PUBLICATIONS

 

Journal Articles  (in reverse chronological order)

 

1.      J. Lakoumentas, J. Drakos, M. Karakantza, G. Sakellaropoulos, V. Megalooikonomou, G. Nikiforidis, “Optimizations of the naïve-Bayes classifier for the prognosis of B-Chronic Lymphocytic Leukemia incorporating flow cytometry data”,  Computer Methods and Programs in Biomedicine (accepted).

 

2.      L. An, H. Ling, Z. Obradovic, D.J. Smith, and V. Megalooikonomou, “Learning pair-wise gene functional similarity by multiplex gene expression maps”, BMC Bioinformatics, 13(Suppl 3):S1, 2012 (in press).

 

3.      M. Barnathan, V. Megalooikonomou, C. Faloutsos, S. Faro, F.B. Mohamed, “TWave: High-Order Analysis of Functional MRI”, NeuroImage, 58(2): pp. 537-548, 2011.

 

4.      A. Charisi, P. Korvesis, V. Megalooikonomou, “Similarity searching of medical image data in distributed systems – Facilitating telemedicine applications”, International Journal of Computational Models and Algorithms in Medicine, 2(1): pp. 60-79, 2011.

 

5.      Q. Wang, V. Megalooikonomou, C. Faloutsos, “Time Series Analysis with Multiple Resolutions”, Information Systems, Vol. 35, No. 1, pp. 56-74, 2010.

 

6.      Q. Wang, V. Megalooikonomou, “A Performance Evaluation Framework for Association Mining in Spatial Data”, Journal of Intelligent Information Systems, Vol. 35, No. 3, pp. 465-494, 2010.

 

7.      L. An, H. Xie, M.H. Chin, Z. Obradovic, D.J. Smith and V. Megalooikonomou, “Analysis of multiplex gene expression maps obtained by voxelation”, BMC Bioinformatics, Vol. 10 (Suppl 4): S10, pp. 1-15, 2009.

 

8.      D. Kontos, V. Megalooikonomou, J. Gee, “Morphometric analysis of brain images with reduced number of statistical tests: a study on the gender-related differentiation of the corpus callosum”, Artificial Intelligence in Medicine, Vol. 47, No. 1, pp. 75-86, 2009.

 

9.      V. Megalooikonomou, M. Barnathan, D. Kontos, P. R. Bakic, A. D.A. Maidment, “A Representation and Classification Scheme for Tree-like Structures in Medical Images: Analyzing the Branching Pattern of Ductal Trees in X-ray Galactograms”, IEEE Transactions on Medical Imaging, Vol. 28, Issue 4, pp. 487-493, 2009.

 

10.  Q. Wang and V. Megalooikonomou, “A Dimensionality Reduction Technique for Efficient Time Series Similarity Analysis”, Information Systems, 33, pp. 115-132, 2008.

 

11.  V. Megalooikonomou, D. Kontos, D. Pokrajac, A. Lazarevic and Z. Obradovic, “An adaptive partitioning approach for mining discriminant regions in 3D image data”, Journal of Intelligent Information Systems, Vol. 31, No. 3, pp. 217-242, 2008.

 

12.  V. Megalooikonomou, D. Kontos, “Medical Data Fusion for Telemedicine: A model for distributed analysis of medical image data across clinical information repositories”, IEEE Engineering in Medicine and Biology Magazine, Vol. 26, No. 5, pp. 36-42, 2007.

 

13.  D. Kontos, V. Megalooikonomou, M. Sobel, “A Statistical Approach for Selecting Discriminative Features of Spatial Regions of Interest”, Intelligent Data Analysis, Vol. 11, No. 2, pp. 111-135, 2007.

 

14.  L. Latecki, V. Megalooikonomou, Q. Wang, D. Yu, “An Elastic Partial Shape Matching Technique”, Pattern Recognition, Vol. 40, No. 11, pp. 3069-3080, 2007.

 

15.  C. Faloutsos and V. Megalooikonomou, “On Data Mining, Compression, and Kolmogorov Complexity”, Data Mining and Knowledge Discovery, Tenth Anniversary Issue, Vol. 15, No. 1, pp. 3-20(18), 2007.

 

16.  D. Kontos, Q. Wang, V. Megalooikonomou, A. H. Maurer, L. C. Knight, S. Kantor, R. S. Fisher, H. P. Simonian, H. P. Parkman, “A Tool for Handling Uncertainty in Segmenting Regions of Interest in Medical Images”, International Journal of Intelligent Systems Technologies, Special Issue on Intelligent Image and Video Processing and Applications: The Role of Uncertainty, Vol. 1, Nos. 3/4, pp. 194-210, 2006.

 

17.  L. J. Latecki, V. Megalooikonomou, R. Miezianko, D. Pokrajac, “Using Spatiotemporal Blocks to Reduce the Uncertainty in Detecting and Tracking Moving Objects in Video”, International Journal of Intelligent Systems Technologies Special Issue on Intelligent Image and Video Processing and Applications: The Role of Uncertainty, Vol. 1, Nos. 3/4, pp. 376-392, 2006.

