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Selected Publications of the Department of Image Processing and Computer Graphics of the year 2001

Articles in journal or book chapters

1. Emese Balogh, Attila Kuba, Csaba Devenyi, and Alberto Del Lungo. Comparison of algorithms for reconstructing hv-convex discrete sets. Linear Algebra and its Applications, 339:23-35, December 2001. [PDF] [doi:10.1016/S0024-3795(01)00430-X]
   Abstract: Three reconstruction algorithms to be used for reconstructing hv-convex discrete sets from their row and column sums are compared. All these algorithms have two versions: one for reconstructing hv-convex polyominoes and another one for reconstructing hv-convex 8-connected discrete sets. In both classes of discrete sets the algorithms are compared from the viewpoints of average execution time and memory complexities. Discrete sets with given sizes are generated with uniform distribution, and then reconstructed from their row and column sums. First we have implemented two previously published algorithms. According to our comparisons, the algorithm which was better from the viewpoint of worst time complexity was the worse from the viewpoint of average time complexity and memory requirements. Then, as a new method, a combination of the two algorithms was also implemented and it is shown that it inherits the best properties of the other two methods.
   
   @ARTICLE{Balogh2001,
   AUTHOR = {Emese Balogh and Attila Kuba and Csaba Devenyi and Alberto Del Lungo},
   JOURNAL = {Linear Algebra and its Applications},
   TITLE = {Comparison of algorithms for reconstructing hv-convex discrete sets},
   YEAR = {2001},
   MONTH = {December},
   PAGES = {23-35},
   VOLUME = {339},
   DOI = {10.1016/S0024-3795(01)00430-X},
   }


2. Sara Brunetti, Alberto DelLungo, F. DelRistoro, Attila Kuba, and Maurice Nivat. Reconstruction of 4- and 8-connected convex discrete sets from row and column projections. Linear Algebra and its Applications, 339:37-57, 2001. [PDF] [doi:10.1016/S0024-3795(01)00435-9]
   Abstract: In this paper we examine the problem of reconstructing a discrete two-dimensional set from its two orthogonal projection (H,V) when the set satisfies some convexity conditions. We show that the algorithm of the paper [Int. J. Imaging Systems and Technol. 9 (1998) 69] is a good heuristic algorithm but it does not solve the problem for all (H,V) instances. We propose a modification of this algorithm solving the problem for all (H,V) instances, by starting to build the ``spine''. The complexity of our reconstruction algorithm is O(mnˇlog(mn)ˇmin{m2,n2}) in the worst case. However, according to our experimental results, in 99% of the studied cases the algorithm is able to reconstruct a solution without using the newly introduced operation. In such cases the upper bound of the complexity of the algorithm is O(mnˇlog(mn)). A systematic comparison of this algorithm was done and the results show that this algorithm has the better average complexity than other published algorithms. The way of comparison and the results are given in a separate paper [Linear Algebra Appl. (submitted)]. Finally we prove that the problem can be solved in polynomial time also in a class of discrete sets which is larger than the class of convex polyominoes, namely, in the class of 8-connected convex sets.
   
   @ARTICLE{Brunetti2001,
   AUTHOR = {Sara Brunetti and Alberto DelLungo and F. DelRistoro and Attila Kuba and Maurice Nivat},
   JOURNAL = {Linear Algebra and its Applications},
   TITLE = {Reconstruction of 4- and 8-connected convex discrete sets from row and column projections},
   YEAR = {2001},
   PAGES = {37-57},
   VOLUME = {339},
   DOI = {10.1016/S0024-3795(01)00435-9},
   }


3. Yulin Ge, Robert I. Grossman, Jayaram K. Udupa, James S. Babb, Laszlo G. Nyul, and Dennis L. Kolson. Brain Atrophy in Relapsing-remitting Multiple Sclerosis: Fractional Volumetric Analysis of Gray Matter and White Matter. Radiology, 220(3):606-610, September 2001. [PDF]
   Abstract: PURPOSE: To determine the fractional brain tissue volume changes in the gray matter and white matter of patients with relapsing-remitting multiple sclerosis (MS) and to correlate these measurements with clinical disability and total lesion load. MATERIALS AND METHODS: Thirty patients with relapsing-remitting MS and 25 healthy control subjects underwent magnetic resonance imaging. Fractional brain tissue volumes (tissue volume relative to total intracranial volume) were obtained from the total segmented gray matter and white matter in each group and were analyzed. RESULTS: The fractional volume of white matter versus that of gray matter was significantly lower (26.4%) in patients with MS (P , .0001) than in control subjects. Neither gray matter nor white matter fractional volume measurements correlated with clinical disability in the patients with MS. CONCLUSION: Loss of brain parenchymal volume in patients with relapsing-remitting MS is predominantly confined to white matter. Analysis of fractional brain tissue volumes provides additional information useful in characterizing MS and may have potential in evaluating treatment strategies.
   
