00528nas a2200145 4500008004100000245005100041210005100092260004600143300001300189100002300202700002300225700002400248700001900272856009100291 2014 eng d00aEquivalent 2D sequential and parallel thinning0 aEquivalent 2D sequential and parallel thinning aBrno, Czech RepublicbSpringer cMay 2014 a91 - 1001 aPalágyi, Kálmán1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aŠlapal, Josef uhttps://www.inf.u-szeged.hu/publication/equivalent-2d-sequential-and-parallel-thinning01195nas a2200205 4500008004100000020002200041022002200063245007200085210006900157260005100226300001400277490000900291520053000300100001900830700002300849700002300872700002400895700001900919856005100938 2014 eng d a978-3-319-07147-3 a978-3-319-07147-300aSufficient conditions for general 2D operators to preserve topology0 aSufficient conditions for general 2D operators to preserve topol aMay 2014, Brno, Czech RepublicbSpringerc2014 a101 - 1120 v84663 a
An important requirement for various applications of binary image processing is to preserve topology. This issue has been earlier studied for two special types of image operators, namely, reductions and additions, and there have been some sufficient conditions proposed for them. In this paper, as an extension of those earlier results, we give novel sufficient criteria for general operators working on 2D pictures.
1 aKardos, Péter1 aPalágyi, Kálmán1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aŠlapal, Josef uhttp://dx.doi.org/10.1007/978-3-319-07148-0_1000593nas a2200145 4500008004100000245008100041210007800122260003800200300001400238100002000252700002000272700002300292700002100315856011100336 2013 eng d00aBináris képek rekonstrukciója két vetületből és morfológiai vázból0 aBináris képek rekonstrukciója két vetületből és morfológiai vázb aVeszprémbNJSZT-KÉPAFcJan 2013 a182 - 1931 aHantos, Norbert1 aBalázs, Péter1 aPalágyi, Kálmán1 aCzúni, László uhttps://www.inf.u-szeged.hu/publication/binaris-kepek-rekonstrukcioja-ket-vetuletbol-es-morfologiai-vazbol00433nas a2200133 4500008004100000020001400041245005100055210005100106260000900157300001000166490000700176100002300183856009300206 2013 eng d a0324-721X00aConference of PhD Students in Computer Science0 aConference of PhD Students in Computer Science c2013 a1 - 30 v211 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/conference-of-phd-students-in-computer-science-001213nas a2200157 4500008004100000020002200041245006900063210006900132260004300201300001200244520065200256100002300908700002600931700003100957856006700988 2013 eng d a978-3-642-41821-100aDeletion Rules for Equivalent Sequential and Parallel Reductions0 aDeletion Rules for Equivalent Sequential and Parallel Reductions aBerlin; HeidelbergbSpringercNov 2013 a17 - 243 a
A reduction operator transforms a binary picture only by changing some black points to white ones, which is referred to as deletion. Sequential reductions may delete just one point at a time, while parallel reductions can alter a set of points simultaneously. Two reductions are called equivalent if they produce the same result for each input picture. This work lays a bridge between the parallel and the sequential strategies. A class of deletion rules are proposed that provide 2D parallel reductions being equivalent to sequential reductions. Some new sufficient conditions for topology-preserving parallel reductions are also reported.
1 aPalágyi, Kálmán1 aRuiz-Shulcloper, Jose1 aSanniti di Baja, Gabriella uhttp://link.springer.com/chapter/10.1007%2F978-3-642-41822-8_301451nas a2200133 4500008004100000245007100041210006900112260005200181300001200233520092000245100002301165700001801188856011101206 2013 eng d00aParallel 3D 12-Subiteration Thinning Algorithms Based on Isthmuses0 aParallel 3D 12Subiteration Thinning Algorithms Based on Isthmuse aHeidelberg; New YorkbSpringer VerlagcJul 2013 a87 - 983 aThinning is an iterative object reduction to obtain skeleton-like shape features of volumetric binary objects. Conventional thinning algorithms preserve endpoints to provide important geometric information relative to the object to be represented. An alternative strategy is also proposed that accumulates isthmuses (i.e., generalization of curve and surface interior points as skeletal elements). This paper presents two parallel isthmus-based 3D thinning algorithms that are capable of producing centerlines and medial surfaces. The strategy which is used is called subiteration-based or directional: each iteration step is composed of 12 subiterations each of which are executed in parallel. The proposed algorithms make efficient implementation possible and their topological correctness is guaranteed.
1 aPalágyi, Kálmán1 aBebis, George uhttps://www.inf.u-szeged.hu/publication/parallel-3d-12-subiteration-thinning-algorithms-based-on-isthmuses00454nas a2200133 4500008004100000245004100041210004100082260003800123300001400161100002000175700002300195700002100218856008100239 2013 eng d00aParallel Thinning Based on Isthmuses0 aParallel Thinning Based on Isthmuses aVeszprémbNJSZT-KÉPAFcJan 2013 a512 - 5251 aNémeth, Gábor1 aPalágyi, Kálmán1 aCzúni, László uhttps://www.inf.u-szeged.hu/publication/parallel-thinning-based-on-isthmuses01135nas a2200157 4500008004100000020002300041245004500064210004500109260002900154300001400183520063300197100001900830700002300849700002000872856008500892 2013 eng d a978-1-4799-1543-9 00aParallel Thinning on the Triangular Grid0 aParallel Thinning on the Triangular Grid aBudapestbIEEEcDec 2013 a277 - 2823 a
One of the fundamental issues of human and computational cognitive psychology is pattern or shape recognition. Various applications in image processing and computer vision rely on skeleton-like shape features A possible technique for extracting these feautures is thinning. Although the majority of 2D thinning algorithms work on digital pictures sampled onthe conventional square grid, the role of some non-conventional grids, like the hexagonal and triangular grid, are of increasing importance as well. In this paper we propose numerous topolgy preserving parallel thinning algorithms that work on the triangular grid.
1 aKardos, Péter1 aPalágyi, Kálmán1 aBaranyi, Péter uhttps://www.inf.u-szeged.hu/publication/parallel-thinning-on-the-triangular-grid01597nas a2200145 4500008004100000245008200041210006900123260004300192300001400235520102400249100001901273700002301292700001401315856012201329 2013 eng d00aSufficient Conditions for Topology Preserving Additions and General Operators0 aSufficient Conditions for Topology Preserving Additions and Gene aCalgarybIASTED - Acta PresscFeb 2013 a107 - 1143 aTopology preservation is a crucial issue of digital topology. Various applications of binary image processing rest on topology preserving operators. Earlier studies in this topic mainly concerned with reductions (i.e., operators that only delete some object points from binary images), as they form the basis for thinning algorithms. However, additions (i.e., operators that never change object points) also play important role for the purpose of generating discrete Voronoi diagrams or skeletons by influence zones (SKIZ). Furthermore, the use of general operators that may both add and delete some points to and from objects in pictures are suitable for contour smoothing. Therefore, in this paper we present some new sufficient conditions for topology preserving reductions, additions, and general operators. Two additions for 2D and 3D contour smoothing are also reported.
1 aKardos, Péter1 aPalágyi, Kálmán1 aLinsen, L uhttps://www.inf.u-szeged.hu/publication/sufficient-conditions-for-topology-preserving-additions-and-general-operators01101nas a2200181 4500008004100000245007200041210006700113260002800180300001400208520046000222100001900682700002300701700002200724700002100746700002000767700002200787856011000809 2013 eng d00aOn Topology Preservation in Triangular, Square, and Hexagonal Grids0 aTopology Preservation in Triangular Square and Hexagonal Grids aTriestebIEEEcSep 2013 a782 - 7873 a
There are three possible partitionings of the continuous plane into regular polygons that leads to triangular, square, and hexagonal grids. The topology of the square grid is fairly well-understood, but it cannot be said of the remaining two regular sampling schemes. This paper presents a general characterization of simple pixels and some simplified sufficient conditions for topology-preserving operators in all the three types of regular grids.
1 aKardos, Péter1 aPalágyi, Kálmán1 aRamponi, Giovanni1 aLončarić, Sven1 aCarini, Alberto1 aEgiazarian, Karen uhttps://www.inf.u-szeged.hu/publication/on-topology-preservation-in-triangular-square-and-hexagonal-grids00513nas a2200133 4500008004100000245006100041210006100102260003800163300001400201100001900215700002300234700002100257856010100278 2013 eng d00aTopology preserving parallel thinning on hexagonal grids0 aTopology preserving parallel thinning on hexagonal grids aVeszprémbNJSZT-KÉPAFcJan 2013 a250 - 2641 aKardos, Péter1 aPalágyi, Kálmán1 aCzúni, László uhttps://www.inf.u-szeged.hu/publication/topology-preserving-parallel-thinning-on-hexagonal-grids01108nas a2200157 4500008004100000020001400041245004300055210004200098260002700140300001600167490000700183520064200190100001900832700002300851856007600874 2013 eng d a0020-716000aTopology-preserving hexagonal thinning0 aTopologypreserving hexagonal thinning bTaylor & Francisc2013 a1607 - 16170 v903 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 work on input images that are sampled on orthogonal grids; however, it is also possible to perform thinning on hexagonal grids (or triangular lattices). In this paper, we point out to the main similarities and differences between the topological properties of these two types of sampling schemes. We give various characterizations of simple points and present some new sufficient conditions for topology-preserving reductions working on hexagonal grids.
1 aKardos, Péter1 aPalágyi, Kálmán uhttp://www.tandfonline.com/doi/abs/10.1080/00207160.2012.724198#preview01225nas a2200205 4500008004100000245005500041210005500096260005200151300001400203490000900217520059400226100002000820700002300840700002500863700002200888700001700910700002100927700002000948856005100968 2012 eng d00a3D Parallel Thinning Algorithms Based on Isthmuses0 a3D Parallel Thinning Algorithms Based on Isthmuses aBrno, Czech RepublicbSpringer VerlagcSep 2012 a325 - 3350 v75173 aThinning is a widely used technique to obtain skeleton-like shape features (i.e., centerlines and medial surfaces) from digital binary objects. Conventional thinning algorithms preserve endpoints to provide important geometric information relative to the object to be represented. An alternative strategy is also proposed that preserves isthmuses (i.e., generalization of curve/surface interior points). In this paper we present ten 3D parallel isthmus-based thinning algorithm variants that are derived from some sufficient conditions for topology preserving reductions.
1 aNémeth, Gábor1 aPalágyi, Kálmán1 aBlanc-Talon, Jacques1 aPhilips, Wilfried1 aPopescu, Dan1 aScheunders, Paul1 aZemčík, Pavel uhttp://dx.doi.org/10.1007/978-3-642-33140-4_2901221nas a2200181 4500008004100000245007800041210006900119260008200188300001400270520050400284100002000788700002000808700002300828700002300851700002500874700002200899856011800921 2012 eng d00aBinary image reconstruction from two projections and skeletal information0 aBinary image reconstruction from two projections and skeletal in aBerlin; Heidelberg; New York; London; Paris; TokyobSpringer VerlagcNov 2012 a263 - 2733 aIn binary tomography, the goal is to reconstruct binary images from a small set of their projections. However, especially when only two projections are used, the task can be extremely underdetermined. In this paper, we show how to reduce ambiguity by using the morphological skeleton of the image as a priori. Three different variants of our method based on Simulated Annealing are tested using artificial binary images, and compared by reconstruction time and error. © 2012 Springer-Verlag.
1 aHantos, Norbert1 aBalázs, Péter1 aPalágyi, Kálmán1 aBarneva, Reneta, P1 aBrimkov, Valentin, E1 aAggarwal, Jake, K uhttps://www.inf.u-szeged.hu/publication/binary-image-reconstruction-from-two-projections-and-skeletal-information00601nas a2200145 4500008004100000245007100041210006900112260006000181300000700241490003300248100002000281700002000301700002300321856011100344 2012 eng d00aBinary tomography using two projections and morphological skeleton0 aBinary tomography using two projections and morphological skelet aSzegedbUniv Szeged Institute of InformaticscJune 2012 a200 vVolume of Extended Abstracts1 aHantos, Norbert1 aBalázs, Péter1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/binary-tomography-using-two-projections-and-morphological-skeleton01373nas a2200193 4500008004100000020002200041245010000063210006900163260005500232300001200287520059000299100001900889700002300908700002800931700002400959700002600983700003001009856014001039 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.
Thinning as a layer-by-layer reduction is a frequently used technique for skeletonization. Sequential thinning algorithms usually suffer from the drawback of being order-dependent, i.e., their results depend on the visiting order of object points. Earlier order-independent sequential methods are based on the conventional thinning schemes that preserve endpoints to provide relevant geometric information of objects. These algorithms can generate centerlines in 2D and medial surfaces in 3D. This paper presents an alternative strategy for order-independent thinning which follows an approach, proposed by Bertrand and Couprie, which accumulates so-called isthmus points. The main advantage of this order-independent strategy over the earlier ones is that it makes also possible to produce centerlines of 3D objects.
1 aKardos, Péter1 aPalágyi, Kálmán1 aPetrou, M1 aSappa, A, D1 aTriantafyllidis, A G uhttp://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=73601390nas a2200157 4500008004100000020002300041245004700064210004400111260003400155300001400189520091000203100001901113700002301132700000501155856007201160 2012 eng d a978-1-4673-5187-4 00aOn Order–Independent Sequential Thinning0 aOrder–Independent Sequential Thinning aKosice, Slovakia bIEEEc2012 a149 - 1543 aThe visual world composed by the human and computational cognitive systems strongly relies on shapes of objects. Skeleton is a widely applied shape feature that plays an important role in many fields of image processing, pattern recognition, and computer vision. Thinning is a frequently used, iterative object reduction strategy for skeletonization. Sequential thinning algorithms, which are based on contour tracking, delete just one border point at a time. Most of them have the disadvantage of order-dependence, i.e., for dissimilar visiting orders of object points, they may generate different skeletons. In this work, we give a survey of our results on order-independent thinning: we introduce some sequential algorithms that produce identical skeletons for any visiting orders, and we also present some sufficient conditions for the order-independence of templatebased sequential algorithms.
1 aKardos, Péter1 aPalágyi, Kálmán1 a uhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=641330500552nas a2200133 4500008004100000245007500041210006900116260004800185300000700233100002000240700002000260700002300280856011500303 2012 eng d00aSolving binary tomography from morphological skeleton via optimization0 aSolving binary tomography from morphological skeleton via optimi aVeszprémbUniversity of PannoniacDec 2012 a421 aHantos, Norbert1 aBalázs, Péter1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/solving-binary-tomography-from-morphological-skeleton-via-optimization01134nas a2200181 4500008004100000020002200041245006400063210006100127260004700188300001400235520048800249100001900737700002300756700002300779700002400802700002200826856010400848 2012 eng d a978-3-642-34731-300aOn topology preservation for triangular thinning algorithms0 atopology preservation for triangular thinning algorithms aAustin, TX, USAbSpringer VerlagcNov 2012 a128 - 1423 aThinning is a frequently used strategy to produce skeleton-like shape features of binary objects. One of the main problems of parallel thinning is to ensure topology preservation. Solutions to this problem have been already given for the case of orthogonal and hexagonal grids. This work introduces some characterizations of simple pixels and some sufficient conditions for parallel thinning algorithms working on triangular grids (or hexagonal lattices) to preserve topology.