 

18.  D. Kontos and V. Megalooikonomou, “Fast and effective characterization for classification and similarity searches of 2D and 3D spatial region data”, Pattern Recognition, Vol. 38, No. 11, pp. 1831-1846, 2005.

 

19.  D. Pokrajac, V. Megalooikonomou, A. Lazarevic, D. Kontos, Z. Obradovic, “Applying Spatial Distribution Analysis Techniques to Classification of 3D Medical Images”, Artificial Intelligence in Medicine, Vol. 33, No. 3, pp. 261-280, Mar. 2005.

 

20.  K. Kumaraswamy, V. Megalooikonomou and C. Faloutsos, “Fractal Dimension and Vector Quantization”, Information Processing Letters, Vol. 91, No. 3, pp. 107-113, 2004.

 

21.  V. Megalooikonomou and Y. Yesha, “Space Efficient Quantization for Decentralized Estimation by a Multi-sensor Fusion System”, Information Fusion, Vol. 5, No. 4, pp. 299-308, 2004.

 

22.  H. P. Simonian, A. H. Maurer, L. C. Knight, S. Kantor, D. Kontos, V. Megalooikonomou, R. S. Fisher, H. P. Parkman, “Simultaneous Assessment of Gastric Accommodation and Emptying: Studies with Liquid and Solid Meals”, Journal of Nuclear Medicine, Vol. 45, No. 7, pp. 1155-1160, 2004.

 

23.  V. Megalooikonomou and Y. Yesha, “Quantization for Distributed Estimation using Neural Networks”, Information Sciences, Vol. 148, No. 1-4, pp. 185-199, 2002.

 

24.  V. Megalooikonomou and Y. Yesha, “Quantizer Design for Distributed Estimation with Communication Constraints and Unknown Observation Statistics”, IEEE Transactions on Communications, Vol. 48, No. 2, pp. 181-184, 2000.

 

25.  V. Megalooikonomou, J. Ford, L. Shen, F. Makedon and A. Saykin, “Data mining in brain imaging”, Statistical Methods in Medical Research, Vol. 9, No. 4, pp. 359-394, 2000.

 

26.  V. Megalooikonomou, C. Davatzikos, and E. H. Herskovits, “A Simulator for Evaluation of Methods for the Detection of Lesion-Deficit Associations”, Human Brain Mapping, Vol. 10, No. 2, pp. 61-73, 2000.

 

27.  E. H. Herskovits, V. Megalooikonomou, C. Davatzikos, A. Chen, R. N. Bryan, J. Gerring, “Is the spatial distribution of brain lesions associated with closed-head injury predictive of subsequent development of attention-deficit hyperactivity disorder? Analysis with brain image database”, Radiology, Vol. 213, No. 2, pp. 389-394, 1999.

 

 

Refereed Publications in Conference  Proceedings (in reverse chronological order)

1.      F. Malliaros, V. Megalooikonomou, C. Faloutsos, “Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection”, Proceedings of the SIAM International Conference on Data Mining, Anaheim, CA, 2012 (to appear).

 

2.      A. Skoura, T. Nuzhnaya, V. Megalooikonomou, “Integration of edge detection and fuzzy connectivity for segmentation of tree-like structures in medical images”, International Conference on Computational Biomedicine, Florida, U.S.A., 2012 (to appear).

 

3.      P. Jiang, J. Peng, G. Zhang, E. Cheng, V. Megalooikonomou, H. Ling, “Learning-based automatic breast tumor detection and segmentation in ultrasound images”, 9th IEEE International Symposium on Biomedical Imaging (ISBI), Barcelona, Spain, 2012 (to appear).

 

4.      T. Nuzhnaya, P.R. Bakic, D. Kontos, V. Megalooikonomou, H. Ling. “Segmentation of anatomical branching structures based on texture features and conditional random field”, in Proc. SPIE Medical Imaging, 8314-54, 2012 (to appear).

 

5.      Y. Wu, F. Xie, J. Yang, E. Cheng, V. Megalooikonomou, and H. Ling.  “Automatic detection of apical roots in oral radiographs”, in Proc. SPIE Medical Imaging, 8315-93, 2012 (to appear).

 

6.      Y. Wu, F. Xie, J. Yang, E. Cheng, V. Megalooikonomou, and H. Ling. “Computer aided periapical lesion diagnosis using quantized texture analysis”, in Proc. SPIE Medical Imaging, 8315-43, 2012 (to appear).

 

7.      F. Malliaros, V. Megalooikonomou, “Expansion Properties of Large Social Graphs”, 2nd Int'l Workshop on Social Networks and Social Media Mining on the Web, in conjunction with the 16th international conference on Database Systems for Advanced Applications (DASFAA), Hong Kong, April 22-25, 2011, Lecture Notes in Computer Science, 2011, Volume 6637/2011, pp. 311-322.

