete-tomography-0