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Magyarul

Selected Publications of the Department of Image Processing and Computer Graphics of the year 2006

Books and proceedings

1. Attila Kuba, Laszlo G. Nyul, and Kalman Palagyi, editors. Discrete Geometry for Computer Imagery, volume 4245 of Lecture Notes in Computer Science. Springer Verlag, October 2006. [WWW] [doi:10.1007/11907350]
   Abstract: This 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.
   @BOOK{Kuba2006,
   PUBLISHER = {Springer Verlag},
   TITLE = {Discrete Geometry for Computer Imagery},
   YEAR = {2006},
   EDITOR = {Attila Kuba and Laszlo G. Nyul and Kalman Palagyi},
   MONTH = {October},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {4245},
   PAGES = {688},
   URL = {http://www.springerlink.com/content/t38633812l42/},
   DOI = {10.1007/11907350},
   }
   

Articles in journal or book chapters

1. Gabor Fichtinger, Everette C. Burdette, Attila Tanacs, Alexandru Patriciu, Dumitru Mazilu, Louis L. Whitcomb, and Dan Stoianovici. Robotically assisted prostate brachytherapy with transrectal ultrasound guidance --- Phantom experiments. Brachytherapy, 5:14-26, 2006. [PDF] [doi:doi:10.1016/j.brachy.2005.10.003]
   Abstract: {\bf PURPOSE:} To report the preliminary experimental results obtained with a robot-assisted trans-rectal ultrasound (TRUS)--guided prostate brachytherapy system. {\bf METHODS AND MATERIALS:} The system consists of a TRUS unit, a spatially coregistered needle insertion robot, and an FDA-approved treatment planning and image-registered implant system. The robot receives each entry/target coordinate pair of the implant plan, inserts a preloaded needle, and then the seeds are deposited. The needles/sources are tracked in TRUS, thus allowing the plan to be updated as the procedure progresses. {\bf RESULTS:} The first insertion attempt was recorded for each needle, without adjustment. All clinically relevant locations were reached in a prostate phantom. Nonparallel and parallel needle trajectories were demonstrated. Based on TRUS, the average transverse placement error was 2 mm (worst case 2.5 mm, 80% less than 2 mm), and the average sagittal error was 2.5 mm (worst case 5.0 mm, 70% less than 2.5 mm). {\bf CONCLUSIONS:} The concept and technical viability of robot-assisted brachytherapy were demonstrated in phantoms. The kinematically decoupled robotic assistant device is inherently safe. Overall performance was promising, but further optimization is necessary to prove the possibility of improved dosimetry.
   @ARTICLE{Fichtinger:2006:Brachytherapy,
   AUTHOR = {Gabor Fichtinger and Everette C. Burdette and Attila Tanacs and Alexandru Patriciu and Dumitru Mazilu and Louis L. Whitcomb and Dan Stoianovici},
   JOURNAL = {Brachytherapy},
   TITLE = {Robotically assisted prostate brachytherapy with transrectal ultrasound guidance --- Phantom experiments},
   YEAR = {2006},
   PAGES = {14--26},
   VOLUME = {5},
   DOI = {doi:10.1016/j.brachy.2005.10.003},
   }
   


2. Zoltan Kato and Ting Chuen Pong. A Markov Random Field Image Segmentation Model for Color Textured Images. Image and Vision Computing, 24(10):1103-1114, October 2006. [PDF]
   Abstract: We propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian estimation via combinatorial optimization (Simulated Annealing). The segmentation is obtained by classifying the pixels into different pixel classes. These classes are represented by multi-variate Gaussian distributions. Thus, the only hypothesis about the nature of the features is that an additive Gaussian noise model is suitable to describe the feature distribution belonging to a given class. Here, we use the perceptually uniform CIE-L*u*v* color values as color features and a set of Gabor filters as texture features. Gaussian parameters are either computed using a training data set or estimated from the input image. We also propose a parameter estimation method using the EM algorithm. Experimental results are provided to illustrate the performance of our method on both synthetic and natural color images.
   @ARTICLE{Kato-Pong2006a,
   AUTHOR = {Zoltan Kato and Ting Chuen Pong},
   JOURNAL = {Image and Vision Computing},
   TITLE = {A Markov Random Field Image Segmentation Model for Color Textured Images},
   YEAR = {2006},
   MONTH = {October},
   NUMBER = {10},
   PAGES = {1103--1114},
   VOLUME = {24},
   PUBLISHER = {Elsevier},
   }
   