1 aKardos, Péter1 aPalágyi, Kálmán1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aAggarwal, Jake, K uhttps://www.inf.u-szeged.hu/publication/on-topology-preservation-for-triangular-thinning-algorithms01191nas a2200181 4500008004100000020002200041245005600063210005600119260002600175300001400201520058900215100002300804700002000827700001900847700002400866700002300890856009600913 2012 eng d a978-94-007-4173-700aTopology Preserving Parallel 3D Thinning Algorithms0 aTopology Preserving Parallel 3D Thinning Algorithms bSpringer-Verlagc2012 a165 - 1883 aA widely used technique to obtain skeletons of binary objects is thinning, which is an iterative layer-by-layer erosion in a topology preserving way. Thinning in 3D is capable of extracting various skeleton-like shape descriptors (i.e., centerlines, medial surfaces, and topological kernels). This chapter describes a family of new parallel 3D thinning algorithms for (26, 6) binary pictures. The reported algorithms are derived from some sufficient conditions for topology preserving parallel reduction operations, hence their topological correctness is guaranteed.
1 aPalágyi, Kálmán1 aNémeth, Gábor1 aKardos, Péter1 aBrimkov, Valentin E1 aBarneva, Reneta, P uhttps://www.inf.u-szeged.hu/publication/topology-preserving-parallel-3d-thinning-algorithms01310nas a2200181 4500008004100000020002300041245006600064210006500130260004000195300001400235520067200249100002000921700002300941700002100964700002200985700001501007856010601022 2011 eng d a978-1-4577-0841-1 00a2D Parallel Thinning Algorithms Based on Isthmus-Preservation0 a2D Parallel Thinning Algorithms Based on IsthmusPreservation aDubrovnik, CroatiabIEEEcSep 2011 a585 - 5903 aSkeletons are widely used shape descriptors which summarize the general form of binary objects. A technique to obtain skeletons is the thinning, that is an iterative layer-by-layer erosion in a topology-preserving way. Conventional thinning algorithms preserve line endpoints to provide important geometric information relative to the object to be represented. Bertrand and Couprie proposed an alternative strategy by accumulating isthmus points that are line interior points. In this paper we present six new 2D parallel thinning algorithms that are derived from some sufficient conditions for topology preserving reductions and based on isthmus-preservation.
1 aNémeth, Gábor1 aPalágyi, Kálmán1 aLončarić, Sven1 aRamponi, Giovanni1 aSersic, D. uhttps://www.inf.u-szeged.hu/publication/2d-parallel-thinning-algorithms-based-on-isthmus-preservation01305nas a2200169 4500008004100000020001400041245009600055210006900151260006500220300001400285490000700299520063100306100002000937700001900957700002300976856013600999 2011 eng d a0324-721X00a2D parallel thinning and shrinking based on sufficient conditions for topology preservation0 a2D parallel thinning and shrinking based on sufficient condition aSzegedbUniversity of Szeged, Institute of Informaticsc2011 a125 - 1440 v203 aThinning and shrinking algorithms, respectively, are capable of extracting medial lines and topological kernels from digital binary objects in a topology preserving way. These topological algorithms are composed of reduction operations: object points that satisfy some topological and geometrical constraints are removed until stability is reached. In this work we present some new sufficient conditions for topology preserving parallel reductions and fiftyfour new 2D parallel thinning and shrinking algorithms that are based on our conditions. The proposed thinning algorithms use five characterizations of endpoints.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/2d-parallel-thinning-and-shrinking-based-on-sufficient-conditions-for-topology-preservation00572nas a2200169 4500008004100000245005500041210005500096260002800151300001400179100001900193700002100212700002100233700001700254700001700271700002300288856009100311 2011 eng d00a3D objektumok lineáris deformációinak becslése0 a3D objektumok lineáris deformációinak becslése aSzegedbNJSZTcJan 2011 a471 - 4801 aTanacs, Attila1 aLindblad, Joakim1 aSladoje, Nataša1 aKato, Zoltan1 aKato, Zoltan1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/3d-objektumok-linearis-deformacioinak-becslese00524nas a2200145 4500008004100000245008900041210007300130260002800203300001400231100001900245700001700264700001700281700002300298856005700321 2011 eng d00aAffin Puzzle: Deformált objektumdarabok helyreállítása megfeleltetések nélkül0 aAffin Puzzle Deformált objektumdarabok helyreállítása megfelelte aSzegedbNJSZTcJan 2011 a206 - 2201 aDomokos, Csaba1 aKato, Zoltan1 aKato, Zoltan1 aPalágyi, Kálmán uhttp://www.inf.u-szeged.hu/kepaf2011/pdfs/S05_03.pdf00582nas a2200145 4500008004100000245008300041210007500124260002800199300001400227100001800241700002000259700001700279700002300296856011700319 2011 eng d00aBináris tomográfiai rekonstrukció objektum alapú evolúciós algoritmussal0 aBináris tomográfiai rekonstrukció objektum alapú evolúciós algor aSzegedbNJSZTcJan 2011 a117 - 1271 aGara, Mihály1 aBalázs, Péter1 aKato, Zoltan1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/binaris-tomografiai-rekonstrukcio-objektum-alapu-evolucios-algoritmussal00427nas a2200133 4500008004100000020001400041245005100055210005100106260000900157300000600166490000700172100002300179856009100202 2011 eng d a0324-721X00aConference of PhD Students in Computer Science0 aConference of PhD Students in Computer Science c2011 a30 v201 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/conference-of-phd-students-in-computer-science00689nas a2200205 4500008004100000245009700041210008000138260002800218300001400246100001700260700001700277700001600294700001700310700001900327700002000346700002000366700001700386700002300403856005700426 2011 eng d00aÉlősejt szegmentálása gráfvágás segítségével fluoreszcenciás mikroszkóp képeken0 aÉlősejt szegmentálása gráfvágás segítségével fluoreszcenciás mik aSzegedbNJSZTcJan 2011 a319 - 3281 aLesko, Milan1 aKato, Zoltan1 aNagy, Antal1 aGombos, Imre1 aTörök, Zsolt1 aVígh, László1 aVígh, László1 aKato, Zoltan1 aPalágyi, Kálmán uhttp://www.inf.u-szeged.hu/kepaf2011/pdfs/S08_02.pdf01818nas a2200217 4500008004100000020002200041245008300063210006900146260004500215300001200260520102200272100002001294700001901314700002301333700002201356700002301378700002401401700002801425700002401453856012301477 2011 eng d a978-3-642-21072-300aA family of topology-preserving 3d parallel 6-subiteration thinning algorithms0 afamily of topologypreserving 3d parallel 6subiteration thinning aMadrid, SpainbSpringer VerlagcMay 2011 a17 - 303 aThinning is an iterative layer-by-layer erosion until only the skeleton-like shape features of the objects are left. This paper presents a family of new 3D parallel thinning algorithms that are based on our new sufficient conditions for 3D parallel reduction operators to preserve topology. The strategy which is used is called subiteration-based: each iteration step is composed of six parallel reduction operators according to the six main directions in 3D. The major contributions of this paper are: 1) Some new sufficient conditions for topology preserving parallel reductions are introduced. 2) A new 6-subiteration thinning scheme is proposed. Its topological correctness is guaranteed, since its deletion rules are derived from our sufficient conditions for topology preservation. 3) The proposed thinning scheme with different characterizations of endpoints yields various new algorithms for extracting centerlines and medial surfaces from 3D binary pictures. © 2011 Springer-Verlag Berlin Heidelberg.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aAggarwal, Jake, K1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aKoroutchev, Kostadin, N1 aKorutcheva, Elka, R uhttps://www.inf.u-szeged.hu/publication/a-family-of-topology-preserving-3d-parallel-6-subiteration-thinning-algorithms00520nas a2200157 4500008004100000245006000041210006000101260002800161300001400189100001900203700002000222700002300242700001700265700002300282856005700305 2011 eng d00aIterációnkénti simítással kombinált vékonyítás0 aIterációnkénti simítással kombinált vékonyítás aSzegedbNJSZTcJan 2011 a174 - 1891 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán1 aKato, Zoltan1 aPalágyi, Kálmán uhttp://www.inf.u-szeged.hu/kepaf2011/pdfs/S05_01.pdf00326nam a2200097 4500008004100000245003300041210003300074260002800107100002300135856007000158 2011 eng d00aKépfeldolgozás haladóknak0 aKépfeldolgozás haladóknak aBudapestbTypotexc20111 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/kepfeldolgozas-haladoknak00559nas a2200145 4500008004100000245007200041210007200113260002800185300001400213100002000227700002000247700001700267700002300284856010600307 2011 eng d00aMediánszűrés alkalmazása algebrai rekonstrukciós módszerekben0 aMediánszűrés alkalmazása algebrai rekonstrukciós módszerekben aSzegedbNJSZTcJan 2011 a106 - 1161 aHantos, Norbert1 aBalázs, Péter1 aKato, Zoltan1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/medianszures-alkalmazasa-algebrai-rekonstrukcios-modszerekben01090nas a2200157 4500008004100000245006600041210006500107260004900172300001400221520051000235100001900745700002300764700002300787700001600810856010600826 2011 eng d00aOrder-independent sequential thinning in arbitrary dimensions0 aOrderindependent sequential thinning in arbitrary dimensions aCrete, GreekbIASTED - Acta PresscJune 2011 a129 - 1343 aSkeletons are region based shape descriptors that play important role in shape representation. This paper introduces a novel sequential thinning approach for n-dimensional binary objects (n =1,2,3, ...). Its main strength lies in its order--independency, i.e., it can produce the same skeletons for any visiting orders of border points. Furthermore, this is the first scheme in this field that is also applicable for higher dimensions.
1 aKardos, Péter1 aPalágyi, Kálmán1 aAndreadis, Ioannis1 aZervakis, M uhttps://www.inf.u-szeged.hu/publication/order-independent-sequential-thinning-in-arbitrary-dimensions01086nas a2200169 4500008004100000020001400041245008100055210006900136260001300205300001400218490000700232520049400239100002000733700001900753700002300772856012100795 2011 eng d a1524-070300aThinning combined with iteration-by-iteration smoothing for 3D binary images0 aThinning combined with iterationbyiteration smoothing for 3D bin cNov 2011 a335 - 3450 v733 aIn this work we present a new thinning scheme for reducing the noise sensitivity of 3D thinning algorithms. It uses iteration-by-iteration smoothing that removes some border points that are considered as extremities. The proposed smoothing algorithm is composed of two parallel topology preserving reduction operators. An efficient implementation of our algorithm is sketched and its topological correctness for (26, 6) pictures is proved. © 2011 Elsevier Inc. All rights reserved.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/thinning-combined-with-iteration-by-iteration-smoothing-for-3d-binary-images00578nas a2200157 4500008004100000245010100041210007700142260002800219300001400247100002000261700001900281700002300300700001700323700002300340856005700363 2011 hun d00aA topológia-megőrzés elegendő feltételein alapuló 3D párhuzamos vékonyító algoritmusok0 atopológiamegőrzés elegendő feltételein alapuló 3D párhuzamos vék aSzegedbNJSZTcJan 2011 a190 - 2051 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aKato, Zoltan1 aPalágyi, Kálmán uhttp://www.inf.u-szeged.hu/kepaf2011/pdfs/S05_02.pdf01286nas a2200205 4500008004100000020002200041245007200063210006900135260004500204300001200249520054400261100001900805700002300824700002200847700002300869700002400892700002800916700002400944856011200968 2011 eng d a978-3-642-21072-300aOn topology preservation for hexagonal parallel thinning algorithms0 atopology preservation for hexagonal parallel thinning algorithms aMadrid, SpainbSpringer VerlagcMay 2011 a31 - 423 aTopology preservation is the key concept in parallel thinning algorithms on any sampling schemes. This paper establishes some sufficient conditions for parallel thinning algorithms working on hexagonal grids (or triangular lattices) to preserve topology. By these results, various thinning (and shrinking to a residue) algorithms can be verified. To illustrate the usefulness of our sufficient conditions, we propose a new parallel thinning algorithm and prove its topological correctness. © 2011 Springer-Verlag Berlin Heidelberg.
1 aKardos, Péter1 aPalágyi, Kálmán1 aAggarwal, Jake, K1 aBarneva, Reneta, P1 aBrimkov, Valentin E1 aKoroutchev, Kostadin, N1 aKorutcheva, Elka, R uhttps://www.inf.u-szeged.hu/publication/on-topology-preservation-for-hexagonal-parallel-thinning-algorithms01129nas a2200157 4500008004100000020001400041245005300055210005300108260003800161300001200199490000700211520061700218100002000835700002300855856009300878 2011 eng d a0899-945700aTopology Preserving Parallel Thinning Algorithms0 aTopology Preserving Parallel Thinning Algorithms bWiley Periodicals, Inc.cFeb 2011 a37 - 440 v213 aThinning is an iterative object reduction technique for extracting medial curves from binary objects. During a thinning process, some border points that satisfy certain topological and geometric constraints are deleted in iteration steps. Parallel thinning algorithms are composed of parallel reduction operators that delete a set of object points simultaneously. This article presents 21 parallel thinning algorithms for (8,4) binary pictures that are derived from the sufficient conditions for topology preservation accommodated to the three parallel thinning approaches. © 2011 Wiley Periodicals, Inc.
1 aNémeth, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/topology-preserving-parallel-thinning-algorithms00552nas 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-tomografiaban00495nas a2200157 4500008004100000020001400041245005300055210005300108260000900161300001200170490000700182100001900189700002000208700002300228856008600251 2010 eng d a0133-339900aBejárásfüggetlen szekvenciális vékonyítás0 aBejárásfüggetlen szekvenciális vékonyítás c2010 a17 - 400 v271 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/bejarasfuggetlen-szekvencialis-vekonyitas00565nas a2200145 4500008004100000245009800041210006900139260006100208300001400269100002000283700002300303700002200326700002300348856004800371 2010 eng d00aParallel Thinning Algorithms Based on Ronse's Sufficient Conditions for Topology Preservation0 aParallel Thinning Algorithms Based on Ronses Sufficient Conditio aSingaporebScientific Research Publishing Inc.cMay 2010 a183 - 1941 aNémeth, Gábor1 aPalágyi, Kálmán1 aWiederhold, Petra1 aBarneva, Reneta, P uhttp://rpsonline.com.sg/rpsweb/iwcia09.html01180nas a2200181 4500008004100000245005800041210005700099260005200156300001400208520057500222100002000797700001900817700002300836700001300859700001500872700001300887856009800900 2010 eng d00aTopology preserving 2-subfield 3D thinning algorithms0 aTopology preserving 2subfield 3D thinning algorithms aInnsbruck, AustriabIASTED ACTA PresscFeb 2010 a310 - 3163 aThis paper presents a new family of 3D thinning algorithms for extracting skeleton-like shape features (i.e, centerline, medial surface, and topological kernel) from volumetric images. A 2-subfield strategy is applied: all points in a 3D picture are partitioned into two subsets which are alternatively activated. At each iteration, a parallel operator is applied for deleting some border points in the active subfield. The proposed algorithms are derived from Ma's sufficient conditions for topology preservation, and they use various endpoint characterizations.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aZagar, B1 aKuijper, A1 aSahbi, H uhttps://www.inf.u-szeged.hu/publication/topology-preserving-2-subfield-3d-thinning-algorithms01486nas a2200181 4500008004100000245007800041210006900119260005900188300001400247490000900261520081200270100002001082700001901102700002301121700002301144700001901167856011801186 2010 eng d00aTopology Preserving 3D Thinning Algorithms using Four and Eight Subfields0 aTopology Preserving 3D Thinning Algorithms using Four and Eight aPóvoa de Varzim, PortugalbSpringer VerlagcJune 2010 a316 - 3250 v61113 aThinning is a frequently applied technique for extracting skeleton-like shape features (i.e., centerline, medial surface, and topological kernel) from volumetric binary images. Subfield-based thinning algorithms partition the image into some subsets which are alternatively activated, and some points in the active subfield are deleted. This paper presents a set of new 3D parallel subfield-based thinning algorithms that use four and eight subfields. The three major contributions of this paper are: 1) The deletion rules of the presented algorithms are derived from some sufficient conditions for topology preservation. 2) A novel thinning scheme is proposed that uses iteration-level endpoint checking. 3) Various characterizations of endpoints yield different algorithms. © 2010 Springer-Verlag.