   @ARTICLE{Ge:2001:BAR,
   AUTHOR = {Yulin Ge and Robert I. Grossman and Jayaram K. Udupa and James S. Babb and Laszlo G. Nyul and Dennis L. Kolson},
   JOURNAL = {Radiology},
   TITLE = {Brain Atrophy in Relapsing-remitting Multiple Sclerosis: Fractional Volumetric Analysis of Gray Matter and White Matter},
   YEAR = {2001},
   MONTH = {September},
   NUMBER = {3},
   PAGES = {606--610},
   VOLUME = {220},
   }


4. Zoltan Kato, Ting Chuen Pong, and John Chung Mong Lee. Color Image Segmentation and Parameter Estimation in a Markovian Framework. Pattern Recognition Letters, 22(3-4):309-321, March 2001. [PDF] Keyword(s): Unsupervised image segmentation, Color, Markov random fields, Pixel classification, Parameter estimation.
   Abstract: An unsupervised color image segmentation algorithm is presented, using a Markov random field (MRF) pixel classification model. We propose a new method to estimate initial mean vectors effectively even if the histogram does not have clearly distinguishable peaks. The only parameter supplied by the user is the number of classes.
   
   @ARTICLE{Kato-etal2001,
   AUTHOR = {Zoltan Kato and Ting Chuen Pong and John Chung Mong Lee},
   JOURNAL = {Pattern Recognition Letters},
   TITLE = {Color Image Segmentation and Parameter Estimation in a Markovian Framework},
   YEAR = {2001},
   MONTH = {March},
   NUMBER = {3-4},
   PAGES = {309--321},
   VOLUME = {22},
   KEYWORDS = {Unsupervised image segmentation, Color, Markov random fields, Pixel classification, Parameter estimation},
   }


5. Attila Kuba and Maurice Nivat. Reconstruction of discrete sets with absorption. Linear Algebra and its Applications, 339:171-194, 2001. [WWW] [PDF] [doi:10.1016/S0024-3795(01)00486-4]
   Abstract: The uniqueness problem is considered when binary matrices are to be reconstructed from their absorbed row and column sums. Let the absorption coefficient n be selected such that en = (1+5^0.5)/2. Then it is proved that if a binary matrix is non-uniquely determined, then it contains a special pattern of 0s and 1s called composition of alternatively corner-connected components. In a previous paper [Discrete Appl. Math. (submitted)] we proved that this condition is also sufficient, i.e., the existence of such a pattern in the binary matrix is necessary and sufficient for its non-uniqueness.
   
   @ARTICLE{Kuba2001a,
   AUTHOR = {Attila Kuba and Maurice Nivat},
   JOURNAL = {Linear Algebra and its Applications},
   TITLE = {Reconstruction of discrete sets with absorption},
   YEAR = {2001},
   PAGES = {171-194},
   VOLUME = {339},
   URL = {http://www.sciencedirect.com/science/article/B6V0R-44CHW26-C/2/e4cd2b3dc91dbb828db15e331a6230cc},
   DOI = {10.1016/S0024-3795(01)00486-4},
   }


6. Kalman Palagyi. A 3D parallel shrinking algorithm. Acta Cybernetica, 15:201-211, 2001. [PDF]
   Abstract: 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.
   