3. Zoltan Kiss, Lajos Rodek, and Attila Kuba. Image reconstruction and correction methods in neutron and X-ray tomography. Acta Cybernetica, 17(3):557-587, 2006. [WWW]
   Abstract: Neutron and X-ray tomography are imaging techniques for getting information about the interior of objects in a non-destructive way. They reconstruct cross-sections from projection images of the object being investigated. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. Taking projections is usually an expensive and time consuming procedure. One of our main goals has been to try to minimize the number of projections - for example, by exploiting more a priori information. A possible way of reducing the number of projections is by the application of discrete tomographic methods. In this case a special class of objects can be reconstructed, consisting of only a few homogenous materials that can be characterized by known discrete absorption values. To this end we have implemented two reconstruction methods. One is able to reconstruct objects consisting of cylinders and spheres made of homogeneous materials only. The other method is a general one in the sense that it can be used for reconstructing any shape. Simulations on phantoms and physical measurements were carried out and the results are presented here.
   @ARTICLE{Kiss2006356,
   AUTHOR = {Zoltan Kiss and Lajos Rodek and Attila Kuba},
   JOURNAL = {Acta Cybernetica},
   TITLE = {Image reconstruction and correction methods in neutron and X-ray tomography},
   YEAR = {2006},
   NUMBER = {3},
   PAGES = {557-587},
   VOLUME = {17},
   URL = {http://www.inf.u-szeged.hu/actacybernetica/vol17n3/08_Kiss.xml},
   }
   


4. Antal Nagy and Attila Kuba. Parameter settings for reconstructing binary matrices from fan-beam projections. Journal of Computing and Information Technology, 14(2):100-110, 2006. [PDF]
   Abstract: The problem of reconstruction of binary matrices from their fan-beam projections is studied. A fan-beam pro- jection model is implemented and used in systematic ex- periments in order to determine the optimal parameter values for data acquisition and reconstruction algorithm. The fan-beam model, the reconstruction algorithm, the simulation experiments, and the results are discussed in the paper.
   @ARTICLE{NagyKuba:2004:ParamFanBeam,
   AUTHOR = {Antal Nagy and Attila Kuba},
   JOURNAL = {Journal of Computing and Information Technology},
   TITLE = {Parameter settings for reconstructing binary matrices from fan-beam projections},
   YEAR = {2006},
   NUMBER = {2},
   PAGES = {100--110},
   VOLUME = {14},
   }
   


5. Krisztian Olle, Balazs Erdohelyi, Endre Varga, Csongor Halmai, and Attila Kuba. MedEdit: A Computer Assisted Image Processing and Navigation System for Orthopedic Trauma Surgery. Acta Cybernetica, 17:589-603, July 2006. [PDF]
   Abstract: The surgery of fractured bones is often a very complex problem. That is the reason why it would be beneficial to create a geometric and mechanic model of the bones before surgical intervention. The model geometry is based on the CT images of the patient and the known physical properties of the bone. A computerised system is presented here, called MedEdit, which helps a surgeon plan an operation. The system includes a Finite Element Analysis (FEA) program to measure the stress effects of the possible surgical solutions. Following the simulation and analysis of the behaviour of the modelled bone, surgeons can find the best surgical solution for the patient.
   @ARTICLE{Olle2006,
   AUTHOR = {Krisztian Olle and Balazs Erdohelyi and Endre Varga and Csongor Halmai and Attila Kuba},
   JOURNAL = {Acta Cybernetica},
   TITLE = {MedEdit: A Computer Assisted Image Processing and Navigation System for Orthopedic Trauma Surgery},
   YEAR = {2006},
   MONTH = {July},
   PAGES = {589-603},
   VOLUME = {17},
   }
   