 

8.      E. Cheng, S. W. Mclaughlin, H. Ling, V. Megalooikonomou, P.R. Bakic, A.D.A. Maidment, “Learning-based vessel segmentation in mammographic images”, 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB), July 27-29, San Jose, California, 2011.

 

9.      L. An, H. Ling, Z. Obradovic, D.J. Smith, V. Megalooikonomou, “Identifying pair-wise gene functional similarity by multiplex gene expression maps and supervised learning”, ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB), Chicago, Illinois, August 1-3, 2011.

 

10.  E. Cheng, J. Chen, B. Gable, Y. Wu, H. Deng, V. Megalooikonomou, J. Yang, and H. Ling. "Automatic Dent-landmark Detection in 3-D CBCT Dental Volumes, Proceedings of Int'l Conf. of the IEEE Engineering in Medicine and Biology Society (EMBC), Boston, 2011.

 

11.  T. Nuzhnaya, E. Cheng, H. Ling, D. Kontos, P.R. Bakic, V. Megalooikonomou, “Segmentation of Anatomical branching Structures based on Texture Features and Graph Cut”, 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Chicago, Illinois, 2011, pp. 673-676.

 

12.  A. Skoura, V. Megalooikonomou, P.R. Bakic, A.D.A. Maidment, “Classifying Ductal Tree Structures Using Topological Descriptors of Branching”, 12th Engineering Applications of Neural Networks (EANN) / 7th Artificial Intelligence Applications and Innovations (AIAI) Joint Conferences, 15 - 18 September 2011, Corfu, Greece, Vol. 364, IFIP Advances in Information and Communication Technology, 2011.

 

13.  T. Nuzhnaya, V. Megalooikonomou, H. Ling, M. Kohn, R. Steiner, “Classification of Texture Patterns in CT Lung Imaging”, Proceedings of SPIE Medical Imaging, Volume: 7963 (Computer Aided Diagnoses), Orlando 2011.

 

14.  E. Cheng, H. Ling, P.R. Bakic, A.D.A. Maidment, V. Megalooikonomou, “Automatic Detection of Regions of Interest in Mammographic Images”, Proceedings of the SPIE Medical Imaging, Orlando 2011.

 

15.  M. Barnathan, V. Megalooikonomou, C. Faloutsos, F.B. Mohamed, S. Faro, “TWave: High-Order Analysis of Spatiotemporal Data”, In Proceedings of the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Hyderabad, India, June, 21-24, 2010, Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, 2010, Volume 6118/2010, pp. 246-253.

 

16.  A. Charisi, V. Megalooikonomou, “Similarity Searches of Medical Image Data in Peer-to-Peer Systems”, 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010), Corfu, Greece, Nov. 2010.

 

17.  M. Barnathan, V. Megalooikonomou, C. Faloutsos, F. Mohamed, S. Faro, “High-order Concept Discovery in Functional Brain Images”, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Rotterdam, The Netherlands, 2010, pp. 664-667.

 

18.  A. Charisi, V. Megalooikonomou, “Content-Based Medical Image Retrieval in Peer-to-Peer Systems”, 1st ACM International Health Informatics Symposium, Arlington, Virginia, Nov. 2010, pp. 724-733.

 

19.  Q. Wang, A. Charisi, L. J. Latecki, J. Gee, V. Megalooikonomou, “Shape Similarity Analysis of Regions of Interest in Medical Images”, Proceedings of the SPIE Medical Imaging 2010: Computer-Aided Diagnosis, San Diego, CA, 2010, Volume 7624, pp. 762428-762428-8.

 

20.  E. Cheng, N, Xie, H. Ling, V. Megalooikonomou, “Mammographic Image Classification using Histogram Intersection”, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Rotterdam, The Netherlands, 2010, pp. 197-200.

 

21.  L. An, H. Xie, Z. Obradovic, D.J. Smith, V. Megalooikonomou, “Identifying Gene Functions using Functional Expression Profiles obtained by Voxelation”, ACM International Conference On Bioinformatics and Computational Biology, Niagara Falls, NY, 2010.

 

22.  T. Nuzhnaya, M. Barnathan, H. Ling, V. Megalooikonomou, P. Bakic, A. Maidment, “Probabilistic Branching Node Detection Using Adaboost and Hybrid Local Features”, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Rotterdam, The Netherlands, 2010, pp. 221-224.

 

23.  E. Miranda, G. Shan, and V. Megalooikonomou, “Performing Vector Quantization Using Reduced Data Representation”, Proceedings of the Data Compression Conference (DCC), Salt Lake City, Utah, 2009.

 

24.  A. Skoura, M. Barnathan, V. Megalooikonomou, “Spatial Feature Extraction Techniques For the Analysis of Ductal Tree Structures”, Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Minneapolis, USA, 2009, pp. 6620-6623.

