Publications

Refereed Publications in International Journals (in reverse chronological order)

  1. G. Kanas, E. I. Zacharaki, G. A. Thomas, P. O. Zinn, V. Megalooikonomou, R. R. Colen, “Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma”, Computer Methods and Programs in Biomedicine, 140, pp. 249-257, 2017.
  2. Simaki, C. Aravantinou, I. Mporas, M. Kondyli, & V. Megalooikonomou, “Sociolinguistic Features for Author Gender Identification: from qualitative evidence to quantitative analysis”, Journal of Quantitative Linguistics, 24(1), pp:65-84, 2017.
  3. Papageorgiou, V. Megalooikonomou and D. Vlachakis, “Genetic and structural study of DNA-directed RNA polymerase II of Trypanosoma brucei towards the designing of novel antiparasitic agents”, PeerJ, Mar 1;5:e3061. doi: 10.7717/peerj.3061, 2017.
  4. Triantafyllopoulos, P. Korvesis, I. Mporas and V. Megalooikonomou, “Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic patients”, Journal of Medical Systems, 40(3), pp. 1-11, 2016.
  5. I. Zacharaki, I. Mporas, K. Garganis, V. Megalooikonomou, “Spike pattern recognition by supervised classification in low dimensional embedding space”, Brain Informatics, 3(2), pp 73-83, 2016.
  6. Pippa, E.I. Zacharaki, I. Mporas, V. Tsirka, M. Richardson, M. Koutroumanidis and V. Megalooikonomou, “Improving Classification of Epileptic and Non-Epileptic EEG Events by Feature Selection”, Neurocomputing, Vol. 171, pp. 576–585, 2016.
  7. Pippa, V. G. Kanas, E. I. Zacharaki, V. Tsirka, M. Koutroumanidis, V. Megalooikonomou, “EEG-based Classification of Epileptic and Non-Epileptic Events using Multi-Array Decomposition”, IJMSTR 4(2): 1-15, 2016.
  8. Zygomalas, D. Karavias, D. Koutsouris, I. Maroulis, D.D. Karavias, K. Giokas, V. Megalooikonomou, “Computer assisted liver tumor surgery using a novel semiautomatic and a hybrid semiautomatic segmentation algorithm”, Medical & Biological Engineering & Computing, pp. 1-11, 10.1007/s11517-015-1369-5, 2015.
  9. G. Kanas, E. I. Zacharaki, C. Davatzikos, K. N. Sgarbas, V. Megalooikonomou, “A low cost approach for brain tumor segmentation based on intensity modeling and 3D Random Walker”, Biomedical Signal Processing and Control, vol. 22, pp. 19-30, 2015.
  10. Mporas, V. Tsirka, E. I. Zacharaki, M. Koutroumanidis, M. Richardson, V. Megalooikonomou, “Seizure detection using EEG and ECG signals for computer-based monitoring, analysis and management of epileptic patients”, Expert Systems with Applications, 42, pp. 3227-3233, 2015.
  11. Skoura, Ι. Mporas, and V. Megalooikonomou, “Classifying Tree Structures using Elastic Matching of Sequence Encodings”, Neurocomputing, vol. 163, pp. 151-159, 2015.
  12. Vlachakis, P. Fakourelis, V. Megalooikonomou, C. Makris, S. Kossida, “DrugOn: a fully integrated pharmacophore modeling and structure optimization toolkit”, PeerJ 3:e725; DOI 10.7717/peerj.725, 2015.
  13. Koutsioumpa, E. Poimenidi, E. Pantazaka, C. Theodoropoulou, A. Skoura, V. Megalooikonomou, N. Kieffer, J. Courty, S. Mizumoto, K. Sugahara and E. Papadimitriou, “Receptor protein tyrosine phosphatase beta/zeta is a functional binding partner for vascular endothelial growth factor”, Molecular Cancer, 14(19), doi:10.1186/s12943-015-0287-3, 2015.
  14. D. Malliaros, V. Megalooikonomou, and C. Faloutsos, “Estimating Robustness in Large Social Graphs”, Knowledge and Information Systems: An International Journal, Volume 45, Issue 3, pp 645-678, 2015.