1 aNémeth, Gábor1 aKardos, Péter1 aPalágyi, Kálmán1 aCampilho, Aurélio1 aKamel, Mohamed uhttps://www.inf.u-szeged.hu/publication/topology-preserving-3d-thinning-algorithms-using-four-and-eight-subfields01333nas a2200217 4500008004100000245006400041210006400105260004400169300001400213490000900227520058400236100002000820700001900840700002300859700002300882700002400905700002500929700002600954700003100980856010401011 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 aThis 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/publication/topology-preserving-parallel-smoothing-for-3d-binary-images00432nas a2200133 4500008004100000020001400041245005100055210005100106260001200157300000600169490000700175100002300182856009300205 2009 eng d a0324-721X00aConference of PhD Students in Computer Science0 aConference of PhD Students in Computer Science c2009/// a30 v191 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/conference-of-phd-students-in-computer-science-101191nas a2200181 4500008004100000020002200041245009900063210006900162260005600231300001400287520045800301100002300759700002000782700001800802700002700820700002300847856013900870 2009 eng d a978-3-642-04396-300aFully Parallel 3D Thinning Algorithms based on Sufficient Conditions for Topology Preservation0 aFully Parallel 3D Thinning Algorithms based on Sufficient Condit aMontreal, Quebec, CanadabSpringer VerlagcSep 2009 a481 - 4923 aThis paper presents a family of parallel thinning algorithms for extracting medial surfaces from 3D binary pictures. The proposed algorithms are based on sufficient conditions for 3D parallel reduction operators to preserve topology for (26,6) pictures. Hence it is self-evident that our algorithms are topology preserving. Their efficient implementation on conventional sequential computers is also presented. © 2009 Springer Berlin Heidelberg.
1 aPalágyi, Kálmán1 aNémeth, Gábor1 aBrlek, Srecko1 aReutenauer, Christophe1 aProvençal, Xavier uhttps://www.inf.u-szeged.hu/publication/fully-parallel-3d-thinning-algorithms-based-on-sufficient-conditions-for-topology-preservation00641nas a2200157 4500008004100000245009200041210007800133260003300211300001000244100001900254700002000273700002300293700002500316700002000341856012200361 2009 hun d00aKritikus párokat vizsgáló bejárásfüggetlen szekvenciális vékonyító algoritmus0 aKritikus párokat vizsgáló bejárásfüggetlen szekvenciális vékonyí aBudapestbAkaprintcJan 2009 a1 - 81 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán1 aChetverikov, Dmitrij1 aSziranyi, Tamas uhttps://www.inf.u-szeged.hu/publication/kritikus-parokat-vizsgalo-bejarasfuggetlen-szekvencialis-vekonyito-algoritmus00635nas a2200169 4500008004100000245007400041210007200115260003300187300001100220100002000231700002100251700002300272700002000295700002500315700002000340856010500360 2009 eng d00aA morfológiai váz általánosítása szomszédsági szekvenciákkal0 amorfológiai váz általánosítása szomszédsági szekvenciákkal aBudapestbAkaprintcJan 2009 a1 - 101 aNémeth, Gábor1 aKovács, György1 aPalágyi, Kálmán1 aFazekas, Attila1 aChetverikov, Dmitrij1 aSziranyi, Tamas uhttps://www.inf.u-szeged.hu/publication/a-morfologiai-vaz-altalanositasa-szomszedsagi-szekvenciakkal01114nas a2200181 4500008004100000020002200041245005500063210005100118260005600169300001400225520052000239100001900759700002000778700002300798700002200821700002300843856006600866 2009 eng d a978-3-642-10208-000aAn order-independent sequential thinning algorithm0 aorderindependent sequential thinning algorithm aPlaya del Carmen, MexicobSpringer VerlagcNov 2009 a162 - 1753 aThinning is a widely used approach for skeletonization. Sequential thinning algorithms use contour tracking: they scan border points and remove the actual one if it is not designated a skeletal point. They may produce various skeletons for different visiting orders. In this paper, we present a new 2-dimensional sequential thinning algorithm, which produces the same result for arbitrary visiting orders and it is capable of extracting maximally thinned skeletons. © Springer-Verlag Berlin Heidelberg 2009.
1 aKardos, Péter1 aNémeth, Gábor1 aPalágyi, Kálmán1 aWiederhold, Petra1 aBarneva, Reneta, P uhttp://link.springer.com/chapter/10.1007/978-3-642-10210-3_1300419nas a2200145 4500008004100000020001400041245003300055210003300088260001200121300000800133490000800141100002800149700002300177856007300200 2009 eng d a0166-218X00aPreface to the Special Issue0 aPreface to the Special Issue c2009/// a4370 v1571 aNyúl, László, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/preface-to-the-special-issue01265nas a2200145 4500008004100000020001400041245005100055210004800106260027600154300001400430490000800444520055300452100002301005856009101028 2008 eng d a0304-397500aA 3D fully parallel surface-thinning algorithm0 a3D fully parallel surfacethinning algorithm aAHUJA N, 1997, IEEE T PATTERN ANAL, V19, P169ARCELLI C, 2006, LECT NOTES COMPUT SC, V4245, P555BERTRAND G, 1994, P SPIE C VISION GEOM, V2356, P113BERTRAND G, 1995, CR ACAD SCI I-MATH, V321, P1077BERTRAND G, 1995, P 5 INT C DISCR GEOM, P233BERTRAND G, bElseviercOct 2008 a119 - 1350 v4063 aThe thinning is an iterative layer by layer erosion until only the "skeletons" of the objects are left. This paper presents a thinning algorithm for extracting medial surfaces from 3D binary pictures. The strategy which is used is called fully parallel, which means that the same parallel operator is applied at each iteration. An efficient implementation of the proposed algorithm on conventional sequential computers is given and the topological correctness for (26, 6) binary pictures is proved. © 2008 Elsevier B.V. All rights reserved.
1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-3d-fully-parallel-surface-thinning-algorithm00715nas a2200169 4500008004100000245010400041210006900145260005300214300000700267100001800274700002000292700002300312700002300335700002000358700002300378856014400401 2008 eng d00aDetermination of geometric features of binary images from their projections by using decision trees0 aDetermination of geometric features of binary images from their aSzeged, HungarybUniversity of SzegedcJuly 2008 a261 aGara, Mihály1 aBalázs, Péter1 aPalágyi, Kálmán1 aBánhelyi, Balázs1 aGergely, Tamás1 aMatievics, István uhttps://www.inf.u-szeged.hu/publication/determination-of-geometric-features-of-binary-images-from-their-projections-by-using-decision-trees01602nas a2200229 4500008004100000245006200041210006000103260005800163520086900221100002001090700002401110700001801134700001701152700001801169700001601187700002801203700002301231700001901254700001901273700002001292856006001312 2008 eng d00aA képfeldolgozás kutatása a Szegedi Tudományegyetemen0 aképfeldolgozás kutatása a Szegedi Tudományegyetemen aDebrecenbDebreceni Egyetem Informatikai Karc2008///3 aA digitális képfeldolgozás kutatásának a Szegedi TudományegyetemTermészettudományi és Informatikai Karán, az Informatikai Tanszékcsoport Képfeldolgozás és Számítógépes Grafika Tanszékén közel négy évtizedes hagyománya van. A Tanszék valamennyi munkatársa nemzetközileg elismert kutatómunkát folytat, melyet már több száz rangos publikáció fémjelez. Számos, a képfeldolgozás kutatásában vezető egyetemmel és kutatóintézettel építettünk ki szoros kapcsolatot és folytattunk eredményes kutatómunkát, aktív résztvevői vagyunk a hazai és a nemzetközi tudományos közéletnek. A legfontosabb, jelenleg is folyó kutatásaink: orvosi képek feldolgozása, diszkrét tomográfia, képszegmentálás, térinformatika, távérzékelés, képregisztráció, vázkijelölés, műtéti tervezés. 1 aBalázs, Péter1 aErdőhelyi, Balázs1 aKatona, Endre1 aKato, Zoltan1 aMáté, Eörs1 aNagy, Antal1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aTanacs, Attila1 aPethő, Attila1 aHerdon, Miklós uhttp://www.agr.unideb.hu/if2008/kiadvany/papers/E62.pdf01308nas a2200217 4500008004100000020002200041022001400063245006100077210006100138260004900199300001400248520057800262100002000840700002300860700002100883700002000904700002500924700001900949700002100968856010100989 2008 eng d a978-3-540-79546-9 a0302-974300aSkeletonization based on metrical neighborhood sequences0 aSkeletonization based on metrical neighborhood sequences aSantorini, GreecebSpringer VerlagcMay 2008 a333 - 3423 aSkeleton is a shape descriptor which summarizes the general formof objects. It can be expressed in terms of the fundamental morphological operations. The limitation of that characterization is that its construction based on digital disks such that cannot provide good approximation to the Euclidean disks. In this paper we define a new type of skeleton based on neighborhood sequences that is much closer to the Euclidean skeleton. A novel method for quantitative comparison of skeletonization algorithms is also proposed. © 2008 Springer- Verlag Berlin Heidelberg.
1 aFazekas, Attila1 aPalágyi, Kálmán1 aKovács, György1 aNémeth, Gábor1 aGasteratos, Antonios1 aVincze, Markus1 aTsotsos, John, K uhttps://www.inf.u-szeged.hu/publication/skeletonization-based-on-metrical-neighborhood-sequences01901nas a2200229 4500008004100000245007400041210006900115260003400184300001400218520110100232100002001333700001801353700002901371700002301400700002801423700002301451700002001474700001901494700002201513700002201535856011401557 2008 eng d00aTechniques of Virtual Dissection of the Colon Based on Spiral CT Data0 aTechniques of Virtual Dissection of the Colon Based on Spiral CT aBerlinbSpringer-Verlagc2008 a257 - 2683 aColorectal cancer represents the third most commonly diagnosedcancer and is the second leading cause of cancer deaths in the United States (Gazelle et al. 2000). In addition, colorectal cancer is responsible for about 11% of all new cancer cases per year (Gazelle et al. 2000). Five-year prognosis is about 90% for patients with localized disease compared to 60% if there is a regional spread and a drop to 10% in patients with distant metastasis (Gazelle et al. 2000). In the field of medicine there is a widely accepted opinion that most colorectal cancers arise from pre-existent adenomatous polyps (Johnson 2000). Therefore, different societies, such as the American Cancer Society, have proposed screening for colorectal cancer (Byers et al. 1997; Winawer et al. 1997). Today, different options exist for detection of colorectal cancer, including digital rectal examination, fecal occult blood testing, flexible and rigid sigmoidoscopy, barium enema and its variants, colonoscopy and recently computed tomography or magnetic resonance-based virtual colonography (Gazelle et al. 2000).
1 aSorantin, Erich1 aBalogh, Emese1 aBartroli, Anna, Vilanova1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aLindbichler, Franz1 aRuppert, Andrea1 aNeri, Emanuele1 aCaramella, Davide1 aBartolozzi, Carlo uhttps://www.inf.u-szeged.hu/publication/techniques-of-virtual-dissection-of-the-colon-based-on-spiral-ct-data00980nas a2200181 4500008004100000020002200041022001400063245004800077210004400125260004700169300001400216520039400230100002300624700002500647700001900672700001900691856008800710 2007 eng d a978-3-540-74271-5 a0302-974300aA 3-subiteration surface-thinning algorithm0 a3subiteration surfacethinning algorithm aVienna, AustriabSpringer VerlagcAug 2007 a628 - 6353 aThinning is an iterative layer by layer erosion for extractingskeleton. This paper presents an efficient parallel 3D thinning algorithm which produces medial surfaces. A three-subiteration strategy is proposed: the thinning operation is changed from iteration to iteration with a period of three according to the three deletion directions. © Springer-Verlag Berlin Heidelberg 2007.
1 aPalágyi, Kálmán1 aKropatsch, Walter, G1 aKampel, Martin1 aHanbury, Allan uhttps://www.inf.u-szeged.hu/publication/a-3-subiteration-surface-thinning-algorithm00602nas a2200157 4500008004100000245006000041210006000101260007300161300001400234100002300248700001900271700001800290700002000308700002000328856009600348 2007 eng d00aAlakreprezentáció szférikus harmonikus sorfejtéssel0 aAlakreprezentáció szférikus harmonikus sorfejtéssel aDebrecenbKépfeldolgozók és Alakfelismerők TársaságacJan 2007 a275 - 2821 aPalágyi, Kálmán1 aPintér, Csaba1 aMáté, Eörs1 aFazekas, Attila1 aHajdú, András uhttps://www.inf.u-szeged.hu/publication/alakreprezentacio-szferikus-harmonikus-sorfejtessel00530nas a2200133 4500008004100000245005500041210005500096260007300151300001400224100002300238700002000261700002000281856009500301 2007 eng d00aEfficient Implementation of 3D Thinning Algorithms0 aEfficient Implementation of 3D Thinning Algorithms aDebrecenbKépfeldolgozók és Alakfelismerők TársaságacJan 2007 a266 - 2741 aPalágyi, Kálmán1 aFazekas, Attila1 aHajdú, András uhttps://www.inf.u-szeged.hu/publication/efficient-implementation-of-3d-thinning-algorithms01085nas a2200181 4500008004100000020002200041022001400063245007500077210006900152260005100221300001400272520041500286100002300701700002300724700002300747700001800770856011500788 2007 eng d a978-3-540-74933-2 a0302-974300aA subiteration-based surface-thinning algorithm with a period of three0 asubiterationbased surfacethinning algorithm with a period of thr aHeidelberg, GermanybSpringer VerlagcSep 2007 a294 - 3033 aThinning on binary images is an iterative layer by layer erosionuntil only the "skeletons" of the objects are left. This paper presents an efficient parallel 3D surface-thinning algorithm. A three-subiteration strategy is proposed: the thinning operation is changed from iteration to iteration with a period of three according to the three deletion directions. © Springer-Verlag Berlin Heidelberg 2007.