 

25.  L. An, Z. Obradovic, D. Smith, O. Bodenreider and V. Megalooikonomou, “Mining Association Rules among Gene Functions in Clusters of Similar Gene Expression Maps”, Proceedings of the Workshop on Data Mining in Functional Genomics, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington D.C., Nov. 2009, pp. 254-259.

 

26.  Α. Skoura, M. Barnathan, V. Megalooikonomou, “Classification of Ductal Tree Structures in Galactograms”, Proceedings of the 6th IEEE International Symposium on Biomedical Imaging (ISBI), Boston, MA, 2009, pp. 1015-1018.

 

27.  H. Ling, M. Barnathan, V. Megalooikonomou, P. Bakic, A. Maidment, “Probabilistic Branching Node Detection Using Hybrid Local Features”, Proceedings of the 6th IEEE International Symposium on Biomedical Imaging (ISBI), Boston, MA, 2009, pp. 233-236.

 

28.  L. An, H. Xie, M. Chin, Z. Obradovic, D. Smith, V. Megalooikonomou, “Analysis of Multiplex Gene Expression Maps Obtained By Voxelation”, Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philadelphia, USA, 2008, pp. 23-28.

 

29.  M. Barnathan, J. Zhang, V. Megalooikonomou, “A Web-Accessible Framework for the Automated Storage and Texture Analysis of Biomedical Images”, Proceedings of the 5th IEEE International Symposium on Biomedical Imaging (ISBI), Paris, France, 2008, pp. 257-259.

 

30.  M. Barnathan, J. Zhang, E. Miranda, V. Megalooikonomou, S. Faro, H. Hensley, L. D. Valle, K. Khalili, J. Gordon, F. B. Mohamed, “A Texture-Based Methodology For Identifying Tissue Type in Magnetic Resonance Images”, Proceedings of the 5th IEEE International Symposium on Biomedical Imaging (ISBI), Paris, France, 2008, pp. 464-467.

 

31.  M. Barnathan, R. Li, V. Megalooikonomou, F. Mohamed, S. Faro, “Wavelet Analysis of 4D Motor Task fMRI Data”, Proceedings of Computer Assisted Radiology and Surgery (CARS), Barcelona, Spain, 2008.

 

32.  M. Barnathan, J. Zhang, D. Kontos, P. Bakic, A. Maidment, V. Megalooikonomou, “Analyzing Tree-Like Structures In Biomedical Images Based On Texture And Branching: An Application To Breast Imaging”, Proceedings of the International Workshop on Digital Mammography (IWDM), Tucson, AZ, 2008.

 

33.  L. J. Latecki, Q. Wang, S. Koknar-Tezel, V. Megalooikonomou, “Optimal Subsequence Bijection”, Proceedings of the IEEE International Conference on Data Mining (ICDM), Omaha, NE, 2007, pp. 565-570.

 

34.  J. Zhang and V. Megalooikonomou, “An effective and efficient technique for searching for similar brain activation patterns”, Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), 2007, pp. 428-431.

 

35.  L. J. Latecki, S. Koknar-Tezel, Q. Wang, and V. Megalooikonomou, “Sequence Matching Capable of Excluding Outliers”,  In Proceedings of Workshop on Time Series Classification at ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD), 2007.

 

36.  Q. Wang, E. Karamani-Liacouras, E. Miranda, U.S. Kanamala, V. Megalooikonomou, “Classification of brain tumors in MR images”, Progress in Biomedical Optics and Imaging, Proceedings of the SPIE Conference on Medical Imaging, 6514, (part 1), 2007.

 

37.  V. Megalooikonomou, J. Zhang, D. Kontos, P.R. Bakic, “Analysis of texture patterns in medical images with an application to breast imaging”, Progress in Biomedical Optics and Imaging, Proceedings of the SPIE Conference on Medical Imaging, 6514, (part 2), 2007.

 

38.  D. Kontos, V. Megalooikonomou, A. Javadi, P. Bakic, A. Maidment, “Classification of Galactograms Using Fractal Properties of the Breast Ductal Network”, Proceedings of the IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Arlington, Virginia, April 6-9, pp. 1324-1327, 2006.

 

39.  P. Bakic, D. Kontos, V. Megalooikonomou, A. Maidment, “Comparison of Methods for Classification of Breast Ductal Branching Patterns”, Proceedings of the 8th International Workshop on Digital Mammography (IWDM), Manchester, England, June 18-21, 2006, Lecture Notes in Computer Science, Vol. 4046, pp. 634-641, 2006.

 

40.  V. Megalooikonomou, D. Kontos, J. Danglemaier, A. Javadi,  P. A. Bakic, A.D.A. Maidment, “A representation and classification scheme for tree-like structures in medical images: An application on branching pattern analysis of ductal trees in x-ray galactograms”, Proceedings of the SPIE Conference on Medical Imaging, Vol. 6144, 61441H, San Diego, California, Feb. 2006.