   @ARTICLE{PalagyiAC2001,
   AUTHOR = {Kalman Palagyi},
   JOURNAL = {Acta Cybernetica},
   TITLE = {A 3D parallel shrinking algorithm},
   YEAR = {2001},
   PAGES = {201-211},
   VOLUME = {15},
   }


7. Attila Tanacs, Gabor Czedli, Kalman Palagyi, and Attila Kuba. Affine matching of two sets of points in arbitrary dimensions. Acta Cybernetica, 15:101-106, 2001. [PDF]
   Abstract: In many applications of computer vision, image processing, and remotely sensed data processing, an appropriate matching of two sets of points is required. Our approach assumes one--to--one correspondence between these sets and finds the optimal global affine transformation that matches them. The suggested method can be used in arbitrary dimensions. A sufficient existence condition for a unique transformation is given and proven.
   
   @ARTICLE{Tanacs:2001:Acta,
   AUTHOR = {Attila Tanacs and Gabor Czedli and Kalman Palagyi and Attila Kuba},
   JOURNAL = {Acta Cybernetica},
   TITLE = {Affine matching of two sets of points in arbitrary dimensions},
   YEAR = {2001},
   PAGES = {101--106},
   VOLUME = {15},
   }


8. Jayaram K. Udupa, Laszlo G. Nyul, Yulin Ge, and Robert I. Grossman. Multiprotocol MR Image Segmentation in Multiple Sclerosis: Experience With Over 1000 Studies. Academic Radiology, 8(11):1116-1126, November 2001. [PDF]
   Abstract: Rationale and Objectives. Multiple sclerosis (MS) is an acquired disease of the central nervous system. Several clinical measures are commonly used to express the severity of the disease, including the Expanded Disability Status Scale and the ambulation index. These measures are subjective and may be difficult to reproduce. The aim of this research is to investigate the possibility of developing more objective measures derived from MR imaging. Materials and Methods. Various magnetic resonance (MR) imaging protocols are being investigated for the study of MS. Seeking to replace the Expanded Disability Status Scale and ambulation index with an objective means to assess the natural course of the disease and its response to therapy, the authors have developed multiprotocol MR image segmentation methods based on fuzzy connectedness to quantify both macrosopic features of the disease (lesions, gray matter, white matter, cerebrospinal fluid, and brain parenchyma) and the microscopic appearance of diseased white matter. Over 1,000 studies have been processed to date. Results. By far the strongest correlations with the clinical measures were demonstrated by the magnetization transfer ratio histogram parameters obtained for the various segmented tissue regions. These findings emphasize the importance of considering the microscopic and diffuse nature of the disease in the individual tissue regions. Brain parenchymal volume also demonstrated a strong correlation with clinical measures, which suggests that brain atrophy is an important disease indicator. Conclusion. Fuzzy connectedness is a viable, highly reproducible segmentation method for studying MS.
   
   @ARTICLE{Udupa:2001:MMI,
   AUTHOR = {Jayaram K. Udupa and Laszlo G. Nyul and Yulin Ge and Robert I. Grossman},
   JOURNAL = {Academic Radiology},
   TITLE = {Multiprotocol MR Image Segmentation in Multiple Sclerosis: Experience With Over 1000 Studies},
   YEAR = {2001},
   MONTH = {November},
   NUMBER = {11},
   PAGES = {1116--1126},
   VOLUME = {8},
   }

Conference articles

1. Gabor Fichtinger, Ken Masamune, Alexandru Patriciu, Attila Tanacs, James H. Anderson, Theodore L. DeWeese, Russel H. Taylor, and Dan Stoianovici. Robotically Assisted Percutaneous Local Therapy and Biopsy. In Proceedings of the IEEE International Conference on Advanced Robotics, Budapest, Hungary, pages 133-151, August 2001. IEEE. [PDF]
   Abstract: We present the concept and prototype of an image-guided robotic system for accurate and consistent placement of percutaneous needles in soft tissue targets under CT-guidance. The system is a promising embodiment of the Surgical CAD/CAM paradigm and as such, easily adaptable to other image guidance modalities, like X-ray fluoroscopy. We also report the first results of pre-clinical experiments on phantoms.
   