  15. Cheng, L. Du, Y. Wu, Y. Zhu, V. Megalooikonomou, and H. Ling, “Discriminative Vessel Segmentation in Retinal Images by Fusing Context-Aware Hybrid Features”, Machine Vision and Applications, 25(7):1779-1792, 2014.
  16. Papageorgiou, S. Loukatou, VL Koumandou, W. Makałowski, V. Megalooikonomou, D. Vlachakis, S. Kossida. “Structural models for the design of novel antiviral agents against Greek Goat Encephalitis”, PeerJ. 2014, 2:e664. doi: 10.7717/peerj.664.
  17. Loukatou, P. Fakourelis, L. Papageorgiou, V. Megalooikonomou, S. Kossida, D. Vlachakis. “Ebola virus epidemic: a deliberate accident?”, J Mol Biochem. 2014, 3(3):72-76.
  18. Skoura, T. Nuzhnaya, and V. Megalooikonomou, “Integrating edge detection and fuzzy connectedness for automated segmentation of anatomical branching structures”, International Journal of Bioinformatics Research and Applications, 10(1), pp. 93-109, 2014.
  19. Papangelopoulos, D. Vlachakis, A. Filntisi, P. Fakourelis, L. Papageorgiou, V. Megalooikonomou, S. Kossida, “State of the art GPGPU applications in bioinformatics”, International Journal of Systems Biology and Biomedical Technologies, 2(4): 24-48, 2014.
  20. Ling, X. Yang, P. Li, V. Megalooikonomou, Y. Xu, J. Yang, “Cross gender-age trabecular texture analysis in dental cone beam computed tomography”, Dentomaxillofacial Radiology, (DMFR), 43:20130324, 2014.
  21. Α. Skoura, P. R. Bakic, and V. Megalooikonomou, “Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers”, Journal of Theoretical and Applied Computer Science, vol. 7, no. 1, pp. 3-19, 2013.
  22. Vlachakis, D. Tsagrasoulis, V. Megalooikonomou, S. Kossida, “Introducing Drugster: a comprehensive and fully integrated drug design, lead and structure optimization toolkit”, Bioinformatics 29 (1): 126-128, 2013.
  23. S. Carvalho, D. Vlachakis, G. Tsiliki, V. Megalooikonomou, S. Kossida. “Protein signatures using electrostatic molecular surfaces in harmonic space”,” PeerJ, 1:e185, http://dx.doi.org/10.7717/peerj.185.
  24. Vlachakis, C. Feidakis, V. Megalooikonomou, S. Kossida, “A two-dimensional visualization tool for amino acid domain sequences”,” Theoretical Biology and Medical Modelling, vol. 10, No.14, 2013.
  25. Vlachakis, G. Tsiliki, D. Tsagkrasoulis, C. S. Carvalho, V. Megalooikonomou, S. Kossida, “Speeding up the drug discovery process: structural similarity searches using molecular surfaces”, EMBNet journal, Bioinformatics in Action, Vol 18, No. 1, 2012.
  26. Lakoumentas, J. Drakos, M. Karakantza, G. Sakellaropoulos, V. Megalooikonomou, G. Nikiforidis, “Optimizations of the naive-Bayes classifier for the prognosis of B-Chronic Lymphocytic Leukemia incorporating flow cytometry data”, Computer Methods and Programs in Biomedicine, 108 (1), 158-67, 2012.
  27. 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.
  28. Barnathan, V. Megalooikonomou, C. Faloutsos, S. Faro, F.B. Mohamed, «TWave: High-Order Analysis of Functional MRI», NeuroImage, 58(2): pp. 537-548, 2011.
  29. 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.
  30. Wang, V. Megalooikonomou, C. Faloutsos, «Time Series Analysis with Multiple Resolutions», Information Systems, Vol. 35, No. 1, pp. 56-74, 2010.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. Wang and V. Megalooikonomou, «A Dimensionality Reduction Technique for Efficient Time Series Similarity Analysis», Information Systems, 33, pp. 115-132, 2008.
  36. 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.
  37. 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.
  38. 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.