6. Kalman Palagyi, Juerg Tschirren, Eric A. Hoffman, and Milan Sonka. Quantitative analysis of pulmonary airway tree structure. Computers in Biology and Medicine, 36:974-996, 2006. [PDF]
   Abstract: A 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).
   @ARTICLE{PalagyiEtalCBM2006,
   AUTHOR = {Kalman Palagyi and Juerg Tschirren and Eric A. Hoffman and Milan Sonka},
   JOURNAL = {Computers in Biology and Medicine},
   TITLE = {Quantitative analysis of pulmonary airway tree structure},
   YEAR = {2006},
   PAGES = {974-996},
   VOLUME = {36},
   }
   

Conference articles

1. Peter Balazs. The number of line-convex directed polyominoes having the same orthogonal projections. In Attila Kuba, Laszlo G. Nyul, and Kalman Palagyi, editors, Proceedings of the International Conference on Discrete Geometry for Computer Imagery, volume 4245 of Lecture Notes in Computer Science, Szeged, Hungary, pages 77-85, October 2006. Springer Verlag. [PDF]
   Abstract: The number of line-convex directed polyominoes with given horizontal 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.
   @INPROCEEDINGS{Balazs2006,
   AUTHOR = {Peter Balazs},
   BOOKTITLE = {Proceedings of the International Conference on Discrete Geometry for Computer Imagery},
   TITLE = {The number of line-convex directed polyominoes having the same orthogonal projections},
   YEAR = {2006},
   ADDRESS = {Szeged, Hungary},
   EDITOR = {Attila Kuba and Laszlo G. Nyul and Kalman Palagyi},
   MONTH = {October},
   PAGES = {77-85},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {4245},
   }
   


2. Sara Brunetti, Alain Daurat, and Attila Kuba. Fast Filling Operations Used in the Reconstruction of Convex Lattice Sets. In Attila Kuba, Laszlo G. Nyul, and Kalman Palagyi, editors, Proceedings of the International Conference on Discrete Geometry for Computer Imagery, volume 4245 of Lecture Notes in Computer Science, Szeged, Hungary, pages 98-109, October 2006. Springer Verlag. [PDF] [doi:10.1007/11907350_9]
   Abstract: Filling operations are procedures which are used in Discrete Tomography for the reconstruction of lattice sets having some convexity constraints. In [1], an algorithm which performs four of these filling operations has a time complexity of O(N2 logN), where N is the size of projections, and leads to a reconstruction algorithm for convex polyominoes running in O(N6 logN)-time. In this paper we first improve the implementation of these four filling operations to a time complexity of O(N2), and additionally we provide an implementation of a fifth filling operation (introduced in [2]) in O(N2 logN) that permits to decrease the overall time-complexity of the reconstruction algorithm to O(N4 logN). More generally, the reconstruction of Q-convex sets and convex lattice sets (intersection of a convex polygon with Z2) can be done in O(N4 logN)-time.
   @INPROCEEDINGS{Brunetti2006,
   AUTHOR = {Sara Brunetti and Alain Daurat and Attila Kuba},
   BOOKTITLE = {Proceedings of the International Conference on Discrete Geometry for Computer Imagery},
   TITLE = {Fast Filling Operations Used in the Reconstruction of Convex Lattice Sets},
   YEAR = {2006},
   ADDRESS = {Szeged, Hungary},
   EDITOR = {Attila Kuba and Laszlo G. Nyul and Kalman Palagyi},
   MONTH = {October},
   PAGES = {98-109},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {4245},
   DOI = {10.1007/11907350_9},
   }
   