   @INPROCEEDINGS{Fichtinger:2001:ICAR,
   AUTHOR = {Gabor Fichtinger and Ken Masamune and Alexandru Patriciu and Attila Tanacs and James H. Anderson and Theodore L. DeWeese and Russel H. Taylor and Dan Stoianovici},
   BOOKTITLE = {Proceedings of the IEEE International Conference on Advanced Robotics},
   TITLE = {Robotically Assisted Percutaneous Local Therapy and Biopsy},
   YEAR = {2001},
   ADDRESS = {Budapest, Hungary},
   MONTH = {August},
   PAGES = {133--151},
   PUBLISHER = {IEEE},
   }


2. Gabor Fichtinger, Sheng Xu, Attila Tanacs, Kieran Murphy, Lee Myers, and Jeffery Williams. Approximate Volumetric Reconstruction from Projected Images. In Wiro J. Niessen and Max A. Viergever, editors, Proceedings of the International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), volume 2208 of Lecture Notes in Computer Science, Utrecht, The Netherlands, pages 1376-1378, October 2001. Springer Verlag. [PDF]
   Abstract: A significant problem in planning of volumetrically prescribed localized treatments is the mathematical impossibility to determine the exact three dimensional shape and volume of a target object from its projected images. Reconstruction accuracy also varies with viewing angle, depending on the convexity and aspect ratios of the target object. In response to this problem, we are developing a robust and efficient technique for approximate volumetric reconstruction, which (A) uses no prior information of the shape and volume of the target, (B) does not require exact silhouettes, (C) accepts arbitrary number of images, (D) produces solid object and measure of its volume, (E) provides confidence measure of the reconstruction and drawing of silhouettes, (F) is robust, fast and easy to implement. Preliminary tests suggest that fairly convex objects can be reconstructed from four views, and typically six views with table rotation allow us to reconstruct fine details as small as 1 mm. The method is applicable for any X-ray guided volumetric treatment. Pilot applications will be planning of radiosurgery of arterioveneous malformations (AVMs) and radiofrequency ablation of soft tissue lesions.
   
   @INPROCEEDINGS{Fichtinger:2001:MICCAI,
   AUTHOR = {Gabor Fichtinger and Sheng Xu and Attila Tanacs and Kieran Murphy and Lee Myers and Jeffery Williams},
   BOOKTITLE = {Proceedings of the International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI)},
   TITLE = {Approximate Volumetric Reconstruction from Projected Images},
   YEAR = {2001},
   ADDRESS = {Utrecht, The Netherlands},
   EDITOR = {Wiro J. Niessen and Max A. Viergever},
   MONTH = {October},
   PAGES = {1376--1378},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {2208},
   }


3. Zoltan Kato and Ting Chuen Pong. A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features. In Wladyslaw Skarbek, editor, Proceedings of the International Conference on Computer Analysis of Images and Patterns, volume 2124 of Lecture Notes in Computer Science, Warsaw, Poland, pages 547-554, September 2001. Springer Verlag. [PDF] Keyword(s): image segmentation, Markov random field model.
   Abstract: In this paper, 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 associated with 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 white noise model is suitable to describe the feature values belonging to a given class. Herein, we use the perceptually uniform CIE-L*u*v* color values as color features and a set of Gabor filters as texture features. We provide experimental results that illustrate the performance of our method on both synthetic and natural color images. Due to the local nature of our MRF model, the algorithm can be highly parallelized.
   
   @INPROCEEDINGS{Kato-Pong2001,
   AUTHOR = {Zoltan Kato and Ting Chuen Pong},
   BOOKTITLE = {Proceedings of the International Conference on Computer Analysis of Images and Patterns},
   TITLE = {A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features},
   YEAR = {2001},
   ADDRESS = {Warsaw, Poland},
   EDITOR = {Wladyslaw Skarbek},
   MONTH = {September},
   PAGES = {547--554},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {2124},
   KEYWORDS = {image segmentation, Markov random field model},
   }


4. Attila Kuba and Antal Nagy. Reconstruction of hv-convex Binary Matrices from Their Absorbed Projections. In Proceedings of the International Workshop on Combinatorial Image Analysis, volume 46 of Electronic Notes in Theoretical Computer Science, Philadephia, Pennsylvani, USA, pages 371-380, August 2001. [PDF] [doi:10.1016/S1571-0661(04)80998-8]
   Abstract: The reconstruction of hv-convex binary matrices from their absorbed projections is considered. Although this problem is NP-complete if the non-absorbed row and column sums are available, it is proved that such a reconstruction problem can be solved in polynomial time from absorbed projections when the absorption is represented by B = (1 + sqrt(5))/2. Also a reconstruction algorithm is given to determine the whole structure of hv-convex binary matrices from such projections.
   