 

41.  L. J. Latecki, V. Megalooikonomou, Q. Wang, R. Lakaemper, C. A. Ratanamahatana, E. Keogh, “Elastic Partial Matching of Time Series”, Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'05), Porto, Portugal, Lecture Notes in Computer Science, Vol. 3721, pp. 577-584, 2005.

 

42.  V. Megalooikonomou, Q. Wang, G. Li, C. Faloutsos, “A Multiresolution Symbolic Representation of Time Series”, in Proceedings of the 21st International Conference on Data Engineering (ICDE), Tokyo, Japan, pp. 668-679, 2005.

 

43.  V. Megalooikonomou, D. Kontos, N. DeClaris and P. Cano, “Utilizing Domain Knowledge in Neural Network Models for Peptide-Allele Binding Prediction”, Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB'05), San Diego, California, Nov. 2005.

 

44.  L. J. Latecki, V. Megalooikonomou, Q. Wang, R. Lakaemper, C. A. Ratanamahatana, and E. Keogh, “Partial Elastic Matching of Time Series”, Proceedings of the Fifth IEEE International Conference on Data Mining (ICDM'05), Houston, Texas, pp. 701-704, Nov. 2005.

 

45.  V. Megalooikonomou, D. Kontos, “Integrating clinical information repositories: A framework for distributed analysis of medical image data”, Proceedings of the 5th International Network Conference (INC 2005), Special Session on Image, Signal and Distributed Data Processing for Networked eHealth Applications, Samos Island, Greece, pp. 545-552, July 5-7, 2005.

 

46.  Q. Wang, V. Megalooikonomou, D. Kontos, “A Medical Image Retrieval Framework”, Proceedings of the 2005 IEEE International Workshop on Machine Learning for Signal Processing (MLSP05), Mystic, Connecticut, pp. 233-238, Sept. 28-30, 2005.

 

47.  Q. Wang, V. Megalooikonomou, “A clustering algorithm for intrusion detection”, Proceedings of the SPIE Conference on Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security, Orlando, Florida, USA, March 28 - April 1, Vol. 5812, pp. 31-38, 2005.

 

48.  D. Kontos, V. Megalooikonomou and J. Gee, “Reducing the computational cost for statistical medical image analysis: An MRI study on the sexual morphological differentiation of the corpus callosum”, Proceedings of the 18th IEEE International Symposium on Computer-Based Medical Systems (CBMS05), Trinity College, Dublin, Ireland, pp. 282-287, June 23-24, 2005.

 

49.  Q. Wang, V. Megalooikonomou, G. Li, “A Symbolic Representation of Time Series”, Proceedings of the 8th IEEE International Symposium on Signal Processing and its Applications (ISSPA05), Sydney, Australia, pp. 28-31, Aug. 28-31, 2005.

 

50.  D. Kontos, Q. Wang, V. Megalooikonomou, A. H. Maurer, L. C. Knight, S. Kantor, R. S. Fisher, H. P. Simonian, H. P. Parkman, “A 3D Image Analysis Tool for SPECT Imaging”, Proceedings of the SPIE Conference on Medical Imaging, San Diego, CA, pp. 839-847, Feb. 12-17, 2005.

 

51.  V. Megalooikonomou, G. Li, Q. Wang, “A Dimensionality Reduction Technique for Efficient Similarity Analysis of Time Series Databases”, Proceedings of the 13th Conference on Information and Knowledge Management (CIKM) 2004, Washington, DC, pp. 160-161, 2004.

 

52.  D. Kontos, V. Megalooikonomou, D. Pokrajac, A. Lazarevic, Z. Obradovic, O. B. Boyko, J. Ford, F. Makedon, A. J. Saykin, “Extraction of Discriminative Functional MRI Activation Patterns and an Application to Alzheimer's Disease”, 7th Annual International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'04), Rennes-Saint Malo, Sept. 26-30, Proceedings, Part II, Lecture Notes in Computer Science 3217, Vol. 2, pp. 727-735, 2004.

 

53.  R. Lakamper, L. J. Latecki, V. Megalooikonomou, Q. Wang, X. Wang, “Learning Descriptive and Distinctive Parts of Objects with a Part-Based Shape Similarity Measure”, Proceedings of the IASTED 6th International Conference on Signal and Image Processing (SIP'04), Honolulu, Hawaii, Aug. 2004.

 

54.  Q. Wang, D. Kontos, G. Li and V. Megalooikonomou, “Application of Time Series Techniques to Data Mining and Analysis of Spatial Patterns in 3D images”, in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, (ICASSP'04), pp. 525-528, May 2004.

 

55.  K. Kumaraswamy, C. Faloutsos, G. Shan and V. Megalooikonomou, “Relation between Fractal Dimension and Performance of Vector Quantization”, in Proceedings of the Data Compression Conference (DCC'04), Salt Lake City, UT, pp. 547, Mar. 2004.