1 aPalágyi, Kálmán1 aHamprecht, Fred, A1 aSchnorr, Christoph1 aJähne, Bernd uhttps://www.inf.u-szeged.hu/publication/a-subiteration-based-surface-thinning-algorithm-with-a-period-of-three00740nas a2200193 4500008004100000245008700041210006900128260004600197300001400243100001800257700001600275700002000291700002300311700001700334700001700351700002800368700002300396856012700419 2006 eng d00aA benchmark evaluation of large-scale optimization approaches to binary tomography0 abenchmark evaluation of largescale optimization approaches to bi aBerlin; HeidelbergbSpringer-Verlagc2006 a146 - 1561 aWeber, Stefan1 aNagy, Antal1 aSchulle, Thomas1 aSchnorr, Christoph1 aKuba, Attila1 aKuba, Attila1 aNyúl, László, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-benchmark-evaluation-of-large-scale-optimization-approaches-to-binary-tomography01025nas a2200157 4500008004100000245004300041210004300084260002600127300000800153490000900161520057500170100001700745700002800762700002300790856005400813 2006 eng d00aDiscrete Geometry for Computer Imagery0 aDiscrete Geometry for Computer Imagery bSpringer-Verlagc2006 a6880 v42453 aThis book constitutes the refereed proceedings of the 13th International Conference on Discrete Geometry for Computer Imagery, DGCI 2006, held in Szeged, Hungary in October 2006. The 28 revised full papers and 27 revised poster papers presented together with 2 invited papers were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on discrete geometry, discrete tomography, discrete topology, distance, image analysis, shape representation, segmentation, skeletonization, as well as surfaces and volumes.
1 aKuba, Attila1 aNyúl, László, Gábor1 aPalágyi, Kálmán uhttp://www.springerlink.com/content/t38633812l42/00729nas a2200181 4500008004100000245009300041210006900134260004500203300001400248100002000262700002100282700002800303700002300331700002300354700002100377700001800398856013100416 2006 eng d00aNew advances for imaging laryngo / trachealstenosis by post processing of spiral-CT data0 aNew advances for imaging laryngo trachealstenosis by post proces aWien; New YorkbSpringer-Verlagc2006/// a297 - 3081 aSorantin, Erich1 aMohadjer, Darius1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aLindbichler, Franz1 aGeiger, Bernhard1 aHruby, Walter uhttps://www.inf.u-szeged.hu/publication/new-advances-for-imaging-laryngo-trachealstenosis-by-post-processing-of-spiral-ct-data01169nas a2200157 4500008004100000245009000041210006900131260004900200300001200249520053200261100002000793700001700813700002800830700002300858856013000881 2006 eng d00aThe number of line-convex directed polyominoes having the same orthogonal projections0 anumber of lineconvex directed polyominoes having the same orthog aBerlin, HeidelbergbSpringer-Verlagc2006/// a77 - 853 aThe number of line-convex directed polyominoes with givenhorizontal and vertical projections is studied. It is proven that diagonally convex directed polyominoes are uniquely determined by their orthogonal projections. The proof of this result is algorithmical. As a counterpart, we show that ambiguity can be exponential if antidiagonal convexity is assumed about the polyomino. Then, the results are generalised to polyominoes having convexity property along arbitrary lines. © Springer-Verlag Berlin Heidelberg 2006.
1 aBalázs, Péter1 aKuba, Attila1 aNyúl, László, Gábor1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/the-number-of-line-convex-directed-polyominoes-having-the-same-orthogonal-projections01893nas a2200181 4500008004100000020001400041245006200055210006200117260026900179300001400448490000700462520105800469100002301527700002101550700002101571700001701592856010201609 2006 eng d a0010-482500aQuantitative analysis of pulmonary airway tree structures0 aQuantitative analysis of pulmonary airway tree structures aANTIGA L, 2003, IEEE T MED IMAGING, V22, P674, DOI10.1109/TMI.2003.812261 AYLWARD SR, 2002, IEEE T MED IMAGING, V21, P61 BLAND JM, 1986, LANCET, V1, P307 BORGEFORS G, 1984, COMPUT VISION GRAPH, V27, P321 BOUIX S, 2003, IEEE C COMP VIS PATT, P449 CHEN ZK, c2006/// a974 - 9960 v363 aA method for computationally efficient skeletonization of three-dimensional tubular structures is reported. The method is specifically targeting skeletonization of vascular and airway tree structures in medical images but it is general and applicable to many other skeletonization tasks. The developed approach builds on the following novel concepts and properties: fast curve-thinning algorithm to increase computational speed, endpoint re-checking to avoid generation of spurious side branches, depth-and-length sensitive pruning, and exact tree-branch partitioning allowing branch volume and surface measurements. The method was validated in computer and physical phantoms and in vivo CT scans of human lungs. The validation studies demonstrated sub-voxel accuracy of branch point positioning, insensitivity to changes of object orientation, and high reproducibility of derived quantitative indices of the tubular structures offering a significant improvement over previously reported methods (p ≪ 0.001). © 2005 Elsevier Ltd. All rights reserved.1 aPalágyi, Kálmán1 aTschirren, Juerg1 aHoffman, Eric, A1 aSonka, Milan uhttps://www.inf.u-szeged.hu/publication/quantitative-analysis-of-pulmonary-airway-tree-structures00555nas a2200145 4500008004100000245006800041210006500109260002500174300001400199100002300213700002500236700002100261700001900282856010800301 2005 eng d00aA 2-Subfield 3D Thinning Algorithm for Extracting Medial Curves0 a2Subfield 3D Thinning Algorithm for Extracting Medial Curves aViennabOCGc2005/// a135 - 1421 aPalágyi, Kálmán1 aChetverikov, Dmitrij1 aCzúni, László1 aVincze, Markus uhttps://www.inf.u-szeged.hu/publication/a-2-subfield-3d-thinning-algorithm-for-extracting-medial-curves01876nas a2200193 4500008004100000020001400041245005800055210005800113260026900171300001600440490000700456520101600463100002101479700002301500700002301523700002101546700001701567856009801584 2005 eng d a0278-006200aMatching and anatomical labeling of human airway tree0 aMatching and anatomical labeling of human airway tree aBALLARD DH, 1982, COMPUTER VISIONBOYDEN EA, 1955, SEGMENTAL ANATOMY LU CARRAGHAN R, 1990, OPER RES LETT, V9, P375 GAREY MR, 1979, COMPUTERS INTRACTABI KITAOKA H, 2002, P MICCAI 2002 TOKYO, P1 MORI K, 2000, IEEE T MED IMAGING, V19, P103 PALAGYI K, 2003, LEc2005/// a1540 - 15470 v243 aMatching of corresponding branchpoints between two human airway trees, as well as assigning anatomical names to the segments and branchpoints of the human airway tree, are of significant interest for clinical applications and physiological studies. In the past, these tasks were often performed manually due to the lack of automated algorithms that can tolerate false branches and anatomical variability typical for in vivo trees. In this paper, we present algorithms that perform both matching of branchpoints and anatomical labeling of in vivo trees without any human intervention and within a short computing time. No hand-pruning of false branches is required. The results from the automated methods show a high degree of accuracy when validated against reference data provided by human experts. 92.9% of the verifiable branchpoint matches found by the computer agree with experts' results. For anatomical labeling, 97.1 % of the automatically assigned segment labels were found to be correct. © 2005 IEEE.1 aTschirren, Juerg1 aMcLennan, Geoffrey1 aPalágyi, Kálmán1 aHoffman, Eric, A1 aSonka, Milan uhttps://www.inf.u-szeged.hu/publication/matching-and-anatomical-labeling-of-human-airway-tree03433nas a2200193 4500008004100000245012500041210006900166260004100235300001200276520262600288100002002914700002102934700002302955700002802978700002303006700002103029700002603050856016303076 2005 eng d00aTechniques in 3D Assessment of Tracheal-Stenosis by the Mean of Spiral Computed Tomography (S-CT) and Their Applications0 aTechniques in 3D Assessment of TrachealStenosis by the Mean of S aSingaporebWorld Scientificc2005/// a61 - 803 aEndotracheal intubation is the most common cause of Laryngo-Tracheal Stenoses (LTS), followed by trauma and prior airway surgery.1–3 In rare cases LTS may have resulted also from inhalation injuries, gastro-esophageal reflux disease, neoplasia and autoimmune diseases like Wegeners granulomatosis or relapsing polychondritis.1,4 In pediatric patients vascular compression of the trachea is a common cause of tracheal indentations.5 Clinical management of these conditions requires information on localization, grade, length and dynamics of the stenosis. Exact LTS information is necessary, since stenoses with a length less than 1.0 cm can be treated by an endoscopic surgery.6,7 Besides Fiberoptic Endoscopy (FE), which represents the gold standard for airway evaluation, imaging modalities like conventional radiography, fluoroscopy, tracheal tomograms, Magnetic Resonance Imaging (MRI) and above all Spiral Computed Tomography (S-CT) are an essential part of the clinical work.1,8 S-CT and the recent introduction of multislice imaging allows volumetric data acquisition of the Laryngo–Tracheal Tract (LTT) during a short time span. Decreased motion artifacts and increased spatial resolution form the basis for high quality post processing.9,10 The improved performance of today's workstations permits the use of sophisticated post processing algorithms even on standard hardware like personal computers. Thus real time 3D display and virtual endoscopic views (virtual endoscopy) are just one mouse click away. Other algorithms compute the medial axis of tubular structures like airways or vessels in 3D, which can be used for the calculation of 3D cross sectional profiles for better demonstration of caliber changes.11 Thus display of S-CT axial source images is moving rapidly to 3D display. Moreover, established network connections within and between institutions allows telemedical cooperation. Web technologies offer an easy to use way for information exchange. The objective of this paper is to present an overview on 3D display and quantification of LTS as well as to provide information how these results can be presented and shared with the referring physicians on the hospitals computer network. This article is structured in seven parts; namely: S-CT data acquisition for LTS imaging; selected 3D image post processing algorithms; 3D display; Virtual endoscopy; Objective LTS degree and length estimation using LTT 3D — cross-sectional profiles; Intranet applications; and a conclusion is drawn in the final section. 1 aSorantin, Erich1 aMohadjer, Darius1 aLindbichler, Franz1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aGeiger, Bernhard1 aLeondes, Cornelius, T uhttps://www.inf.u-szeged.hu/publication/techniques-in-3d-assessment-of-tracheal-stenosis-by-the-mean-of-spiral-computed-tomography-s-ct-and-their-applications00861nas a2200169 4500008004100000020001400041245007700055210006900132260026900201300001400470490000900484100002300493700002100516700002100537700001700558856011600575 2004 eng d a0302-974300aAssessment of intrathoracic airway trees: Methods and in vivo validation0 aAssessment of intrathoracic airway trees Methods and in vivo val aBLAND JM, 1986, LANCET, V1, P307CHEN ZK, 2003, COMPUT MED IMAG GRAP, V27, P469, DOI 10.1016/S0895-6111(03)00039-9 GERIG G, 1993, LECT NOTES COMPUTER, V687, P94 KITAOKA H, 1999, J APPL PHYSIOL, V87, P2207 KONG TY, 1989, COMPUT VISION GRAPH, V48, P357 MADDAc2004/// a341 - 3520 v31171 aPalágyi, Kálmán1 aTschirren, Juerg1 aHoffman, Eric, A1 aSonka, Milan uhttps://www.inf.u-szeged.hu/publication/assessment-of-intrathoracic-airway-trees-methods-and-in-vivo-validation00519nas a2200145 4500008004100000245004000041210003900081260007500120300001400195100002300209700002000232700002200252700002200274856007700296 2004 eng d00aLégutak vizsgálata 3D CT-képeken0 aLégutak vizsgálata 3D CTképeken aMiskolcbNeumann János Számítógép-tudományi TársaságcJan 2004 a232 - 2361 aPalágyi, Kálmán1 aGácsi, Zoltán1 aBarkóczy, Péter1 aSárközi, Gábor uhttps://www.inf.u-szeged.hu/publication/legutak-vizsgalata-3d-ct-kepeken02458nas a2200265 4500008004100000245007500041210006900116260027500185300001600460520132700476100002301803700001701826700002101843700002101864700002401885700002201909700002301931700002001954700002301974700001901997700001702016700002702033700001702060856011502077 2004 eng d00aLiver segment approximation in CT data for surgical resection planning0 aLiver segment approximation in CT data for surgical resection pl aBellingham; WashingtonScheele, J., Anatomical and atypical liver resection (2001) Chirurg, 72 (2), pp. 113-124;Couinaud, C., (1957) Le Foie - Etudes Anatomiques et Chirurgicales, , Masson, Paris; Strunk, H., Stuckmann, G., Textor, J., Willinek, W., LimitbSPIEc2004/// a1435 - 14463 aSurgical planning of liver tumor resections requires detailed three-dimensional (3D) understanding of the complex arrangement of vasculature, liver segments and tumors. Knowledge about location and sizes of liver segments is important for choosing an optimal surgical resection approach and predicting postoperative residual liver capacity. The aim of this work is to facilitate such surgical planning process by developing a robust method for portal vein tree segmentation. The work also investigates the impact of vessel segmentation on the approximation of liver segment volumes. For segment approximation, smaller portal vein branches are of importance. Small branches, however, are difficult to segment due to noise and partial volume effects. Our vessel segmentation is based on the original gray-values and on the result of a vessel enhancement filter. Validation of the developed portal vein segmentation method in computer generated phantoms shows that, compared to a conventional approach, more vessel branches can be segmented. Experiments with in vivo acquired liver CT data sets confirmed this result. The outcome of a Nearest Neighbor liver segment approximation method applied to phantom data demonstrates, that the proposed vessel segmentation approach translates into a more accurate segment partitioning.1 aBeichel, Reinhardt1 aPock, Thomas1 aJanko, Christian1 aZotter, Roman, B1 aReitinger, Bernhard1 aBornik, Alexander1 aPalágyi, Kálmán1 aSorantin, Erich1 aWerkgartner, Georg1 aBischof, Horst1 aSonka, Milan1 aFitzpatrick, J Michael1 aSonka, Milan uhttps://www.inf.u-szeged.hu/publication/liver-segment-approximation-in-ct-data-for-surgical-resection-planning02509nas a2200265 4500008004100000245007700041210007700118260007500195300001400270520158400284100001601868700001801884700002801902700001701930700001801947700002301965700001801988700001702006700002802023700001902051700002002070700002202090700002202112856010902134 2004 eng d00aSzámítógépes képfeldolgozás oktatása a Szegedi Tudományegyetemen0 aSzámítógépes képfeldolgozás oktatása a Szegedi Tudományegyetemen aMiskolcbNeumann János Számítógép-tudományi TársaságcJan 2004 a191 - 1963 aAz SZTE Informatikai Tanszékcsoportja által gondozott szakoktanterveiben 1993 óta szerepel a képfeldolgozás és alkalmazásainak oktatása. A kreditrendszer bevezetésével a Képfeldolgozás I. tárgy kötelező az ötéves képzésben részt vevő informatikus hallgatóknak. Ezen felül a választható szakirányok között szintén szerepel a Képfeldolgozás szakirány. A szakirányon belül különböző képpfeldolgozási területeket tárgyaló kurzusok épülnek egymásra. Az elméleti megalapozás mellett a képfeldolgozás alkalmazásaira is nagy hangsúlyt fektetünk. A kutatások illetve az orvosi alkalmazások fejlesztése során szerzett eredményeket a kötelező jellegű tárgyak mellett speciálkollégiumok keretében építjül be az otkatási anyagba. Számos hallgatónk választ a képfeldolgzás területéről témát a diplomamunkájához, dolgozataikkal rendszeresen és sikerrel szerepelnek az OTDK-n. Hallgatóink évente több hónapot tölthetnek külföldi partneregyetemeinken, ahol a kutató- és fejlesztőmunka mellett nálunk is elfogadott kurzusokat teljesíthetnek. A képfeldolgozás témakörön belül "ipari" projekt munkákban is egyre több hallgató vesz részt. A doktori programon belül is meghirdetünk képfeldolgozáshoz kapcsolódó kutatási irányokat. Az évente megrendezésre kerülő, 11-éves múltra visszatekintő Képfeldolgozó Nyári Iskolának (SSIP) eddig hatszor adott otthont Szeged. A rendszvénysorozat kiemelkedő fontosságú nemzetközi fórum hallgatóink és oktatóink számára is.