  39. Latecki, V. Megalooikonomou, Q. Wang, D. Yu, «An Elastic Partial Shape Matching Technique», Pattern Recognition, Vol. 40, No. 11, pp. 3069-3080, 2007.
  40. 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.
  41. 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.
  42. 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
  43. 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.
  44. 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.
  45. Kumaraswamy, V. Megalooikonomou and C. Faloutsos, «Fractal Dimension and Vector Quantization», Information Processing Letters, Vol. 91, No. 3, pp. 107-113, 2004.
  46. 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.
  47. 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.
  48. Megalooikonomou and Y. Yesha, «Quantization for Distributed Estimation using Neural Networks», Information Sciences, Vol. 148, No. 1-4, pp. 185-199, 2002.
  49. 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.
  50. 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.
  51. 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.
  52. 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. G. Dimitropoulos, S. Papagianni and V. Megalooikonomou, “Lag Correlation Discovery and Classification for Time Series and Data Streams”, in Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security (IoTBDS), Porto, Portugal, Apr. 24-26, 2017.
  2. Chunjuan Bo, Liang Xin, Peng Chu, Jonathan Xu, Dong Wang, Yang Jie, Vasilis Megalooikonomou, Haibin Ling, “Osteoporosis Prescreening Using Dental Panoramic Radiographs Feature Analysis”, IEEE International Symposium on Biomedical Imaging (ISBI) Apr. 18-21, Melbourne, Australia, 2017.
  3. F. Tagkalakis, D. Vlachakis, V. Megalooikonomou, A. Skodras, “A Novel Approach to Finger Vein Authentication”, IEEE International Symposium on Biomedical Imaging (ISBI) Apr. 18-21, Melbourne, Australia, 2017.
  4. G. Drakopoulos and V. Megalooikonomou, “An adaptive higher order scheduling policy with an application to biosignal processing”, in Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 921-928, Dec. 2016.
  5. P. Ntanasis, E. Pippa, A. T. Özdemir, B. Barshan, V. Megalooikonomou, “Investigation of sensor placement for accurate fall detection”, 6th EAI International Conference on Wireless Mobile Communication and Healthcare (MobiHealth) – “Transforming healthcare through innovations in mobile and wireless technologies”, Milan, Italy, Nov. 14–16, 2016.
  6. G. Drakopoulos, A. Kanavos, C. Makris, and V. Megalooikonomou, “Comparing Algorithmic Principles for Fuzzy Graph Communities over Neo4j”, Chapter in Advances in Combining Intelligent Methods, volume 116 of the Springer series Intelligent Systems Reference Library, pp 47-73, Nov. 2016.
  7. F. Tagkalakis, A. Papagiannaki, G. Drakopoulos and V. Megalooikonomou,  “Augmenting fMRI generated brain connectivity with temporal information”, 7th International Conference on Information, Intelligence, Systems and Applications (IISA), Chalkidiki, Greece, 2016.
  8. G. Drakopoulos and V. Megalooikonomou, “Regularizing Large Biosignals with Finite Differences”, 7th International Conference on Information, Intelligence, Systems and Applications (IISA), Chalkidiki, Greece, 2016.
  9. V. Simaki, I. Mporas, & V. Megalooikonomou. (2016). “Age Identification of Twitter Users: Classification Methods and Sociolinguistic Analysis”, 17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2016.
  10. E. Cheng, L. Zhu, J. Yang, Azhari, S. Sitam, X. Liang, V. Megalooikonomou, H. Ling, “Learning-based landmarks detection for osteoporosis analysis”. SPIE Medical Imaging: Image Processing 2016: 97841X.
  11. G. Drakopoulos and V. Megalooikonomou, “A Graph Framework for Multimodal Medical Information Processing”, International Symposium on Mobile and Assistive Technology for Healthcare (MATH) at the 8th International Conference on eHealth, Telemedicine, and Social Medicine (eTELEMED), Venice, Italy, 2016.
  12. G. Drakopoulos, S. Kontopoulos, C. Makris, V. Megalooikonomou, “Large Graph Models: A Review”. CoRR abs/1601.06444 (2016).