 

56.  D. Kontos, V. Megalooikonomou, M. Sobel, Q. Wang, “An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data”, Joint International Workshops on  Syntactic and Structural Pattern Recognition (SSPR) and Statistical Pattern Recognition (SPR), Lisbon, Portugal, Proceedings, Lecture Notes in Computer Science 3138, pp. 379-387, 2004.

 

57.  D. Kontos and V. Megalooikonomou, “Fast and Effective Characterization of 3D Region of Interest in Medical Image Data”, in Proceedings of the SPIE International Symposium on Medical Imaging 2004, San Diego, CA, Feb. 2004, Volume 5370 Medical Imaging, pp. 1324-1331, 2004.

 

58.  D. Kontos, V. Megalooikonomou, F. Makedon, “Computationally Intelligent Methods for Mining 3D Medical Images” ,in Lecture Notes in Artificial Intelligence, 3025, 3rd Hellenic Conference on Artificial Intelligence, Samos Island, Greece, pp. 72-81, May 2004.

 

59.  D. Kontos, V. Megalooikonomou, N. Ghubade, C. Faloutsos, “Detecting discriminative functional MRI activation patterns using space filling curves”, in Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Cancun, Mexico, pp. 963-967, Sept. 2003.

 

60.  J. Ford, H. Farid, F. Makedon, L.A. Flashman, T.W. McAllister, V. Megalooikonomou and A.J. Saykin, “Patient Classification of fMRI Activation Maps”, 6th Annual International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'03), Montreal, Canada, Proceedings, Part II, Lecture Notes in Computer Science 2879, pp. 58-65, Nov. 2003.

 

61.  K. Kumaraswamy, V. Megalooikonomou, “Fractal Dimension and Vector Quantization”, in Proceedings of the Workshop on Fractals and Self Similarity in Data Mining, 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'03), Washington, DC, USA, pp. 24-27, Aug. 24-27, 2003.

 

62.  V. Megalooikonomou, H. Dutta, D. Kontos, “Fast and Effective Characterization of 3D Region Data”, in Proceedings of the IEEE International Conference on Image Processing (ICIP), Rochester, NY, pp. 421-424, Sept. 2002.

 

63.  V. Megalooikonomou, “Evaluating the performance of association mining methods in 3-D medical image databases”, in Proceedings of the 2nd SIAM International Conference on Data Mining (SDM), Arlington, VA, pp. 474-494, Apr. 2002.

 

64.  V. Megalooikonomou, D. Pokrajac, A. Lazarevic and Z. Obradovic, “Effective classification of 3-D image data using partitioning methods”, in Proceedings of the Conference on Visualization and Data Analysis, SanJose, CA, pp. 62-73, Jan. 2002.

 

65.  Lazarevic, D. Pokrajac, V. Megalooikonomou and Z. Obradovic, “Distinguishing Among 3-D Distributions for Brain Image Data Classification”, Proceedings of the 4th International Conference on Neural Networks and Expert Systems in Medicine and Healthcare, Milos Island, Greece, pp. 389-396, June 2001.

 

66.  L. Shen, L. Cheng, J. Ford, F. Makedon, V. Megalooikonomou, T. Steinberg, “Mining the Most Interesting Web Access Associations”, in Proceedings of the World Conference on the WWW and Internet (WebNet), San Antonio, Texas, pp. 489-494, Nov. 2000.

 

67.  V. Megalooikonomou, C. Davatzikos, and E. H. Herskovits, “Mining Lesion-Deficit Associations in a Brain Image Database”, in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), San Diego, CA, pp. 347-351, 1999.

 

68.  V. Megalooikonomou and Y. Yesha, “Design of Neural Network Quantizers for a Distributed Estimation System with Communication Constraints”, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Seattle, Washington, pp. 3469-3472, May 1998.

 

69.  V. Megalooikonomou and Y. Yesha, “Quantization for Distributed Estimation with Communication and Storage Constraints”, in Proceedings of the 35th Annual Allerton Conference on Communications, Control, and Computing, Urbana, Illinois, pp. 102-112, Sept. 1997.

 

70.  V. Megalooikonomou and Y. Yesha, “Quantization for Distributed Estimation with Unknown Observation Statistics”, Proceedings of the 31st Annual Conference on Information Sciences and Systems, Baltimore, Maryland, pp. 138-143, Mar. 1997.

 

Refereed Extended Abstracts in Journals and conference proceedings (in reverse chronological order)

1.      M. Yi, T. Nuzhnaya, V. Megalooikonomou, X. Wang, L. Latecki, M. Kohn, R. Steiner, “Lung CT Image Classification Using Locality-Constrained Linear Coding”, ΙΕΕΕ Nuclear Science Symposium and Medical Imaging Conference, Oct. 23-29, 2011, Valencia, Spain.

 

2.      T. Nuzhnaya, V. Megalooikonomou, H. Ling, M. Kohn, R. Steiner, "Classification and quantification of emphysema texture patterns in CT lung imaging", Proceedings of the 2011 International Functional Lung Imaging Workshop, Philadelphia, USA, Feb 28 - Mar 2, 2011.