1 aNagy, Antal1 aBalogh, Emese1 aDudásné Nagy, Mariann1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán1 aKatona, Endre1 aKato, Zoltan1 aNyúl, László, Gábor1 aTanacs, Attila1 aGácsi, Zoltán1 aBarkóczy, Péter1 aSárközi, Gábor uhttps://www.inf.u-szeged.hu/publication/szamitogepes-kepfeldolgozas-oktatasa-a-szegedi-tudomanyegyetemen02328nas a2200241 4500008004100000020001400041245012200055210006900177260001200246300001600258490000700274520144300281100002001724700002001744700002401764700002301788700002801811700002201839700002301861700002301884700001801907856016101925 2003 eng d a0033-832X00a3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses0 a3D cross section of the laryngotracheal tract A new method for v c2003/// a1056 - 10680 v433 aPURPOSE: Demonstration of a technique for 3D assessment oftracheal stenoses, regarding site, length and degree, based on spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT scanning and automated segmentation of the laryngo-tracheal tract (LTT) was followed by the extraction of the LTT medial axis using a skeletonisation algorithm. Orthogonal to the medial axis the LTT 3D cross sectional profile was computed and presented as line charts, where degree and length were obtained. Values for both parameters were compared between 36 patients and 18 normal controls separately. Accuracy and precision was derived from 17 phantom studies. RESULTS: Average degree and length of tracheal stenoses were found to be 60.5% and 4.32 cm in patients compared to minor caliber changes of 8.8% and 2.31 cm in normal controls (p <0.005). For the phantoms an excellent correlation between the true and computed 3D cross sectional profile was found (p <0.005) and an accuracy for length and degree measurements of 2.14 mm and 2.53% respectively could be determined. The corresponding figures for the precision were found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3D cross sectional profiles permit objective, accurate and precise assessment of LTT caliber changes. Minor LTT caliber changes can be observed even in normals and, in case of an otherwise normal S-CT study, can be regarded as artefacts. 1 aSorantin, Erich1 aHalmai, Csongor1 aErdőhelyi, Balázs1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aOllé, Krisztián1 aLindbichler, Franz1 aFriedrich, Gerhard1 aKiesler, Karl uhttps://www.inf.u-szeged.hu/publication/3d-cross-section-of-the-laryngotracheal-tract-a-new-method-for-visualization-and-quantification-of-tracheal-stenoses02330nas a2200241 4500008004100000020001400041245012200055210006900177260001200246300001600258490000700274520144300281100002001724700002001744700002401764700002301788700002801811700002201839700002301861700002301884700001801907856016301925 2003 eng d a0033-832X00a3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses0 a3D cross section of the laryngotracheal tract A new method for v c2003/// a1056 - 10680 v433 aPURPOSE: Demonstration of a technique for 3D assessment oftracheal stenoses, regarding site, length and degree, based on spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT scanning and automated segmentation of the laryngo-tracheal tract (LTT) was followed by the extraction of the LTT medial axis using a skeletonisation algorithm. Orthogonal to the medial axis the LTT 3D cross sectional profile was computed and presented as line charts, where degree and length were obtained. Values for both parameters were compared between 36 patients and 18 normal controls separately. Accuracy and precision was derived from 17 phantom studies. RESULTS: Average degree and length of tracheal stenoses were found to be 60.5% and 4.32 cm in patients compared to minor caliber changes of 8.8% and 2.31 cm in normal controls (p <0.005). For the phantoms an excellent correlation between the true and computed 3D cross sectional profile was found (p <0.005) and an accuracy for length and degree measurements of 2.14 mm and 2.53% respectively could be determined. The corresponding figures for the precision were found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3D cross sectional profiles permit objective, accurate and precise assessment of LTT caliber changes. Minor LTT caliber changes can be observed even in normals and, in case of an otherwise normal S-CT study, can be regarded as artefacts. 1 aSorantin, Erich1 aHalmai, Csongor1 aErdőhelyi, Balázs1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aOllé, Krisztián1 aLindbichler, Franz1 aFriedrich, Gerhard1 aKiesler, Karl uhttps://www.inf.u-szeged.hu/publication/3d-cross-section-of-the-laryngotracheal-tract-a-new-method-for-visualization-and-quantification-of-tracheal-stenoses-002541nas a2200253 4500008004100000022001400041245013200055210007100187260002600258300001400284490000700298520172500305100002102030700002102051700002402072700002302096700002802119700002302147700001502170700002002185700001802205700001602223856004802239 2003 eng d a0033-832X00a3D-Querschnittsprofil des Laryngotrachealtrakts—Eine neue Methode zur Visualisierung und Quantifizierung von Trachealstenosen0 a3DQuerschnittsprofil des Laryngotrachealtrakts—Eine neue Methode bSpringer-Verlagc2003 a1056-10680 v433 aDemonstration of a technique for 3D assessment of tracheal stenoses, regarding site, length and degree, based on spiral computed tomography (S-CT).
S-CT scanning and automated segmentation of the laryngo-tracheal tract (LTT) was followed by the extraction of the LTT medial axis using a skeletonisation algorithm. Orthogonal to the medial axis the LTT 3D cross sectional profile was computed and presented as line charts, where degree and length were obtained. Values for both parameters were compared between 36 patients and 18 normal controls separately. Accuracy and precision was derived from 17 phantom studies.
Average degree and length of tracheal stenoses were found to be 60.5% and 4.32 cm in patients compared to minor caliber changes of 8.8% and 2.31 cm in normal controls (p <0.005). For the phantoms an excellent correlation between the true and computed 3D cross sectional profile was found (p <0.005) and an accuray for length and degree measurements of 2.14 mm and 2.53% respectively could be determined. The corresponding figures for the precision were found to be 0.92 mm and 2.56%.
LTT 3D cross sectional profiles permit objective, accurate and precise assessment of LTT caliber changes. Minor LTT caliber changes can be observed even in normals and, in case of an otherwise normal S-CT study, can be regarded as artefacts.
1 aSorantin, Erich.1 aHalmai, Csongor.1 aErdőhelyi, Balázs1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aOllé, Krisztián.1 aGeiger, B.1 aLindbichler, F.1 aFriedrich, G.1 aKiesler, K. uhttp://dx.doi.org/10.1007/s00117-003-0990-801319nas a2200277 4500008004100000020001400041245016100055210006900216260026900285300001600554490000700570100002100577700002500598700001700623700002000640700001700660700001600677700001800693700001900711700002200730700002100752700002300773700002100796700002300817856020100840 2003 eng d a1076-633200aCharacterization of the interstitial lung diseases via density-based and texture-based analysis of computed tomography images of lung structure and function0 aCharacterization of the interstitial lung diseases via densityba aBAE KT, 1997, RADIOLOGY, V203, P705BENTLEY MD, 1994, CIRC RES, V74, P945 CHULHO W, 2003, J APPL PHYSIOL, V94, P2483 CLARKE LP, 2001, ACAD RADIOL, V8, P447 COXSON H, 2003, AM J RESP CRIT CARE, V167, A81 COXSON H, 2003, AM J RESP CRIT CARE, V167, A81 COXSONc2003/// a1104 - 11180 v101 aHoffman, Eric, A1 aReinhardt, Joseph, M1 aSonka, Milan1 aSimon, Brett, A1 aGuo, Junfeng1 aSaba, Osama1 aChon, Deokiee1 aSamrah, Shaher1 aShikata, Hidenori1 aTschirren, Juerg1 aPalágyi, Kálmán1 aBeck, Kenneth, C1 aMcLennan, Geoffrey uhttps://www.inf.u-szeged.hu/publication/characterization-of-the-interstitial-lung-diseases-via-density-based-and-texture-based-analysis-of-computed-tomography-images-of-lung-structure-and-function00857nas a2200157 4500008004100000245008000041210006900121260028600190300001400476100002300490700002100513700001700534700001400551700001500565856011900580 2003 eng d00aQuantitative analysis of intrathoracic airway trees: Methods and validation0 aQuantitative analysis of intrathoracic airway trees Methods and aBerlin; HeidelbergBLAND JM, 1986, LANCET, V1, P307BORGEFORS G, 1984, COMPUT VISION GRAPH, V27, P321 CORMEN TH, 1990, INTRO ALGORITHMS GONZALES RC, 1992, DIGITAL IMAGE PROCES KITAOKA H, 1999, J APPL PHYSIOL, V87, P2207 KONG TY, 1989, COMPUT VISION GRAPH, VbSpringer Verlagc2003/// a222 - 2331 aPalágyi, Kálmán1 aTschirren, Juerg1 aSonka, Milan1 aTaylor, C1 aNoble, J A uhttps://www.inf.u-szeged.hu/publication/quantitative-analysis-of-intrathoracic-airway-trees-methods-and-validation00600nas a2200157 4500008004100000245007100041210006900112260009400181300001400275100002300289700002100312700001700333700001700350700002700367856004800394 2003 eng d00aQuantitative analysis of three-dimensional tubular tree structures0 aQuantitative analysis of threedimensional tubular tree structure aBellingham; WashingtonbSPIE - The International Society for Optical Engineeringc2003/// a277 - 2871 aPalágyi, Kálmán1 aTschirren, Juerg1 aSonka, Milan1 aSonka, Milan1 aFitzpatrick, J Michael uhttp://spie.org/x648.html?product_id=45926800759nas a2200133 4500008004100000020001400041245007400055210006900129260026900198300001400467490000700481100002300488856011400511 2002 eng d a0167-865500aA 3-subiteration 3D thinning algorithm for extracting medial surfaces0 a3subiteration 3D thinning algorithm for extracting medial surfac aBERTRAND G, 1994, P SPIE C VISION GEOM, V2356, P113BERTRAND G, 1995, PATTERN RECOGN LETT, V16, P979 BLUM H, 1967, MODELS PERCEPTION SP, P362 BORGEFORS G, 1984, COMPUT VISION GRAPH, V27, P321 BORGEFORS G, 1999, PATTERN RECOGN, V32, P1225 GERIG G, 1993, LECc2002/// a663 - 6750 v231 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-3-subiteration-3d-thinning-algorithm-for-extracting-medial-surfaces00771nas a2200205 4500008004100000245009400041210007800135260003100213300001400244100002200258700001600280700002000296700002800316700001700344700002200361700001700383700001800400700002300418856012400441 2002 eng d00aDigitális képtároló és képtovábbító rendszer (PACS) a Szegedi Tudományegyetemen0 aDigitális képtároló és képtovábbító rendszer PACS a Szegedi Tudo aSzegedbNJSZT-KÉPAFc2002 a132 - 1391 aAlmási, László1 aNagy, Antal1 aAlexin, Zoltán1 aNyúl, László, Gábor1 aKuba, Attila1 aCsernay, László1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/digitalis-keptarolo-es-keptovabbito-rendszer-pacs-a-szegedi-tudomanyegyetemen-000772nas a2200205 4500008004100000245009400041210007800135260003400213300001400247100002200261700001600283700002000299700002800319700001700347700002200364700001700386700001800403700002300421856012200444 2002 eng d00aDigitális képtároló és képtovábbító rendszer (PACS) a Szegedi Tudományegyetemen0 aDigitális képtároló és képtovábbító rendszer PACS a Szegedi Tudo aSzegedbNJSZT-KÉPAFc2002/// a132 - 1391 aAlmási, László1 aNagy, Antal1 aAlexin, Zoltán1 aNyúl, László, Gábor1 aKuba, Attila1 aCsernay, László1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/digitalis-keptarolo-es-keptovabbito-rendszer-pacs-a-szegedi-tudomanyegyetemen00468nam a2200121 4500008004100000245006000041210005900101260003400160100001700194700001800211700002300229856009400252 2002 eng d00aKépfeldolgozók és Alakfelismerők III. Konfereciája0 aKépfeldolgozók és Alakfelismerők III Konfereciája aSzegedbNJSZT-KÉPAFc2002///1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/kepfeldolgozok-es-alakfelismerok-iii-konfereciaja01410nas a2200469 4500008004100000020001400041245013000055210006900185260001200254300000800266490000700274100001500281700001900296700002000315700001600335700001800351700001500369700001500384700001500399700001500414700001800429700001400447700001500461700001800476700001400494700001600508700001300524700001300537700001200550700001600562700001400578700002100592700001700613700002300630700002900653700002800682700001500710700001500725700001800740700001500758856016700773 2002 eng d a0938-799400aMedical Image Processing, Surgical Planning, Image-Guided Therapy and Robotic Applications: Recent Developments for Radiology0 aMedical Image Processing Surgical Planning ImageGuided Therapy a c2002/// a5040 v121 aBale, R, J1 aBirkfellner, W1 aSorantin, Erich1 aStaedele, H1 aKettenbach, J1 aRecheis, W1 aVoegele, M1 aSweeney, R1 aKovács, P1 aWegenkittl, R1 aBodner, G1 aJaschke, W1 azur Nedden, D1 aEisner, E1 aKronreig, G1 aFurst, M1 aHanel, R1 aFigl, M1 aBergmann, H1 aHanson, D1 aRuskó, László1 aRodek, Lajos1 aPalágyi, Kálmán1 aBartroli, Anna, Vilanova1 aNyúl, László, Gábor1 aJacob, A L1 aBaumann, B1 aBalogh, Emese1 aMessmer, P uhttps://www.inf.u-szeged.hu/publication/medical-image-processing-surgical-planning-image-guided-therapy-and-robotic-applications-recent-developments-for-radiology00762nas a2200181 4500008004100000020001400041245014000055210006900195260001200264300001200276490000900288100002100297700002300318700002500341700002100366700001700387856017600404 2002 eng d a0302-974300aSegmentation, skeletonization, and branchpoint matching - A fully automated quantitative evaluation of human intrathoratic airway trees0 aSegmentation skeletonization and branchpoint matching A fully au c2002/// a12 - 190 v24891 aTschirren, Juerg1 aPalágyi, Kálmán1 aReinhardt, Joseph, M1 aHoffman, Eric, A1 aSonka, Milan uhttps://www.inf.u-szeged.hu/publication/segmentation-skeletonization-and-branchpoint-matching-a-fully-automated-quantitative-evaluation-of-human-intrathoratic-airway-trees00486nas a2200145 4500008004100000245004500041210004200086260003400128300001200162100002300174700001700197700001800214700002300232856008500255 2002 eng d00aA sequential 3D curve-thinning algorithm0 asequential 3D curvethinning algorithm aSzegedbNJSZT-KÉPAFc2002/// a42 - 511 aPalágyi, Kálmán1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-sequential-3d-curve-thinning-algorithm02304nas a2200253 4500008004100000020001400041245007800055210006900133260001200202300001400214490000700228520147500235100002001710700002001730700002401750700002301774700002801797700002201825700002101847700002301868700002301891700001801914856011801932 2002 eng d a0278-006200aSpiral-CT-based assessment of tracheal stenoses using 3-D-skeletonization0 aSpiralCTbased assessment of tracheal stenoses using 3Dskeletoniz c2002/// a263 - 2730 v213 aPURPOSE: Demonstration of a technique for three-dimensional (3-D) assessment of tracheal-stenoses, regarding site, length and degree, based on spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT scanning and automated segmentation of the laryngo-tracheal tract (LTT) was followed by the extraction of the LTT medial axis using a skeletonization algorithm. Orthogonal to the medial axis the LTT 3-D cross-sectional profile was computed and presented as line charts, where degree and length was obtained. Values for both parameters were compared between 36 patients and 18 normal controls separately. Accuracy and precision was derived from 17 phantom studies. RESULTS: Average degree and length of tracheal stenoses was found to be 60.5% and 4.32 cm in patients compared with minor caliber changes of 8.8% and 2.31 cm in normal controls (p << 0.0001). For the phantoms an excellent correlation between the true and computed 3-D cross-sectional profile was found (p << 0.005) and an accuracy for length and degree measurements of 2.14 mm and 2.53% respectively could be determined. The corresponding figures for the precision were found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3-D cross-sectional profiles permit objective, accurate and precise assessment of LTT caliber changes. Minor LTT caliber changes can be observed even in normals and, in case of an otherwise normal S-CT study, can be regarded as artifacts. 