  13. E. Pippa, I. Mporas and V. Megalooikonomou, “Feature Selection Evaluation for Light Human Motion Identification in Frailty Monitoring System”, 2nd International Conference on Information and Communication Technologies for Ageing Well and e-Helath (ICT4AWE), Rome, Italy, 2016.
  14. K. G. Nikolakopoulos, I. Koukouvelas, N. Argyropoulos, V. Megalooikonomou, “Quarry monitoring using GPS measurements and UAV photogrammetry”, Proc. SPIE 9644, Earth Resources and Environmental Remote Sensing/GIS Applications VI, 96440J (October 20, 2015); doi:10.1117/12.2195402, Toulouse, France, September 21, 2015.
  15. I. Mporas, A. Efstathiou, and V.  Megalooikonomou, “Sleep Stages Classification from Electroencephalographic Signals based on Unsupervised Feature Space Clustering”, International Conference on Brain and Health Informatics (BIH), Aug. 30- Sept. 2, 2015.
  16. V. Simaki, C. Aravantinou, I. Mporas and V. Megalooikonomou, “Automatic Estimation of Web Bloggers’ Age using Regression Models”, 17th International Conference on Speech and Computer (SPECOM), Sept. 20-24, 2015, Athens, Greece.
  17. C. Aravantinou, V. Simaki, I. Mporas and V. Megalooikonomou, “Gender Classification of Web Authors Using Feature Selection and Language Models”, 17th International Conference on Speech and Computer (SPECOM), Sept. 20-24, 2015, Athens, Greece.
  18. V. Simaki, A. Koumpouri, I. Mporas and V. Megalooikonomou, “Gender Identification of Blog Authors: Do Men and Women Prefer Different Character Unigrams? ” 17th International Conference on Speech and Computer (SPECOM), Sept. 20-24, 2015, Athens, Greece.
  19. A. Koumpouri, I. Mporas, V. Megalooikonomou, “Opinion Recognition on Movie Reviews by Combining Classifiers”, 17th International Conference on Speech and Computer (SPECOM), Sept. 20-24, 2015, Athens, Greece.
  20. G. Drakopoulos, A. Kanavos, C. Markis, V. Megalooikonomou, “On converting community detection algorithms for fuzzy graphs in Neo4j”, 5th International Workshop on Combinations of Intelligent Methods and Applications (CIMA-15), in conjunction with the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI-15), 09-11 November 2015, Vietri sul Mare, Italy.
  21. G. Drakopoulos, A. Baroutiadi, V. Megalooikonomou, “Higher order graph centrality measures for Neo4j”, 6th International Conference on Information, Intelligence, Systems and Applications (IISA2015), Ionian University, Corfu, Greece, July 6-8, 2015.
  22. G. Drakopoulos, V. Megalooikonomou, “On the weight sparsity of multilayer perceptrons”, 6th International Conference on Information, Intelligence, Systems and Applications (IISA2015), Ionian University, Corfu, Greece, July 6-8, 2015.
  23. F. K. Kartsakalis, A. Skoura, V. Megalooikonomou, “Retrieving Similar Segmented Objects using Motion Descriptors”, XIII International Conference on Image Processing (ICIP), Zurich, Switzerland, Jan. 13-14, 2015.
  24. A. Skoura, V. Megalooikonomou, “Analyzing Anatomical Structures of Branching Topology through Elastic Matching of Tree Encodings”, Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), pp. 393-396, Beijing, China, May 2014.
  25. P. Li, X. Yang, F. Xie, J. Yang, E. Cheng, V. Megalooikonomou, Y. Xu, H. Ling, “Trabecular Texture Analysis in Dental CBCT by Multi-ROI Multi-Feature Fusion”, Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), pp. 393-396, Beijing, China, May 2014.
  26. O. Politi, I. Mporas, V. Megalooikonomou, “Comparative Evaluation of Feature Extraction Methods for Human Motion Detection”, 3rd Mining Humanistic Data Workshop (MHDW) – AIAI, Greece, Sept. 2014.
  27. O. Politi, I. Mporas, V. Megalooikonomou, “Human Motion Detection in Daily Activity Tasks Using Wearable Sensors”, Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), pp. 2315-2319, Portugal, 2014.