 

3.      J. Lakoumentas, V. Megalooikonomou, G. Nikiforidis, “Optimizations of the naïve-Bayes classifier for the prognosis of B-Chronic Lymphocytic Leukemia”, International Conference on Biomedical Data & Knowledge Mining: Towards Biomarker Discovery", July 7-9, 2010, Chania, Crete.

 

4.      A. Skoura, V. Megalooikonomou, A. Diamantopoulos, G. Kagadis, “Classification of Normal and Ischemic Revascularized Arterial Networks in Angiographies based on Morphological Characteristics”, International Conference on Biomedical Data & Knowledge Mining: Towards Biomarker Discovery", July 7-9, 2010, Chania, Crete.  

      

5.      A. Skoura, M. Barnathan, V. Megalooikonomou, P.R. Bakic, A.D.A. Maidment, “Detection of breast cancer radiological findings by computing the asymmetry of the ductal tree structures in galactograms”, Proc. of IMPAKT Breast Cancer Conference, Brussels, Belgium, May 7-9, 2009, Annals of Oncology, Vol. 20 (Suppl. 2), ii35-ii36, 2009.

 

6.      A. Skoura, M. Barnathan, V. Megalooikonomou, P.R. Bakic, A.D.A. Maidment, “Comparison amongst descriptors of breast ductal tree which detect breast cancer radiological findings in galactograms”, Proc. of IMPAKT Breast Cancer Conference, Brussels, Belgium, May 7-9, 2009, Annals of Oncology, Vol. 20 (Suppl. 2), ii36, 2009.

 

7.      A. Skoura, M. Barnathan, V. Megalooikonomou, P.R. Bakic, A.D.A. Maidment, “Development of a novel descriptor of the breast ductal tree to detect breast cancer radiological findings in galactograms”, Proc. of IMPAKT Breast Cancer Conference, Brussels, Belgium, May 7-9, 2009, Annals of Oncology, Vol. 20 (Suppl. 2), ii36, 2009.

 

8.      G. Kagadis, A. Skoura, V. Megalooikonomou, A. Diamantopoulos, K. Katsanos, D. Karnabatidis, D. Mihailidis, G. Nikiforidis, “Morphological characterization of arterial trees in an experimental hindlimb ischemia model”, 51st Annual Meeting of the American Association of Physicists in Medicine (AAPM), California, USA, 2009, Medical Physics, 2009;36(6):2473 - 2474.

 

9.      M. Barnathan, V. Megalooikonomou, S. H. Faro, H. Hensley, L. Knight, L. Del Valle, K. Khalili, J. Gordon, F. B. Mohamed, “A Texture based Methodology for Quantification of CNS tumors in Spontaneous Transgenic Mouse Medulloblastoma Model”, World Molecular Imaging Congress, Nice, France, Sept. 10-13, 2008.

 

10.  D. Kontos, Q. Wang, E. Miranda, J. Zhang, V. Megalooikonomou “Data Mining Techniques Applied on Human Brain Image Data”, Society for Neuroscience Annual Satellite Meeting, Oct. 14-18, Atlanta, GA, 2006.

 

11.  Q. Wang, V. Megalooikonomou, D. Kontos, E. Miranda, V. Calhoun, “Similarity Searches in Brain Image Databases”, Human Brain Mapping Conference, Florence, Italy, June 11-15, 2006, Neuroimage, Vol. 31, Suppl. 1, pp. S173, 2006.

 

12.  Q. Wang, V. Megalooikonomou, E. Miranda, E. Karamani-Liacouras, U. S. Kanamalla, “Classification of Brain Tumors in MR Images”, Human Brain Mapping Conference (OHBM'06), Florence, Italy, June 11-15, 2006, Neuroimage, Vol. 31, Suppl. 1, pp. S172, 2006.

 

13.  D. Kontos, V. Megalooikonomou and J. Gee, “Effective Reduction of Statistical Tests for Morphological Analysis: Application to a Study of the Corpus Callosum”, Human Brain Mapping Conference, Toronto, Canada, June 12-16, 2005, Neuroimage, Vol. 26, Suppl. 1, pp. 35, 2005.

 

14.  V. Megalooikonomou, D. Kontos and A. Saykin, “Characterizing 3D Regions of Interest in fMRI Activation Maps”, Human Brain Mapping Conference, Toronto, Canada, June 12-16, 2005, Neuroimage, Vol. 26, Suppl. 1, pp. 38, 2005.

 

15.  V. Megalooikonomou, Q. Wang, D. Kontos, G. Li, J. Ford, A. Saykin, “Analysis of Brain Image Data using Sequence Analysis Techniques”, Human Brain Mapping Conference, Budapest, Hungary, June 13-17, 2004, Neuroimage, Vol. 22, Suppl. 1, pp. e1850, 2004.