1 aSorantin, Erich1 aHalmai, Csongor1 aErdőhelyi, Balázs1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aOllé, Krisztián1 aGeiger, Bernhard1 aLindbichler, Franz1 aFriedrich, Gerhard1 aKiesler, Karl uhttps://www.inf.u-szeged.hu/publication/spiral-ct-based-assessment-of-tracheal-stenoses-using-3-d-skeletonization02066nas a2200229 4500008004100000245007700041210007700118260004100195300001400236520126900250100001601519700001801535700002801553700001701581700001801598700002801616700002301644700001901667700001901686700002001705856011101725 2002 eng d00aSzámítógépes képfeldolgozás oktatása a Szegedi Tudományegyetemen0 aSzámítógépes képfeldolgozás oktatása a Szegedi Tudományegyetemen aDebrecenbDebreceni Egyetemc2002/// a750 - 7573 aA Szegedi Tudományegyetem tanterveiben 1993 óta szerepel aképfeldolgozás és alkalmazásainak oktatása. A tantárgy ez idő alatt sok változáson ment át. Jelenleg a Képfeldolgozás szakirányt választó hallgatók részesülnek ilyen képzésben. Az adott szakirányon belül különböző képfeldolgozási területek oktatása épül egymásra. Az oktatás során nem csak elméleti és gyakorlati ismereteket szerezhetnek a hallgatók, hanem néhány (főleg orvosi) alkalmazás is bemutatásra kerül. A kötelező jellegű tárgyak mellett speciálkollégiumok engednek bepillantást más kiegészítő területekre. A hallgatók a képfeldolgozás témával rendszeresen vesznek rész helyi és országos Tudományos DIákköri Konferenciákon. Az utóbbi időben sikerült a képfeldolgozásban érdekelt cégekkel felvenni a kapcsolatot, így évente több hallgató vehet részt ipari alkalmazások fejlesztésében. A doktori programon belül is meghirdetünk képfeldolgozáshoz kapcsolódó kutatási irányokat. Ezenkívül rendszeresen megrendezzük a nemzetközi Képfeldolgozó Nyári Iskolákat, ahol nemcsak Magyarországról, hanem a környező országokból is fogadunk hallgatókat és oktatókat. 1 aNagy, Antal1 aBalogh, Emese1 aDudásné Nagy, Mariann1 aKuba, Attila1 aMáté, Eörs1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aTanacs, Attila1 aArató, Péter1 aHerdon, Miklós uhttps://www.inf.u-szeged.hu/publication/szamitogepes-kepfeldolgozas-oktatasa-a-szegedi-tudomanyegyetemen-000524nas a2200157 4500008004100000245004500041210004500086260003400131300001200165100002800177700002200205700001700227700001800244700002300262856008100285 2002 eng d00aTöbbdimenziós MRI képek feldolgozása0 aTöbbdimenziós MRI képek feldolgozása aSzegedbNJSZT-KÉPAFc2002/// a96 - 971 aNyúl, László, Gábor1 aUdupa, Jayaram, K1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/tobbdimenzios-mri-kepek-feldolgozasa02292nas a2200217 4500008004100000020001400041245014800055210006900203260001200272300001400284490000700298520142100305100002001726700002301746700001801769700002901787700002301816700002801839700002101867856018601888 2002 eng d a1682-863100aVirtual dissection and automated polyp detection of the colon based on spiral CT - Techniques and preliminary experience on a cadaveric phantom0 aVirtual dissection and automated polyp detection of the colon ba c2002/// a143 - 1490 v343 aBackground: CT colonography was found to be sensitive andspecific for detection of colonic polyps and colorectal cancer (CRC). Depending on the software used, CT colonography requires a certain amount of operator interaction, which limits it's widespread usage. The goal of this papers is to present two novel automated techniques for displaying CT colonography: virtual dissection and automated colonic polyp detection. Methods: Virtual dissection refers to a technique where the entire colon is virtually stretched and flattened thus simulating the view on the pathologist's table. Colonic folds show a 'global outward bulging of the contour', whereas colonic polyps exhibit the inverse ('local inward bulging'). This feature is used to map areas of 'local inward bulging' with colours on 3D reconstructions. A cadaveric phantom with 13 artificially inserted polyps was used for validation of both techniques. Results: On virtual dissection all 13 inserted polyps could be identified. They appeared either as bumps or as local broadening of colonic folds. In addition, the automated colonic polyp detection algorithm was able to tag all polyps. Only 10 min of operator interaction were necessary for both techniques. Conclusions: Virtual dissection overcomes the shortcomings of CT colonography, and automated colonic polyp detection establishes a roadmap of the polyps. 1 aSorantin, Erich1 aWerkgartner, Georg1 aBalogh, Emese1 aBartroli, Anna, Vilanova1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aRuskó, László uhttps://www.inf.u-szeged.hu/publication/virtual-dissection-and-automated-polyp-detection-of-the-colon-based-on-spiral-ct-techniques-and-preliminary-experience-on-a-cadaveric-phantom00597nas a2200193 4500008004100000245003600041210003600077260003400113300001400147100001800161700002000179700002800199700002300227700001700250700001700267700001800284700002300302856007800325 2002 eng d00aVirtual Dissection of the Colon0 aVirtual Dissection of the Colon aSzegedbNJSZT-KÉPAFc2002/// a109 - 1171 aBalogh, Emese1 aSorantin, Erich1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aKuba, Attila1 aKuba, Attila1 aMáté, Eörs1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/virtual-dissection-of-the-colon-000685nas a2200217 4500008004100000245003600041210003600077260003900113300001400152100002000166700001800186700002900204700002300233700002800256700002100284700001900305700002300324700002200347700002200369856007600391 2002 eng d00aVirtual Dissection of the Colon0 aVirtual Dissection of the Colon aNew YorkbSpringer-Verlagc2002/// a197 - 2091 aSorantin, Erich1 aBalogh, Emese1 aBartroli, Anna, Vilanova1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aLončarić, Sven1 aSubasic, Marco1 aKovacevic, Domagoj1 aCaramella, Davide1 aBartolozzi, Carlo uhttps://www.inf.u-szeged.hu/publication/virtual-dissection-of-the-colon01428nas a2200205 4500008004100000245010800041210006900149260004200218300001400260520063500274100001800909700002000927700002800947700002300975700001700998700002301015700001801038700001901056856014701075 2002 eng d00aVirtual dissection of the colon: technique and first experiments with artificial and cadaveric phantoms0 aVirtual dissection of the colon technique and first experiments aBellingham; WashingtonbSPIEc2002/// a713 - 7213 aVirtual dissection refers to a display technique for polypdetection, where the colon is digitally straightened and then flattened using multirow detector Computed Tomograph (CT) images. As compared to virtual colonoscopy where polyps may be hidden from view behind the folds, the unravelled colon is more suitable for polyp detection, because the entire inner surface of the colon is displayed in a single view. The method was tested both on artificial and cadaveric phantoms. All polyps could be recognized on both phantoms. This technique for virtual dissection requires only a minimum of operator interaction. 1 aBalogh, Emese1 aSorantin, Erich1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aKuba, Attila1 aWerkgartner, Georg1 aSpuller, Ekke1 aMun, Seong, Ki uhttps://www.inf.u-szeged.hu/publication/virtual-dissection-of-the-colon-technique-and-first-experiments-with-artificial-and-cadaveric-phantoms00957nas a2200133 4500008004100000245003800041210003600079260003300115300001200148490000700160520055500167100002300722856007800745 2001 eng d00aA 3D parallel shrinking algorithm0 a3D parallel shrinking algorithm aSzegedbUniversity of Szeged a201-2110 v153 a
Shrinking is a frequently used preprocessing step in image processing. This paper presents an efficient 3D parallel shrinking algorithm for transforming a binary object into its topological kernel. The applied strategy is called directional: each iteration step is composed of six subiterations each of which can be executed in parallel. The algorithm makes easy implementation possible, since deletable points are given by 3x3x3 matching templates. The topological correctness of the algorithm is proved for (26,6) binary pictures.
1 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-3d-parallel-shrinking-algorithm00394nas a2200133 4500008004100000020001400041245003800055210003600093260000900129300001400138490000700152100002300159856007800182 2001 eng d a0324-721X00aA 3D parallel shrinking algorithm0 a3D parallel shrinking algorithm c2001 a201 - 2110 v151 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-3d-parallel-shrinking-algorithm00575nas a2200169 4500008004100000020001400041245006700055210006600122260000900188300001400197490000700211100001900218700002000237700002300257700001700280856010800297 2001 eng d a0324-721X00aAffine matching of two sets of points in arbitrary dimensions.0 aAffine matching of two sets of points in arbitrary dimensions c2001 a101 - 1060 v151 aTanacs, Attila1 aCzédli, Gábor1 aPalágyi, Kálmán1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/affine-matching-of-two-sets-of-points-in-arbitrary-dimensions-000630nas a2200205 4500008004100000020001400041245006800055210006600123260001200189300001400201490000900215100002300224700002000247700001800267700001700285700002000302700002400322700002100346856005700367 2001 eng d a0302-974300aA sequential 3D thinning algorithm and its medical applications0 asequential 3D thinning algorithm and its medical applications c2001/// a409 - 4150 v20821 aPalágyi, Kálmán1 aSorantin, Erich1 aBalogh, Emese1 aKuba, Attila1 aHalmai, Csongor1 aErdőhelyi, Balázs1 aHausegger, Klaus uhttp://www.springerlink.com/content/py49qu0e434n0n1601121nas a2200193 4500008004100000245007900041210006900120260004200189300001400231520040900245100002000654700001800674700002900692700002300721700002800744700002100772700001800793856011600811 2001 eng d00aVirtual Dissection of the Colon Based on Helical CT Data - Can It Be Done?0 aVirtual Dissection of the Colon Based on Helical CT Data Can It aZagrebbUniversity of Zagrebc2001/// a224 - 2293 aColorectal cancer is the third most commonly diagnosed cancer;and colonic polyps are known precursors of that particular cancer. Virtual dissection refers to a display technique for polyp detection based on helical CT data, where the colon is dissected and flattened as on the pathologist's table. The approach and image processing as well as the early experience are described in this paper. 1 aSorantin, Erich1 aBalogh, Emese1 aBartroli, Anna, Vilanova1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aLončarić, Sven1 aBabic, Hrvoje uhttps://www.inf.u-szeged.hu/publication/virtual-dissection-of-the-colon-based-on-helical-ct-data-can-it-be-done00730nas a2200133 4500008004100000020001400041245006300055210006000118260026900178300001400447490000900461100002300470856010300493 2000 eng d a0302-974300aA 3D 3-subiteration thinning algorithm for medial surfaces0 a3D 3subiteration thinning algorithm for medial surfaces aBERTRAND G, 1994, P SPIE C VISION GEOM, V2356, P113BERTRAND G, 1995, PATTERN RECOGN LETT, V16, P979 BLU H, 1967, MODELS PERCEPTION SP, P362 GONG WX, 1990, P 10 INT C PATT REC, P188 KONG TY, 1989, COMPUT VISION GRAPH, V48, P357 KONG TY, 1995, INT J PATTERNc2000/// a406 - 4180 v19531 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/a-3d-3-subiteration-thinning-algorithm-for-medial-surfaces00710nas a2200181 4500008004100000245009500041210008100136260002900217300001300246100002300259700002000282700002000302700002400322700002500346700001700371700002000388856012000408 2000 eng d00a3D vékonyítás és alkalmazása vérerek és légutak átmérőjének meghatározására0 a3D vékonyítás és alkalmazása vérerek és légutak átmérőjének megh aNoszvajbNJSZTcJan 2000 a95 - 1001 aPalágyi, Kálmán1 aSorantin, Erich1 aHalmai, Csongor1 aErdőhelyi, Balázs1 aMartonossy, László1 aKuba, Attila1 aSziranyi, Tamas uhttps://www.inf.u-szeged.hu/publication/3d-vekonyitas-es-alkalmazasa-vererek-es-legutak-atmerojenek-meghatarozasara00766nas a2200181 4500008004100000245009400041210006900135260008100204300001400285100002000299700002000319700002400339700002500363700002300388700002100411700001800432856013400450 2000 eng d00aNew advances for imaging of laryngotracheal stenosis by post processing of spiral-CT data0 aNew advances for imaging of laryngotracheal stenosis by post pro aBerlin; Heidelberg; New York; London; Paris; TokyobSpringer-Verlagc2000/// a275 - 2851 aSorantin, Erich1 aHalmai, Csongor1 aErdőhelyi, Balázs1 aMartonossy, László1 aPalágyi, Kálmán1 aGeiger, Bernhard1 aHruby, Walter uhttps://www.inf.u-szeged.hu/publication/new-advances-for-imaging-of-laryngotracheal-stenosis-by-post-processing-of-spiral-ct-data00517nas a2200169 4500008004100000020001400041245005200055210005100107260000900158300001400167490000900181100001900190700002000209700002300229700001700252856007800269 2000 eng d a0302-974300aPoint-based registration assuming affine motion0 aPointbased registration assuming affine motion c2000 a329 - 3380 v18881 aTanacs, Attila1 aCzédli, Gábor1 aPalágyi, Kálmán1 aKuba, Attila uhttp://www.inf.u-szeged.hu/ipcg/publications/papers/Tanacs_2000_AFPAC.pdf00572nas a2200169 