  28. D. Triantafyllopoulos, V. Megalooikonomou, “Eye blink artifact removal in EEG using tensor decomposition”, 3rd Mining Humanistic Data Workshop (MHDW) “ AIAI, Greece, Sept. 2014.
  29. E. Pippa, E. I. Zacharaki, I. Mporas,V. Tsirka, M. Richardson, M. Koutroumanidis, V. Megalooikonomou, “Classification of Epileptic and Non-Epileptic EEG Events”, 4th Int. Conf. on Wireless Mobile Communication and Healthcare (MOBIHEALTH 2014), Athens, Greece, Nov. 2014.
  30. I. Mporas, V. Tsirka, E.I. Zacharaki, M. Koutroumanidis, V. Megalooikonomou, “Evaluation of Time and Frequency Domain Features for Seizure Detection from Combined EEG and ECG signals”, 7th Int. Conf. on PErvasive Technologies Related to Assistive Environments (PETRA), Rhodes Island, Greece, 2014.
  31. E.I. Zacharaki, K. Garganis, I. Mporas, V. Megalooikonomou, “Spike detection in EEG by LPP and SVM”, IEEE EMBS Int. Conf. on Biomedical and Health Informatics (BHI), pp.668-671, Valencia, Spain, June 2014.
  32. I. Mporas, V. Tsirka, E.I. Zacharaki, M. Koutroumanidis, V. Megalooikonomou, “Online Seizure Detection from EEG and ECG signals for Monitoring of Epileptic Patients,” 8th Hellenic Conference on Artificial Intelligence (SETN), Lecture Notes in Computer Science, vol. 8445, pp 442-447, 2014.
  33. I. Mporas, P. Korvesis, E. Zacharaki, V. Megalooikonomou, “Sleep Spindle Detection in EEG Signals Combining HMMs and SVMs”, Proceedings of the 2nd Mining Humanistic Data Workshop (MHDW), Engineering Applications of Neural Networks (EANN), 13-16 Sept. 2013, Communications in Computer and Information Science series, Vol. 0384, 2013.
  34. A. Skoura, T. Nuzhnaya, P. Bakic, V. Megalooikonomou, “Classifying Ductal Trees Using Geometrical Features and Ensemble Learning Techniques”, Proceedings of the 2nd Mining Humanistic Data Workshop (MHDW), Engineering Applications of Neural Networks (EANN), 13-16 Sept. 2013, Communications in Computer and Information Science series, Vol. 0384, pp 146-155, Halkidiki, Greece, 13-16 Sept, 2013.
  35. A. Charisi, F. D. Malliaros, E. I. Zacharaki, V. Megalooikonomou, “Multiresolution Similarity Search in Time Series Data: An Application to EEG Signals”, 6th International Conference on Pervasive Technologies Related to Assistive Environments, PETRA”13, Island of Rhodes, Greece, May 29-31, 2013.
  36. A. Skoura, T. Nuzhnaya, P. R. Bakic, V. Megalooikonomou, “Detecting and Localizing Tree Nodes in Anatomic Structures of Branching Topology”, International Conference on Image Analysis and Recognition, Lecture Notes in Computer Science, Volume 7950, pp 485-493, P”voa de Varzim, Portugal, June 26-28, 2013.
  37. E.I. Zacharaki, E. Pippa, A. Koupparis, V. Kokkinos, G. Kostopoulos, V. Megalooikonomou, “One-class classification of temporal EEG patterns for K-complex extraction,” 35th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC “13), pp. 5801-5804, Osaka, Japan, July 3-7, 2013.
  38. E.I. Zacharaki, E. Pippa, A. Koupparis, G.K. Kostopoulos, V. Megalooikonomou, “Classification of EEG waveforms by spectral clustering,” 5th Pan-Hellenic Conference on Biomedical Technology, Athens, April 4-6, 2013.
  39. A. Skoura and V. Megalooikonomou, “Analyzing Anatomical Tree-like Structures”, 5th Panhellenic Conference of Biomedical Technology, Athens, Greece, April 4-6, 2013.
