thecenter

Staff

Maite Termenon

Postdoctoral Researcher

MRI, graph theory, resting state, reliability, machine learning, classification

E-Mail: m.termenon@bcbl.eu
Tel.: +34 943 309 300 Ext. 227

Publications

  • Termenon, M., Graña, M., Savio, A., Akusok, A., Miche, Y., Björk, K.-M., & Lendasse, A., ( 2016 ) Brain MRI morphological patterns extraction tool based on Extreme Learning Machine and majority vote classification. Neurocomputing, 174, Part A, 344–351, DOI: 10.1016/j.neucom.2015.03.111
  • Termenon, M., Jaillard, A., Achard, S., & Delon-Martin, C. , ( 2016 ) Graph based hub disruption index captures reorganization of contralesional hemisphere in stroke patients. Frontiers in Computational Neuroscience, 10, 84, DOI: 10.3389/fncom.2016.00084
  • Termenon, M., Jaillard, A., Delon-Martin, C., & Achard. S. , ( 2016 ) Reliability of graph analysis of resting state fMRI using test-retest dataset from the Human Connectome Project. Neuroimage, 142, 172-187. DOI: 10.1016/j.neuroimage.2016.05.062
  • Miche, Y., Akusok, A., Veganzones, D., Björk, K.-M., Séverin, E., du Jardin, P., Termenon, M., & Lendasse, A. , ( 2015 ) SOM-ELM—Self-Organized Clustering using ELM Neurocomputing, 165, 238–254, DOI: 10.1016/j.neucom.2015.03.014
  • Termenon, M., Chyzhyk, D., Graña, M., Barros-Loscertales, A., & Avila, C. , ( 2013 ) Cocaine Dependent Classification on MRI Data Extracting Features from Voxel Based Morphometry. Natural and Artificial Computation in Engineering and Medical Applications. 2 Eds. Springer Berlin Heidelberg, 140–148.
  • Termenon, M., Graña, M., Besga, A., Echeveste, J., Pérez, J. M., & Gonzalez-Pinto, A. , ( 2013 ) Diagnosis of Bipolar Disorder Based on Principal Component Analysis and SVM. Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Eds. Springer International Publishing, 569–578.
  • Termenon, M., Graña, M., Barrós-Loscertales, A., & Ávila. C. , ( 2013 ) Extreme Learning Machines for Feature Selection and Classification of Cocaine Dependent Patients on Structural MRI Data. Neural Processing Letters, 38, 3, 375–387, DOI: 10.1007/s11063-013-9277-x
  • Termenon, M., Fernández, E., Graña, M., Barrós-Loscertales, A., Bustamante, J. C., & Ávila, C. , ( 2013 ) Impact of Circularity Analysis on Classification Results: A Case Study in the Detection of Cocaine Addiction Using Structural MRI. Advanced Techniques for Knowledge Engineering and Innovative Applications. Eds. Springer Berlin Heidelberg, 101–114.
  • Termenon, M., Graña, M., Barrós-Loscertales, A., Bustamante, J., & Ávila, C, ( 2012 ) Cocaine Dependent Classification Using Brain Magnetic Resonance Imaging. Hybrid Artificial Intelligent Systems, 7209. Eds. Springer Berlin / Heidelberg, 2012, 448–454.
  • Besga, A., Termenon, M., Graña, M., Echeveste, J., Pérez, J. M., & Gonzalez-Pinto, A. , ( 2012 ) Discovering Alzheimer’s disease and bipolar disorder white matter effects building computer aided diagnostic systems on brain diffusion tensor imaging features. Neuroscience Letters, 520, 1, 71–76, DOI: 10.1016/j.neulet.2012.05.033
  • Termenon, M., Graña, M., Besga, A., Echeveste, J., & Gonzalez-Pinto, A. , ( 2012 ) Lattice independent component analysis feature selection on diffusion weighted imaging for Alzheimer’s disease classification. Neurocomputing, 114, 132–141, DOI: 10.1016/j.neucom.2012.08.044
  • Termenon, M., & Graña, M. , ( 2011 ) A Two Stage Sequential Ensemble Applied to the Classification of Alzheimer’s Disease Based on MRI Features. Neural Processing Letters, 35, 1, 1–12, DOI: 10.1007/s11063-011-9200-2
  • Termenon, M., Besga, A., Echeveste, J., Gonzalez-Pinto, A., & Graña, M. , ( 2011 ) Alzheimer Disease Classification on Diffusion Weighted Imaging Features. New Challenges on Bioinspired Applications, Ferrández, J. M., Sánchez, J. R. Á., de la Paz, F., & Toledo, F. J., Eds. Springer Berlin Heidelberg, 120–127.
  • Graña, M., Termenon, M., Savio, A., Gonzalez-Pinto, A., Echeveste, J., Pérez, J. M., & Besga, A. , ( 2011 ) Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson’s correlation. Neuroscience Letters, 502, no. 3, 225–229, DOI: 10.1016/j.neulet.2011.07.049
  • Termenon, M., & Graña, M. , ( 2011 ) Further Results on Alzheimer Disease Detection on Structural MRI Features. Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011, 87. Eds. Springer Berlin/Heidelberg, 2011, 515–522.
  • Chyzyk, D., Termenon, M., & Savio, A. , ( 2010 ) A Comparison of VBM Results by SPM, ICA and LICA. Hybrid Artificial Intelligence Systems. Eds. Springer Berlin Heidelberg, 429–435.
  • Savio, A., Charpentier, J., Termenon, M., Shinn, A. K., & Graña, M. , ( 2010 ) Neural classifiers for schizophrenia diagnostic support on diffusion imaging data. Neural Network World, 20, 935–949.
  • Toro, C., Termenon, M., Posada, J., Oyarzun, J., & Falcón. J. , ( 2007 ) Ontology Supported Adaptive User Interfaces for Structural CAD Design. Digital Enterprise Technology, Eds. Boston, MA: Springer US, 283–290.
  • Toro, C., Posada, J., Termenon, M., Oyarzun, J., & Falcón, J. , ( 2006 ) Knowledge Based Tools To Support The Structural Design Process. Knowledge-Based Intelligent Information And Engineering Systems, 4251. Eds. Springer Berlin Heidelberg, 2006, 679–686.