4500008004100000020001400041245006500055210006500120260001200185300001400197490000600211100002300217700002000240700002000260700001700280856010500297 1999 eng d a1428-639400a3D thinning and its applications to medical image processing0 a3D thinning and its applications to medical image processing c1999/// a397 - 4080 v31 aPalágyi, Kálmán1 aSorantin, Erich1 aHalmai, Csongor1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/3d-thinning-and-its-applications-to-medical-image-processing00723nas a2200145 4500008004100000020001400041245005000055210005000105260026900155300001400424490000900438100002300447700001700470856009000487 1999 eng d a0302-974300aDirectional 3D thinning using 8 subiterations0 aDirectional 3D thinning using 8 subiterations aBERTRAND G, 1994, P SPIE C VISION GEOM, V2356, P113BERTRAND G, 1995, PATTERN RECOGN LETT, V16, P979 GONG WX, 1990, P 10 INT C PATT REC, P188 KONG TY, 1989, COMPUT VISION GRAPH, V48, P357 KONG TY, 1995, INT J PATTERN RECOGN, V9, P813 LEE TC, 1994, CVGIP-GRc1999/// a325 - 3360 v15681 aPalágyi, Kálmán1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/directional-3d-thinning-using-8-subiterations00715nas a2200145 4500008004100000020001400041245005300055210005000108260026900158300001400427490000700441100002300448700001700471856008100488 1999 eng d a1077-316900aA parallel 3D 12-subiteration thinning algorithm0 aparallel 3D 12subiteration thinning algorithm aBERTRAND G, 1994, P SPIE C VISION GEOM, V2356, P113BERTRAND G, 1995, PATTERN RECOGN LETT, V16, P979 BLUM H, 1967, MODELS PERCEPTION SP, P362 BORGEFORS G, 1984, COMPUT VISION GRAPH, V27, P321 CALABI L, 1965, 60429 PARK MATH LAB GERIG G, 1993, LECT NOTES COc1999/// a199 - 2210 v611 aPalágyi, Kálmán1 aKuba, Attila uhttp://www.inf.u-szeged.hu/ipcg/publications/papers/PalagyiKuba_GMIP1999.pdf00717nas a2200181 4500008004100000245009200041210006900133260005800202300001400260100001900274700002300293700001700316700001400333700001500347700001700362700002200379856013400401 1999 eng d00aTarget registration error of point-based methods assuming rigid-body and linear motions0 aTarget registration error of pointbased methods assuming rigidbo aLjubljanabSlovenian Society of InformaticscAug 1999 a223 - 2331 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila1 aPernus, F1 aKovacic, S1 aStiehl, H, S1 aViergever, Max, A uhttps://www.inf.u-szeged.hu/publication/target-registration-error-of-point-based-methods-assuming-rigid-body-and-linear-motions-000781nas a2200145 4500008004100000020001400041245007100055210006800126260026900194300001400463490000700477100002300484700001700507856011100524 1998 eng d a0167-865500aA 3D 6-subiteration thinning algorithm for extracting medial lines0 a3D 6subiteration thinning algorithm for extracting medial lines aBERTRAND G, 1994, P SPIE C VISION GEOM, V2356, P113BERTRAND G, 1995, PATTERN RECOGN LETT, V16, P979 BLUM H, 1967, MODELS PERCEPTION SP, P362 GONG WX, 1990, P 10 INT C PATT REC, P188 KONG TY, 1989, COMPUT VISION GRAPH, V48, P357 LEE TC, 1994, CVGIP-GRAPH Mc1998/// a613 - 6270 v191 aPalágyi, Kálmán1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/a-3d-6-subiteration-thinning-algorithm-for-extracting-medial-lines00473nas a2200145 4500008004100000020001400041245005400055210005200109260001200161300001400173490000600187100002300193700001700216856009400233 1998 eng d a1330-113600aA hybrid thinning algorithm for 3D medical images0 ahybrid thinning algorithm for 3D medical images c1998/// a149 - 1640 v61 aPalágyi, Kálmán1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/a-hybrid-thinning-algorithm-for-3d-medical-images00597nas a2200157 4500008004100000020001400041245009200055210006900147260001200216300001400228490000600242100001900248700002300267700001700290856013200307 1998 eng d a1230-053500aMedical image registration based on interactively identified anatomical landmark points0 aMedical image registration based on interactively identified ana c1998/// a151 - 1580 v71 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/medical-image-registration-based-on-interactively-identified-anatomical-landmark-points00596nas a2200157 4500008004100000020001400041245009200055210006900147260000900216300001400225490000600239100001900245700002300264700001700287856013400304 1998 eng d a1230-053500aMedical image registration based on interactively identified anatomical landmark points0 aMedical image registration based on interactively identified ana c1998 a151 - 1580 v71 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila uhttps://www.inf.u-szeged.hu/publication/medical-image-registration-based-on-interactively-identified-anatomical-landmark-points-000551nas a2200157 4500008004100000245004400041210004300085260007600128300001200204100001900216700002300235700001700258700002100275700001800296856007900314 1998 eng d00aPont alapú regisztráció, képfúzió0 aPont alapú regisztráció képfúzió aBudapestbNeumann János Számítógép-tudományi TársaságcNov 1998 a67 - 701 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila1 aKozmann, György1 aSzakolczai, K uhttps://www.inf.u-szeged.hu/publication/pont-alapu-regisztracio-kepfuzio-000549nas a2200157 4500008004100000245004400041210004300085260007600128300001200204100001900216700002300235700001700258700002100275700001800296856007700314 1998 eng d00aPont alapú regisztráció, képfúzió0 aPont alapú regisztráció képfúzió aBudapestbNeumann János Számítógép-tudományi TársaságcNov 1998 a67 - 701 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila1 aKozmann, György1 aSzakolczai, K uhttps://www.inf.u-szeged.hu/publication/pont-alapu-regisztracio-kepfuzio00537nas a2200145 4500008004100000245004900041210004900090260007600139300001200215100002300227700001700250700002100267700001800288856008500306 1998 eng d00aVékonyító algoritmusok 3D orvosi képekre0 aVékonyító algoritmusok 3D orvosi képekre aBudapestbNeumann János Számítógép-tudományi TársaságcNov 1998 a63 - 661 aPalágyi, Kálmán1 aKuba, Attila1 aKozmann, György1 aSzakolczai, K uhttps://www.inf.u-szeged.hu/publication/vekonyito-algoritmusok-3d-orvosi-kepekre00555nas a2200145 4500008004100000245004800041210004500089260009600134300001200230100002300242700001700265700002000282700001900302856008800321 1997 eng d00aAn algorithm for thinning 3D medical images0 aalgorithm for thinning 3D medical images aKeszthelybPannon Agrártudományi Egyetem Georgikon Mezőgazdaságtudományi KarcOct 1997 a64 - 711 aPalágyi, Kálmán1 aKuba, Attila1 aSziranyi, Tamas1 aBerke, József uhttps://www.inf.u-szeged.hu/publication/an-algorithm-for-thinning-3d-medical-images00685nas a2200157 4500008004100000245008600041210007500127260009600202300001000298100001900308700002300327700001700350700002000367700001900387856012100406 1997 eng d00aOrvosi képek regisztrációja interaktívan kijelölt anatómiai pontok alapján0 aOrvosi képek regisztrációja interaktívan kijelölt anatómiai pont aKeszthelybPannon Agrártudományi Egyetem Georgikon Mezőgazdaságtudományi KarcOct 1997 a1 - 81 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila1 aSziranyi, Tamas1 aBerke, József uhttps://www.inf.u-szeged.hu/publication/orvosi-kepek-regisztracioja-interaktivan-kijelolt-anatomiai-pontok-alapjan-000683nas a2200157 4500008004100000245008600041210007500127260009600202300001000298100001900308700002300327700001700350700002000367700001900387856011900406 1997 eng d00aOrvosi képek regisztrációja interaktívan kijelölt anatómiai pontok alapján0 aOrvosi képek regisztrációja interaktívan kijelölt anatómiai pont aKeszthelybPannon Agrártudományi Egyetem Georgikon Mezőgazdaságtudományi KarcOct 1997 a1 - 81 aTanacs, Attila1 aPalágyi, Kálmán1 aKuba, Attila1 aSziranyi, Tamas1 aBerke, József uhttps://www.inf.u-szeged.hu/publication/orvosi-kepek-regisztracioja-interaktivan-kijelolt-anatomiai-pontok-alapjan00605nas a2200157 4500008004100000245007700041210006900118260003000187300001400217100002300231700001700254700001900271700002300290700001700313856011700330 1997 eng d00aA parallel 12-subiteration 3D thinning algorithm to extract medial lines0 aparallel 12subiteration 3D thinning algorithm to extract medial aBerlinbSpringerc1997/// a400 - 4071 aPalágyi, Kálmán1 aKuba, Attila1 aSommer, Gerald1 aDaniilidis, Kostas1 aPauli, Josef uhttps://www.inf.u-szeged.hu/publication/a-parallel-12-subiteration-3d-thinning-algorithm-to-extract-medial-lines00814nas a2200145 4500008004100000245007200041210006900113260028600182300001400468100002300482700001700505700001800522700001600540856011200556 1997 eng d00aA thinning algorithm to extract medial lines from 3D medical images0 athinning algorithm to extract medial lines from 3D medical image aBerlin; HeidelbergGERIG G, 1993, LECT NOTES COMPUTER, V687, P94GONG WX, 1990, P 10 INT C PATT REC, P188 KONG TY, 1989, COMPUT VISION GRAPH, V48, P357 LEE TC, 1994, CVGIP-GRAPH MODEL IM, V6, P462 MA CM, 1994, CVGIP-IMAG UNDERSTAN, V59, P328 PALAGYI K, 1996bSpringer Verlagc1997/// a411 - 4161 aPalágyi, Kálmán1 aKuba, Attila1 aDuncan, James1 aGindi, Gene uhttps://www.inf.u-szeged.hu/publication/a-thinning-algorithm-to-extract-medial-lines-from-3d-medical-images01278nas a2200217 4500008004100000245005800041210005800099260001300157300001200170520059300182100001700775700002000792700001600812700002800828700002300856700001800879700002200897700002200919700002100941856009800962 1996 eng d00aDICOM Based PACS and Its Application in the Education0 aDICOM Based PACS and Its Application in the Education cOct 1996 a46 - 493 aSZOTE-PACS is a DICOM based PACS developed at the Universitiesof Szeged. It is able to collect studies from different modalities and convert them into DICOM format. The DICOM studies can be edited, modified by RIS data, then verified and transferred into the archiving server. There is a graphic application based on Oracle for searching and other database management functions of the Archive. The archived studies can be presented and/or processed on the viewing workstations. SZOTE- PACS also supports the creation and presentation of educational materials fror medical students.
1 aKuba, Attila1 aAlexin, Zoltán1 aNagy, Antal1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aNagy, Mariann1 aAlmási, László1 aCsernay, László1 aOrphanoudakis, S uhttps://www.inf.u-szeged.hu/publication/dicom-based-pacs-and-its-application-in-the-education01280nas a2200217 4500008004100000245005800041210005800099260001300157300001200170520059300182100001700775700002000792700001600812700002800828700002300856700001800879700002200897700002200919700002100941856010000962 1996 eng d00aDICOM Based PACS and Its Application in the Education0 aDICOM Based PACS and Its Application in the Education cOct 1996 a46 - 493 aSZOTE-PACS is a DICOM based PACS developed at the Universitiesof Szeged. It is able to collect studies from different modalities and convert them into DICOM format. The DICOM studies can be edited, modified by RIS data, then verified and transferred into the archiving server. There is a graphic application based on Oracle for searching and other database management functions of the Archive. The archived studies can be presented and/or processed on the viewing workstations. SZOTE- PACS also supports the creation and presentation of educational materials fror medical students.
1 aKuba, Attila1 aAlexin, Zoltán1 aNagy, Antal1 aNyúl, László, Gábor1 aPalágyi, Kálmán1 aNagy, Mariann1 aAlmási, László1 aCsernay, László1 aOrphanoudakis, S uhttps://www.inf.u-szeged.hu/publication/dicom-based-pacs-and-its-application-in-the-education-000512nas a2200145 4500008004100000245005400041210005400095260003100149300001200180100002300192700002200215700001400237700002100251856009400272 1996 eng d00aMedical image registration based on fuzzy objects0 aMedical image registration based on fuzzy objects aBudapestbKFKIc1996.08.29 a44 - 481 aPalágyi, Kálmán1 aUdupa, Jayaram, K1 aTarnay, K1 aFazekas, Zoltán uhttps://www.inf.u-szeged.hu/publication/medical-image-registration-based-on-fuzzy-objects00510nas a2200133 4500008004100000245006300041210006300104260003000167300001400197100002300211700002200234700002100256856009900277 1996 eng d00aOrvosi képek fuzzy objektumokon alapuló regisztrációja0 aOrvosi képek fuzzy objektumokon alapuló regisztrációja aBudapestbNJSZTcNov 1996 a107 - 1101 aPalágyi, Kálmán1 aUdupa, Jayaram, K1 aKozmann, György uhttps://www.inf.u-szeged.hu/publication/orvosi-kepek-fuzzy-objektumokon-alapulo-regisztracioja02773nas a2200217 4500008004100000245012100041210007200162260003100234300001400265520192700279100001702206700002002223700002802243700001602271700002302287700002802310700002202338700002202360700002102382856015202403 1996 eng d00aSZOTE-PACS: A Szent-Györgyi Albert Orvostudományi Egyetem képarchiváló és továbbító rendszerének szoftvere0 aSZOTEPACS A SzentGyörgyi Albert Orvostudományi Egyetem képarchiv aVeszprémbNJSZTcNov 1996 a173 - 1763 aA Szent-Györgyi Albert Orvostudományi Egyetem kép-archiváló és -továbbító rendszer (SZOTE-PACS) szoftverének a fejlesztését ismertetjük előadásunkban. A cél egy olyan számítógépes hálózat elkészítése, amely nemcsak a klinikai vizsgálatok képeinek tárolásával és átvitelével kapcsolatos feladatokat látja el, de támogatja az oktatási és konzultációs tevékenységéeket is. A SZOTE-PACS 3 részre bontható: képfelvevő, archiváló és megjelenítő állomásokra. A képfelvevő munkaállomásoknak kettős feladata van: egyrészt a különféle modalitásokon (CT, MR, NM, US és SPECT) vagy röntgenfilm-scanneren felvett, illetve a DICOM- szabványnak megfelelő állomásról beérkező vizsgálatok begyűjtése, másrészt az Interfile 3.3, ACR-NEMA 2.0 vagy TIFF formátumú vizsgálatok DICOM formátumra való automatikus konvertálása. A rendszer képes a Radiológiai Klinika Információs Rendszerében (RIS) levő információk átvételére és beépítésére is. Az így előkészített vizsgálatok átküldhetők a központi szerverre, ahol azok az archívumban automatiksan tárolódnak. A jelenlegi diszk kapacitás mellett 15 napig őrizzük a vizsgálatokat. A tervek szerint 15 nap után csak a képeket töröljük a szerverről, a vizsgálat egyéb (nem képi) adatai továbbra is megőrzésre kerülnek. Az archívumban Oracle adatbázis kezeéő rendszer segíti a visszakeresést, a mejelenítést és a módosítást. A feldolgozó munkaállomásokra (PC-k, UNOX-állomások vagy X-terminálok) kérheti le a felhasználó a szerveren tárolt vizsgálatokat. Itt jeleníthetők meg illetve dolgozhatók fel a vizsgálatok képei. Az orvostanhallgatók és doktoranduszok képzésére HTML-ben írt oktatási anyagok állíthatók össze a tárolt szöveges és képi adatokból. Az oktatási anyagokat a rendszer külön adatbázisban tárolja.