  40. Y. Wu, F. Xie, J. Yang, E. Cheng, V. Megalooikonomou, H. Ling, “Automatic detection of apical roots in oral radiographs”, in Proc. SPIE 8315-93, Medical Imaging 2012: Computer-Aided Diagnosis, 83152M, 2012.
  41. Y. Wu, F. Xie, J. Yang, E. Cheng, V. Megalooikonomou, H. Ling, “Computer aided periapical lesion diagnosis using quantized texture analysis”, Proc. SPIE 8315-43, Medical Imaging: Computer-Aided Diagnosis, 831518, 2012.
  42. T. Nuzhnaya, P. Bakic, D. Kontos, V. Megalooikonomou, H. Ling, “Segmentation of anatomical branching structures based on texture features and conditional random field”, SPIE Proceedings Vol. 8314, Medical Imaging: Image Processing, David R. Haynor; Sebastien Ourselin, Editors, 2012
  43. 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), pp. 1587-1590, Barcelona, Spain, 2012.
  44. E. I. Zacharaki, A. Skoura, L. An, D. Smith, V. Megalooikonomou, “Using an Atlas-Based Approach in the Analysis of Gene Expression Maps Obtained by Voxelation”, 1st Workshop on Algorithms for Data and Text Mining in Bioinformatics (WADTMB 2012), Artificial Intelligence Applications and Innovations IFIP Advances in Information and Communication Technology, Volume 382, pp 566-575, Halkidiki, Greece, September 27-30, 2012.
  45. E.I. Zacharaki, A. Skoura, D.J. Smith,” S.H. Faro, L. An, V. Megalooikonomou, “Combining gene expression and function in a spatially localized approach”, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philadelphia, PA, pp. 1-8, 2012.
  46. 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.
  47. 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.
  48. 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.
  49. 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.
  50. 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.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. 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.
  58. 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.
  59. 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.
  60. 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.
  61. 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.
  62. 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.
  63. 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.
  64. 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.
  65. 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.
  66. 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.
  67. 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.
  68. 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.
  69. 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.
  70. 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.
  71. 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.
  72. 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.
  73. 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.
  74. 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.
  75. 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.
  76. 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.
  77. 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.
  78. 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.
  79. 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.
  80. 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.
  81. 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.
  82. 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.
  83. 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.
  84. 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.
  85. 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.
  86. 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.
  87. 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.
  88. 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.
  89. 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.
  90. 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.
  91. 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.
  92. 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.
  93. 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.
  94. 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.
  95. 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.
  96. 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.
  97. 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.
  98. 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.
  99. 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.
  100. 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.
  101. 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.
  102. 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.
  103. 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.
  104. 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.
  105. 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.
  106. 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.
  107. 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.
  108. 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.
  109. 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.
  110. 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.
  111. 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.
  112. 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.
  113. 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.

 

Extended Abstracts in Journals and Conference  Proceedings (in reverse chronological order)

  1. Kagadis G, Alexakos C, Papadimitroulas P, Mihailidis D, Megalooikonomou V, Siablis D, Papanikolaou N, Karnabatidis D, SU-E-I-69: A Cloud Based Application for MRI Brain Image Processing, AAPM 57th Annual Meeting & Exhibition, Med Phys. 2015 Jun; 42(6):3257. doi: 10.1118/1.4924066.
  2. Zygomalas A, Megalooikonomou V, Koutsouris D, Karavias D, Karagiannidis I, Amanatidis T, Maroulis I, Giokas K, Karavias D. (2015), Liver 3D modeling and hepatectomy simulation for the residents’ preoperative education, Appeared in the 2nd International Conference on Medical Education Informatics, Thessaloniki, Greece. PeerJ PrePrints 3:e1335 https://dx.doi.org/10.7287/peerj.preprints.1092v1.
  3. Zygomalas A, Megalooikonomou V, Koutsouris D, Karavias D, Karagiannidis I, Amanatidis T, Maroulis I, Giokas K, Karavias D. (2015) Virtual hepatic surgery scenarios using manipulated real liver models. Appeared in the 2nd International Conference on Medical Education Informatics Thessaloniki, Greece. PeerJ PrePrints 3:e1333 https://dx.doi.org/10.7287/peerj.preprints.1090v1.