3. Peter Horvath, Ian Jermyn, Zoltan Kato, and Josiane Zerubia. A Higher-Order Active Contour Model for Tree Detection. In Proceedings of the International Conference on Pattern Recognition, volume 2, Hong Kong, China, pages 130-133, August 2006. IAPR, IEEE. [PDF]
   Abstract: We present a model of a 'gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short range repulsive interactions, and apply it to the extraction of tree crowns from aerial images. The method uses the recently introduced 'higher order active contours' (HOACs), which incorporate long-range interactions between contour points, and thereby include prior geometric information without using a template shape. This makes them ideal when looking for multiple instances of an entity in an image. We study an existing HOAC model for networks, and show via a stability calculation that circles stable to perturbations are possible for constrained parameter sets. Combining this prior energy with a data term, we show results on aerial imagery that demonstrate the effectiveness of the method and the need for prior geometric knowledge. The model has many other potential applications.
   @INPROCEEDINGS{Horvath-etal2006,
   AUTHOR = {Peter Horvath and Ian Jermyn and Zoltan Kato and Josiane Zerubia},
   BOOKTITLE = {Proceedings of the International Conference on Pattern Recognition},
   TITLE = {A Higher-Order Active Contour Model for Tree Detection},
   YEAR = {2006},
   ADDRESS = {Hong Kong, China},
   MONTH = {August},
   ORGANIZATION = {IAPR},
   PAGES = {130--133},
   PUBLISHER = {IEEE},
   VOLUME = {2},
   }
   


4. Peter Horvath, Ian Jermyn, Zoltan Kato, and Josiane Zerubia. An improved `gas of circles' higher-order active contour model and its application to tree crown extraction. In Prem Kalra and Shmuel Peleg, editors, Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing, volume 4338 of Lecture Notes in Computer Science, Madurai, India, pages 152-161, December 2006. Springer Verlag. [PDF]
   Abstract: A central task in image processing is to find the region in the image corresponding to an entity. In a number of problems, the region takes the form of a collection of circles, e.g. tree crowns in remote sensing imagery; cells in biological and medical imagery. In [1], a model of such regions, the 'gas of circles' model, was developed based on higher-order active contours, a recently developed framework for the inclusion of prior knowledge in active contour energies. However, the model suffers from a defect. In [1], the model parameters were adjusted so that the circles were local energy minima. Gradient descent can become stuck in these minima, producing phantom circles even with no supporting data. We solve this problem by calculating, via a Taylor expansion of the energy, parameter values that make circles into energy inflection points rather than minima. As a bonus, the constraint halves the number of model parameters, and severely constrains one of the two that remain, a major advantage for an energy-based model. We use the model for tree crown extraction from aerial images. Experiments show that despite the lack of parametric freedom, the new model performs better than the old, and much better than a classical active contour.
   @INPROCEEDINGS{Horvath-etal2006a,
   AUTHOR = {Peter Horvath and Ian Jermyn and Zoltan Kato and Josiane Zerubia},
   BOOKTITLE = {Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing},
   TITLE = {An improved `gas of circles' higher-order active contour model and its application to tree crown extraction},
   YEAR = {2006},
   ADDRESS = {Madurai, India},
   EDITOR = {Prem Kalra and Shmuel Peleg},
   MONTH = {December},
   PAGES = {152--161},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {4338},
   }
   


5. Zoltan Kato and Ting Chuen Pong. A Multi-Layer MRF Model for Video Object Segmentation. In P. J. Narayanan, Shree K. Nayar, and Heung-Yeung Shum, editors, Proceedings of the Asian Conference on Computer Vision, volume 3852 of Lecture Notes in Computer Science, Hyderabad, India, pages 953-962, January 2006. Springer Verlag. [PDF]
   Abstract: A novel video object segmentation method is proposed which aims at combining color and motion information. The model has a multilayer structure: Each feature has its own layer, called feature layer, where a classical Markov random field (MRF) image segmentation model is defined using only the corresponding feature. A special layer is assigned to the combined MRF model, called combined layer, which interacts with each feature layer and provides the segmentation based on the combination of different features. Unlike previous methods, our approach doesn’t assume motion boundaries being part of spatial ones. Therefore a very important property of the proposed method is the ability to detect boundaries that are visible only in the motion feature as well as those visible only in the color one. The method is validated on synthetic and real video sequences.
   @INPROCEEDINGS{Kato-Pong2006,
   AUTHOR = {Zoltan Kato and Ting Chuen Pong},
   BOOKTITLE = {Proceedings of the Asian Conference on Computer Vision},
   TITLE = {A Multi-Layer MRF Model for Video Object Segmentation},
   YEAR = {2006},
   ADDRESS = {Hyderabad, India},
   EDITOR = {P. J. Narayanan and Shree K. Nayar and Heung-Yeung Shum},
   MONTH = {January},
   PAGES = {953--962},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {3852},
   }
   