1 aKuba, Attila1 aAlexin, Zoltán1 aNyúl, László, Gábor1 aNagy, Antal1 aPalágyi, Kálmán1 aDudásné Nagy, Mariann1 aCsernay, László1 aAlmási, László1 aKozmann, György uhttps://www.inf.u-szeged.hu/publication/szote-pacs-a-szent-gyorgyi-albert-orvostudomanyi-egyetem-keparchivalo-es-tovabbito-rendszerenek-szoftvere-002771nas a2200217 4500008004100000245012100041210007200162260003100234300001400265520192700279100001702206700002002223700002802243700001602271700002302287700002802310700002202338700002202360700002102382856015002403 1996 eng d00aSZOTE-PACS: A Szent-Györgyi Albert Orvostudományi Egyetem képarchiváló és továbbító rendszerének szoftvere0 aSZOTEPACS A SzentGyörgyi Albert Orvostudományi Egyetem képarchiv aVeszprémbNJSZTcNov 1996 a173 - 1763 aA Szent-Györgyi Albert Orvostudományi Egyetem kép-archiváló és -továbbító rendszer (SZOTE-PACS) szoftverének a fejlesztését ismertetjük előadásunkban. A cél egy olyan számítógépes hálózat elkészítése, amely nemcsak a klinikai vizsgálatok képeinek tárolásával és átvitelével kapcsolatos feladatokat látja el, de támogatja az oktatási és konzultációs tevékenységéeket is. A SZOTE-PACS 3 részre bontható: képfelvevő, archiváló és megjelenítő állomásokra. A képfelvevő munkaállomásoknak kettős feladata van: egyrészt a különféle modalitásokon (CT, MR, NM, US és SPECT) vagy röntgenfilm-scanneren felvett, illetve a DICOM- szabványnak megfelelő állomásról beérkező vizsgálatok begyűjtése, másrészt az Interfile 3.3, ACR-NEMA 2.0 vagy TIFF formátumú vizsgálatok DICOM formátumra való automatikus konvertálása. A rendszer képes a Radiológiai Klinika Információs Rendszerében (RIS) levő információk átvételére és beépítésére is. Az így előkészített vizsgálatok átküldhetők a központi szerverre, ahol azok az archívumban automatiksan tárolódnak. A jelenlegi diszk kapacitás mellett 15 napig őrizzük a vizsgálatokat. A tervek szerint 15 nap után csak a képeket töröljük a szerverről, a vizsgálat egyéb (nem képi) adatai továbbra is megőrzésre kerülnek. Az archívumban Oracle adatbázis kezeéő rendszer segíti a visszakeresést, a mejelenítést és a módosítást. A feldolgozó munkaállomásokra (PC-k, UNOX-állomások vagy X-terminálok) kérheti le a felhasználó a szerveren tárolt vizsgálatokat. Itt jeleníthetők meg illetve dolgozhatók fel a vizsgálatok képei. Az orvostanhallgatók és doktoranduszok képzésére HTML-ben írt oktatási anyagok állíthatók össze a tárolt szöveges és képi adatokból. Az oktatási anyagokat a rendszer külön adatbázisban tárolja.
1 aKuba, Attila1 aAlexin, Zoltán1 aNyúl, László, Gábor1 aNagy, Antal1 aPalágyi, Kálmán1 aDudásné Nagy, Mariann1 aCsernay, László1 aAlmási, László1 aKozmann, György uhttps://www.inf.u-szeged.hu/publication/szote-pacs-a-szent-gyorgyi-albert-orvostudomanyi-egyetem-keparchivalo-es-tovabbito-rendszerenek-szoftvere01510nas a2200205 4500008004100000245006500041210006300106260004100169300001400210520081800224100001701042700002001059700002301079700001601102700002801118700001901146700002001165700002001185856009901205 1996 eng d00aA többdimenziós képfeldolgozás programjai és oktatásuk0 atöbbdimenziós képfeldolgozás programjai és oktatásuk aDebrecenbDebreceni Egyetemc1996/// a649 - 6563 aNowdays, the multidimensional (i.e. higher than 2-dimensional)image processing has been a strongly developing area. One of its most important application areas is the medicine, where numerous diagnostic imaging devices (e.g., CT, MR, SPECT etc.) are able to produce 3- or even higher dimensional images. We have studied the possibility of introduction of multidimensional image processing into the subjects of Image Processing at József Attila University. First, we considered the methods of generation of such images, then the different standards accepted in the medical applications. From the processing algorithms we have dealt with the 3D skeletons, binary operations, reconstruction and registration. These topics are discussed in the education of graduated and PhD students as well. 1 aKuba, Attila1 aFazekas, Attila1 aPalágyi, Kálmán1 aNagy, Antal1 aNyúl, László, Gábor1 aPethő, Attila1 aBakonyi, Péter1 aHerdon, Miklós uhttps://www.inf.u-szeged.hu/publication/a-tobbdimenzios-kepfeldolgozas-programjai-es-oktatasuk01509nas a2200205 4500008004100000245006500041210006300106260003800169300001400207520081800221100001701039700002001056700002301076700001601099700002801115700001901143700002001162700002001182856010101202 1996 eng d00aA többdimenziós képfeldolgozás programjai és oktatásuk0 atöbbdimenziós képfeldolgozás programjai és oktatásuk aDebrecenbDebreceni Egyetemc1996 a649 - 6563 aNowdays, the multidimensional (i.e. higher than 2-dimensional)image processing has been a strongly developing area. One of its most important application areas is the medicine, where numerous diagnostic imaging devices (e.g., CT, MR, SPECT etc.) are able to produce 3- or even higher dimensional images. We have studied the possibility of introduction of multidimensional image processing into the subjects of Image Processing at József Attila University. First, we considered the methods of generation of such images, then the different standards accepted in the medical applications. From the processing algorithms we have dealt with the 3D skeletons, binary operations, reconstruction and registration. These topics are discussed in the education of graduated and PhD students as well. 1 aKuba, Attila1 aFazekas, Attila1 aPalágyi, Kálmán1 aNagy, Antal1 aNyúl, László, Gábor1 aPethő, Attila1 aBakonyi, Péter1 aHerdon, Miklós uhttps://www.inf.u-szeged.hu/publication/a-tobbdimenzios-kepfeldolgozas-programjai-es-oktatasuk-001885nas a2200193 4500008004100000245003600041210003600077260003400113300000700147520132200154100001701476700002301493700002801516700001601544700002201560700001601582700001501598856007801613 1995 eng d00aPresentation of 3D SPECT images0 aPresentation of 3D SPECT images aSmolenice, SlovakiacMay 1995 a823 aThe problem of presentation of 3D SPECT (Single-Photon EmissionComputed Tomography) images are considered. Instead of the classical 2D image presentation methods (displaying the slices) the following methods are studied: presentation of sections with a 3D reference image, generation of 3D phase and amplitude images (for gated heart studies), surface rendering and volume rendering by 3DVIEWNIX (MIGP, Univ. Pennsylvania) software. The projections are collected by a single-head SPECT system. After preprocessing (centre-of-rotation, uniformity correction) and reconstruction of the transversal sections absorption- correction and special 3D processing can be done. There are clinical programs for the different kinds of studies (e.g. brain SPECT, heart SPECT). The processed section images are stored and converted into Interfile 3.3 format. The first two presentation methods are available on our SPECT system. In order to use the 3DVIEWNIX software the file of the reconstructed sections is converted into a generalized ACR-NEMA format and transferred into our university network. The 3DVIEWNIX system runs on UNIX machines. It is suitable to visualize, manipulate and analyse multidimensional image data like SPECT. The results of the surface and volume rendering of brain and heart studies are presented.
1 aKuba, Attila1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aNagy, Antal1 aCsernay, László1 aBajla, Ivan1 aKarovic, K uhttps://www.inf.u-szeged.hu/publication/presentation-of-3d-spect-images-001883nas a2200193 4500008004100000245003600041210003600077260003400113300000700147520132200154100001701476700002301493700002801516700001601544700002201560700001601582700001501598856007601613 1995 eng d00aPresentation of 3D SPECT images0 aPresentation of 3D SPECT images aSmolenice, SlovakiacMay 1995 a823 aThe problem of presentation of 3D SPECT (Single-Photon EmissionComputed Tomography) images are considered. Instead of the classical 2D image presentation methods (displaying the slices) the following methods are studied: presentation of sections with a 3D reference image, generation of 3D phase and amplitude images (for gated heart studies), surface rendering and volume rendering by 3DVIEWNIX (MIGP, Univ. Pennsylvania) software. The projections are collected by a single-head SPECT system. After preprocessing (centre-of-rotation, uniformity correction) and reconstruction of the transversal sections absorption- correction and special 3D processing can be done. There are clinical programs for the different kinds of studies (e.g. brain SPECT, heart SPECT). The processed section images are stored and converted into Interfile 3.3 format. The first two presentation methods are available on our SPECT system. In order to use the 3DVIEWNIX software the file of the reconstructed sections is converted into a generalized ACR-NEMA format and transferred into our university network. The 3DVIEWNIX system runs on UNIX machines. It is suitable to visualize, manipulate and analyse multidimensional image data like SPECT. The results of the surface and volume rendering of brain and heart studies are presented.
1 aKuba, Attila1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aNagy, Antal1 aCsernay, László1 aBajla, Ivan1 aKarovic, K uhttps://www.inf.u-szeged.hu/publication/presentation-of-3d-spect-images00524nas a2200145 4500008004100000245004500041210004500086260006300131300001600194100001800210700002300228700001900251700002300270856008500293 1995 eng d00aSignature verification using neuron nets0 aSignature verification using neuron nets aRiver EdgebWorld Sci. Publishing, River Edge, NJc1995/// a1115 - 11221 aKatona, Endre1 aPalágyi, Kálmán1 aTóth, Nándor1 aBorgefors, Gunilla uhttps://www.inf.u-szeged.hu/publication/signature-verification-using-neuron-nets01558nas a2200181 4500008004100000245005600041210005600097260002700153300001400180520096900194100002801163700001601191700002301207700002001230700001701250700002001267856008901287 1994 eng d00aSzabványos képformák orvosi képek tárolására0 aSzabványos képformák orvosi képek tárolására aSzegedbSZOTEc1994/// a112 - 1163 aAz orvosi képalkotó berendezések fejlődésével elengedhetetlennévált a szabványos orvosi képformátumok kialakítása. A különféle eszközökön készült felvételek feldolgozását, összehasonlítását és hálózatban való továbbítását megnehezítette, hogy a gyártók a képeket csak egyéni, többé-kevésbé publikált formátumban tárolták. Ezen a helyzeten kívánnak változtatni különféle szervezetek olyan szabványok bevezetésével, amelyek speciálisan orvosi képek esetében lehetnek hasznosak. A szabványosítási törekvések eredményeként mára három nagy irányzat alakult ki: ACR-NEMA, DICOM és Interfile. Előadásunkban vázoljuk az orvosi képek tárolási formátumainál érvényesülő specifikus szempontokat, röviden ismertetjük az említett szabványokat és bemutatjuk az általunk eddig készített, a különféle formátumok közötti konverziót biztosító programokat. 1 aNyúl, László, Gábor1 aNagy, Antal1 aPalágyi, Kálmán1 aTolnai, József1 aKuba, Attila1 aHantos, Zoltán uhttps://www.inf.u-szeged.hu/publication/szabvanyos-kepformak-orvosi-kepek-tarolasara01557nas a2200181 4500008004100000245005600041210005600097260002400153300001400177520096900191100002801160700001601188700002301204700002001227700001701247700002001264856009101284 1994 eng d00aSzabványos képformák orvosi képek tárolására0 aSzabványos képformák orvosi képek tárolására aSzegedbSZOTEc1994 a112 - 1163 aAz orvosi képalkotó berendezések fejlődésével elengedhetetlennévált a szabványos orvosi képformátumok kialakítása. A különféle eszközökön készült felvételek feldolgozását, összehasonlítását és hálózatban való továbbítását megnehezítette, hogy a gyártók a képeket csak egyéni, többé-kevésbé publikált formátumban tárolták. Ezen a helyzeten kívánnak változtatni különféle szervezetek olyan szabványok bevezetésével, amelyek speciálisan orvosi képek esetében lehetnek hasznosak. A szabványosítási törekvések eredményeként mára három nagy irányzat alakult ki: ACR-NEMA, DICOM és Interfile. Előadásunkban vázoljuk az orvosi képek tárolási formátumainál érvényesülő specifikus szempontokat, röviden ismertetjük az említett szabványokat és bemutatjuk az általunk eddig készített, a különféle formátumok közötti konverziót biztosító programokat. 1 aNyúl, László, Gábor1 aNagy, Antal1 aPalágyi, Kálmán1 aTolnai, József1 aKuba, Attila1 aHantos, Zoltán uhttps://www.inf.u-szeged.hu/publication/szabvanyos-kepformak-orvosi-kepek-tarolasara-000477nas a2200133 4500008004100000020001400041245006700055210006700122260001200189300001400201490000700215100002300222856009800245 1993 eng d a0133-339900aLokális párhuzamos eljárás bináris képek zajszűrésére0 aLokális párhuzamos eljárás bináris képek zajszűrésére c1993/// a373 - 3960 v171 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/lokalis-parhuzamos-eljaras-binaris-kepek-zajszuresere00429nas a2200133 4500008004100000245003900041210003900080260002900119300001200148100001900160700002300179700001400202856007900216 1991 eng d00aImage processing on cellprocessors0 aImage processing on cellprocessors aBudapestbNJSZTc1991/// a31 - 401 aKöles, Péter1 aPalágyi, Kálmán1 aGyorgy, A uhttps://www.inf.u-szeged.hu/publication/image-processing-on-cellprocessors00482nas a2200133 4500008004100000245005600041210005600097260002900153300001400182100001900196700002300215700001400238856009600252 1991 eng d00aNeural Network Implementation on Cellular Processor0 aNeural Network Implementation on Cellular Processor aBudapestbNJSZTc1991/// a129 - 1371 aTóth, Nándor1 aPalágyi, Kálmán1 aGyorgy, A uhttps://www.inf.u-szeged.hu/publication/neural-network-implementation-on-cellular-processor00538nas a2200157 4500008004100000245005400041210005400095260003700149300001400186100001500200700002300215700001200238700002000250700001600270856009400286 1990 eng d00aCellular program development for the M1 processor0 aCellular program development for the M1 processor aBerlinbAkademie Verlagc1990/// a315 - 3191 aTűzkő, T1 aPalágyi, Kálmán1 aWolf, G1 aLegendi, Tamás1 aSchendel, U uhttps://www.inf.u-szeged.hu/publication/cellular-program-development-for-the-m1-processor00764nas a2200133 4500008004100000020001400041245007600055210006900131260026900200300001400469490000800483100002300491856011600514 1989 eng d a0302-974300aSOLUTION OF DENSE SYSTEMS OF LINEAR-EQUATIONS USING CELLULAR PROCESSORS0 aSOLUTION OF DENSE SYSTEMS OF LINEAREQUATIONS USING CELLULAR PROC aBOYANCZYK A, 1981, NUMERICALLY STABLE S, P21HWANG K, 1982, IEEE T COMPUT, V31, P1215 KATONA E, 1986, PARALLEL COMPUTING 8 KATONA E, 1988, 4TH P CELL M TU BRAU KUNG HT, 1978, SYSTOLIC ARRAYS, P32 LEGENDI T, 1977, CELLPROCESSORS COMPU, V11, P147 MIKLOSKO J,c1989/// a311 - 3160 v3421 aPalágyi, Kálmán uhttps://www.inf.u-szeged.hu/publication/solution-of-dense-systems-of-linear-equations-using-cellular-processors00552nas a2200157 4500008004100000245005000041210005000091260005700141300001400198100002300212700002000235700002200255700001500277700001200292856009000304 1987 eng d00aCellular algorithms for matrix multiplication0 aCellular algorithms for matrix multiplication aAmsterdambNorth-Holland Publishing Companyc1987/// a122 - 1291 aPalágyi, Kálmán1 aLegendi, Tamás1 aParkinson, Dennis1 aVollmar, R1 aWolf, G uhttps://www.inf.u-szeged.hu/publication/cellular-algorithms-for-matrix-multiplication