  4. C. Kagadis, C. Alexakos, P. Papadimitroulas, N. Papanikolaou, V. Megalooikonomou, D. Karnabatidis, “Cloud Computing Application for Brain Tumor Detection”, European Congress of Radiology (ECR), March 4-8, Vienna, 2015.
  5. 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, Valencia, Spain, Oct. 23-29, 2011.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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

  1. Megalooikonomou, D. Triantafyllopoulos, E.I. Zacharaki, I. Mporas, “Offline Analysis Server and Offline Algorithms”, Chapter in Cyberphysical Systems for Epilepsy and Related Brain Disorders: Multi-parametric Monitoring and Analysis for Diagnosis and Optimal Disease Management, N.S. Voros, C. Antonopoulos (Eds.), Springer, 2015.
  2. Megalooikonomou, D. Triantafyllopoulos, E.I. Zacharaki, I. Mporas,“DSMS and Online Algorithms”, Chapter in Cyberphysical Systems for Epilepsy and Related Brain Disorders: Multi-parametric Monitoring and Analysis for Diagnosis and Optimal Disease Management, N.S. Voros, C. Antonopoulos (Eds.), Springer, 2015.
  3. Hey, P. Anastasopoulou, A. Bideaux, C. Antonopoulos, N. Voros, A. Fernandez, V. Megalooikonomou, A. Krukowski, “System Architecture”, Chapter in Cyberphysical Systems for Epilepsy and Related Brain Disorders: Multi-parametric Monitoring and Analysis for Diagnosis and Optimal Disease Management, N.S. Voros, C. Antonopoulos (Eds.), Springer, 2015.
  4. Skoura, V. Megalooikonomou, A. Diamantopoulos, G.C. Kagadis, D. Karnabatidis, «Classification of tree and network topology structures in medical images», in Data Mining for Biomarker Discovery, P.M. Pardalos et al., Springer Optimization and Its Applications, Volume 65, 2012, DOI: 10.1007/978-1-4614-2107-8, Springer Science +Business Media, pp.79-90.
  5. 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.
  6. 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.

 

Other Publications

  1. V. Charpantidis, V. Megalooikonomou, «Spatiotemporal data analysis and knowledge extraction in Geographic Information Systems», ΕΥΡΗΚΑ 2011, 5ο Πανελλήνιο Επιστημονικό Συνέδριο για Προπτυχιακούς και Μεταπτυχιακούς Φοιτητές στην Πληροφορική, τις συναφείς Τεχνολογίες και τις Εφαρμογές, Καστοριά, 2011.
  2. Π. Κορβέσης, Β. Μεγαλοοικονόμου, «Τεχνικές εξόρυξης γνώσης σε δεδομένα χρονοσειρών», 3ο Πανελλήνιο Επιστημονικό Φοιτητικό Συνέδριο Πληροφορικής, Κέρκυρα, 2009.
  3. Φ. Μαλλιαρός, Β. Μεγαλοοικονόμου, «Τεχνικές εξόρυξης δεδομένων χωρίς παραμέτρους», 3ο Πανελλήνιο Επιστημονικό Φοιτητικό Συνέδριο Πληροφορικής, Κέρκυρα, 2009.
  4. Α. Σκούρα, Β. Μεγαλοοικονόμου, “Αναπαράσταση και κατηγοριοποίηση δενδρικών δομών από ιατρικά δεδομένα”, 3ο Πανελλήνιο Επιστημονικό Φοιτητικό Συνέδριο Πληροφορικής, Κέρκυρα, 2009.

 

Technical Reports

  1. Megalooikonomou, «Kolmogorov Incompressibility Method in Formal Proofs: A Critical Survey», Technical Report TR CS-97-01, Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Jan. 1997.
  2. V. Megalooikonomou, K. A. Elliget and N. DeClaris, «Image Based Study of Cytoskeleton Injury», Technical Report TR MI-96-25, Division of Medical Informatics, Department of Pathology, School of Medicine, University of Maryland at Baltimore, Sept. 1996.