6. Stefan Weber, Antal Nagy, Thomas Schule, Christoph Schnorr, and Attila Kuba. A Benchmark Evaluation of Large-Scale Optimization Approaches to Binary Tomography. In Attila Kuba, Laszlo G. Nyul, and Kalman Palagyi, editors, Proceedings of the International Conference on Discrete Geometry for Computer Imagery, volume 4245 of Lecture Notes in Computer Science, Szeged, Hungary, pages 146-156, October 2006. Springer Verlag. [PDF] [doi:10.1007/11907350_13]
   Abstract: Discrete tomography concerns the reconstruction of functions with a finite number of values from few projections. For a number of important real-world problems, this tomography problem involves thousands of variables. Applicability and performance of discrete tomography therefore largely depend on the criteria used for reconstruction and the optimization algorithm applied. From this viewpoint, we evaluate two major optimization strategies, simulated annealing and convex-concave regularization, for the case of binary-valued functions using various data sets. Extensive numerical experiments show that despite being quite different from the viewpoint of optimization, both strategies show similar reconstruction performance as well as robustness to noise.
   @INPROCEEDINGS{Weber2006,
   AUTHOR = {Stefan Weber and Antal Nagy and Thomas Schule and Christoph Schnorr and Attila Kuba},
   BOOKTITLE = {Proceedings of the International Conference on Discrete Geometry for Computer Imagery},
   TITLE = {A Benchmark Evaluation of Large-Scale Optimization Approaches to Binary Tomography},
   YEAR = {2006},
   ADDRESS = {Szeged, Hungary},
   EDITOR = {Attila Kuba and Laszlo G. Nyul and Kalman Palagyi},
   MONTH = {October},
   PAGES = {146-156},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {4245},
   DOI = {10.1007/11907350_13},
   }
   


7. Stefan Weber, Thomas Schule, Attila Kuba, and Christoph Schnorr. Binary Tomography with Deblurring. In R. Reulke, U. Eckardt, B. Flach, U. Knauer, and K. Polthier, editors, Proceedings of the International Workshop on Combinatorial Image Analysis, volume 4040 of Lecture Notes in Computer Science, Berlin, Germany, pages 375-388, June 2006. Springer Verlag. [WWW] [doi:10.1007/11774938]
   Abstract: We study two scenarios of limited-angle binary tomography with data distorted with an unknown convolution: Either the projection data are taken from a blurred object, or the projection data themselves are blurred. These scenarios are relevant in case of scattering and due to a finite resolution of the detectors. Assuming that the unknown blurring process is adequately modeled by an isotropic Gaussian convolution kernel with unknown scale-parameter, we show that parameter estimation can be combined with the reconstruction process. To this end, a recently introduced Difference-of-Convex-Functions programming approach to limited-angle binary tomographic reconstruction is complemented with Expectation-Maximization iteration. Experimental results show that the resulting approach is able to cope with both ill-posed problems, limited-angle reconstruction and deblurring, simultaneously.
   @INPROCEEDINGS{Weber2006a,
   AUTHOR = {Stefan Weber and Thomas Schule and Attila Kuba and Christoph Schnorr},
   BOOKTITLE = {Proceedings of the International Workshop on Combinatorial Image Analysis},
   TITLE = {Binary Tomography with Deblurring},
   YEAR = {2006},
   ADDRESS = {Berlin, Germany},
   EDITOR = {R. Reulke and U. Eckardt and B. Flach and U. Knauer and K. Polthier},
   MONTH = {June},
   PAGES = {375-388},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {4040},
   URL = {http://www.springerlink.com/content/u2t064111r714746},
   DOI = {10.1007/11774938},
   }
   

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