   @INPROCEEDINGS{Kuba2001,
   AUTHOR = {Attila Kuba and Antal Nagy},
   BOOKTITLE = {Proceedings of the International Workshop on Combinatorial Image Analysis},
   TITLE = {Reconstruction of hv-convex Binary Matrices from Their Absorbed Projections},
   YEAR = {2001},
   ADDRESS = {Philadephia, Pennsylvani, USA},
   MONTH = {August},
   PAGES = {371-380},
   SERIES = {Electronic Notes in Theoretical Computer Science},
   VOLUME = {46},
   DOI = {10.1016/S1571-0661(04)80998-8},
   }


5. Laszlo G. Nyul, Jayaram K. Udupa, and Punam K. Saha. Task-specific Comparison of 3-D Image Registration methods. In M. Sonka and K. M. Hanson, editors, Proceedings of Medical Imaging 2001: Image Processing, volume 4322 of SPIE Proceedings, San Diego, USA, pages 1588-1598, July 2001. [doi:10.1117/12.431044]
   Abstract: We present a new class of approaches for rigid-body registration and their evaluation in studying Multiple Sclerosis via multi protocol MRI. Two pairs of rigid-body registration algorithms were implemented, using cross- correlation and mutual information, operating on original gray-level images and on the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local scale value assigned to it, defined as the radius of the largest sphere centered at the voxel with homogeneous intensities. 3D data of the head were acquired from 10 MS patients using 6 MRI protocols. Images in some of the protocols have been acquired in registration. The co-registered pairs were used as ground truth. Accuracy and consistency of the 4 registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no best method. For medium and large misregistration, methods using mutual information, for small misregistration, and for the consistency tests, correlation methods using the original gray-level images give the best results. We have previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have considerable potential for image registration as suggested by this work.
   
   @INPROCEEDINGS{Nyul:2001:TC3,
   AUTHOR = {Laszlo G. Nyul and Jayaram K. Udupa and Punam K. Saha},
   BOOKTITLE = {Proceedings of Medical Imaging 2001: Image Processing},
   TITLE = {Task-specific Comparison of 3-D Image Registration methods},
   YEAR = {2001},
   ADDRESS = {San Diego, USA},
   EDITOR = {M. Sonka and K. M. Hanson},
   MONTH = {July},
   PAGES = {1588--1598},
   SERIES = {SPIE Proceedings},
   VOLUME = {4322},
   DOI = {10.1117/12.431044},
   }


6. Kalman Palagyi, Erich Sorantin, Emese Balogh, Attila Kuba, Csongor Halmai, Balazs Erdohelyi, and Klaus Hausegger. A sequential 3D thinning algorithm and its medical applications. In Michael F. Insana and Richard M. Leahy, editors, Proceedings of the International Conference on Information Processing in Medical Imaging (IPMI), volume 2082 of Lecture Notes in Computer Science, Davis, CA, USA, pages 409-415, June 2001. Springer Verlag. [PDF]
   Abstract: Skeleton is a frequently applied shape feature to represent the general form of an object. Thinning is an iterative object reduction technique for producing a reasonable approximation to the skeleton in a topology preserving way. This paper describes a sequential 3D thinning algorithm for extracting medial lines of objects in (26,6) pictures. Our algorithm has been successfully applied in medical image analysis. Three of the emerged applications (analysing airways, blood vessels, and colons) are also presented.
   
   @INPROCEEDINGS{PalagyiEtalIPMI2001,
   AUTHOR = {Kalman Palagyi and Erich Sorantin and Emese Balogh and Attila Kuba and Csongor Halmai and Balazs Erdohelyi and Klaus Hausegger},
   BOOKTITLE = {Proceedings of the International Conference on Information Processing in Medical Imaging (IPMI)},
   TITLE = {A sequential 3D thinning algorithm and its medical applications},
   YEAR = {2001},
   ADDRESS = {Davis, CA, USA},
   EDITOR = {Michael F. Insana and Richard M. Leahy},
   MONTH = {June},
   PAGES = {409-415},
   PUBLISHER = {Springer Verlag},
   SERIES = {Lecture Notes in Computer Science},
   VOLUME = {2082},
   }

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