 

16.  D. Kontos, V. Megalooikonomou, Q. Wang, J. Ford, F. Makedon, A. Saykin, “Identifying Discriminative fMRI Activation Signatures in Alzheimer's Disease: Studying a Series of Semantic Decision Tasks”, Human Brain Mapping Conference, Budapest, Hungary, June 13-17, 2004, Neuroimage, Vol. 22, Suppl. 1, pp. e2219-e2220, 2004.

 

17.  V. Megalooikonomou, D. Kontos, D. Pokrajac, A. Lazarevic, Z. Obradovic, O. Boyko, A. Saykin, J. Ford, F. Makedon, “Classification and Mining of Brain Image Data Using Adaptive Recursive Partitioning Methods: Application to Alzheimer Disease and Brain Activation Patterns”, Human Brain Mapping Conference, New York, NY, June 18-22, 2003, Neuroimage, Vol. 19, No. 2, Suppl. 1, pp. e1958-e1959, 2003.

 

18.  H.P. Simonian, S.B. Kantor, L.C. Knight, A.H. Maurer, V. Megalooikonomou, R.S. Fisher, H.P. Parkman, “Simultaneous assessment of gastric accomodation and emptying of solid and liquid meals”, Digestive Diseases Week (DDW'03), Orlando, Florida, May 17-22, 2003, Gastroenterology, Vol. 124, No. 4, A53-A53 Suppl. S, Apr. 2003.

 

19.  A.H. Maurer, H.P. Simonian, S.B. Kantor, L.C. Knight, V. Megalooikonomou, R.S. Fisher, H.P. Parkman, “Simultaneous Assessment of Gastric Accomodation and Emptying of a Solid Meal: A New Scintigraphic Test”, Society of Nuclear Medicine (SNM'03) 50th Annual Meeting, New Orleans, Louisiana, June 21-25, 2003.

 

20.  J. Ford, F. Makedon, V. Megalooikonomou, A. Saykin, L. Shen, T. Steinberg, “Spatial Comparison of fMRI Activation Maps for Data Mining: A Methodology of Hierarchical Characterization and Classification”, 7th Annual Meeting of the Organization for Human Brain Mapping, Brighton, UK, June, 2001, Neuroimage, Vol. 13, No. 6, S1302, 2001.

 

21.  Saykin, L. Flashman, L. Shen, J. Ashburner, M. Sparling, A. Donnelly, F. Makedon, D. Isecke, J. Ford, V. Megalooikonomou, T. McAllister, “Hippocampal Shape in Schizophrenia: A Deformation-Based Morphometric Analysis”, 7th Annual Meeting of the Organization for Human Brain Mapping, Brighton, UK, June, 2001, Neuroimage, Vol. 13, No. 6, S1096, 2001.

 

22.  D. Pokrajac, A. Lazarevic, V. Megalooikonomou, Z. Obradovic, “Classification of Brain Image Data using measures of distributional distance”, 7th Annual Meeting of the Organization for Human Brain Mapping, Brighton, UK, June, 2001, Neuroimage, Vol. 13, No. 6, S 222, 2001.

 

23.  E. H. Herskovits, V. Megalooikonomou, C. Davatzikos, J. Gerring, R. N. Bryan, “Evaluation of Closed-Head Injury Data with a Brain-Image Database: Statistical Analysis and Simulation”, presented at the 5th International Conference on Functional Mapping of the Human Brain (HBM'99), Dusseldorf, Germany, June 1999.

 

24.  E. H. Herskovits, V. Megalooikonomou, C. Davatzikos, R. N. Bryan, J. Gerring, “Spatial distribution of brain lesions associated with closed-head injury: Association with subsequent development of attention-deficit hyperactivity disorder”, Radiology, Vol. 209, Suppl. S, p. 479, Nov. 1998.

 

25.  K. A. Elliget, V. Megalooikonomou, “Automated identification and visualization of actin cytoskeleton injury in anoxic NRK-52E renal epithelial cells via volume investigation”, Molecular Biology of the Cell, Vol. 8, Suppl. S, pp. 269a, Nov. 1997.

 

Book Chapters  (in reverse chronological order)

1.      A. Skoura, V. Megalooikonomou, A. Diamantopoulos, G.C. Kagadis, D. Karnabatidis, “Classification of tree and network topology structures in medical images”, Springer-Verlag (to appear).

 

2.      L. Kozanidis, S. Stamou, V. Megalooikonomou, “Toward Semantics-Aware Web Crawling”, chapter in Data Management in the Semantic Web (H. Jin, editor), Nova Science Publishers, Inc., 2011, pp. 39-56, ISBN: 978-1-61122-862-5.

 

3.      V. Megalooikonomou and E. H. Herskovits, “Mining Structure-Function Associations in a Brain Image Database”, chapter in Medical Data Mining and Knowledge Discovery, pp. 153-179, K.J. Cios (ed.), Physica-Verlag, Heidelberg, 2001.