Publications

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Book Chapter
Aja-Fernández, S., G. Ramos-Llordén, and G. Vegas-Sánchez-Ferrero, "Nonlinear despeckle filtering", Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video: IET, 2018.
Martin-Fernandez, M., R. San Jose-Estepar, C-F. Westin, and C. Alberola-Lopez, "A novel Gauss-Markov random field approach for regularization of diffusion tensor maps", Computer Aided Systems Theory-EUROCAST 2003: Springer Berlin Heidelberg, pp. 506–517, 2003.
Conference Paper
Arribas, J. I., J. Cid-Sueiro, T. Adali, and A. R. Figueiras-Vidal, "Neural architectures for parametric estimation of a posteriori probabilities by constrained conditional density functions", Neural Networks for Signal Processing - Proceedings of the IEEE Workshop, Madison, WI, USA, IEEE, Piscataway, NJ, United States, 1999.
San-Jose-Revuelta, L. Miguel, M. Martin-Fernandez, and C. Alberola-Lopez, "Neural Network-Assisted Fiber Tracking of Synthetic and White Matter DT-MR Images.", World Congress on Engineering, pp. 618–623, 2007.
Wu, Y., J. He, Y. Man, and J. I. Arribas, "Neural network fusion strategies for identifying breast masses", IEEE International Conference on Neural Networks - Conference Proceedings, Budapest, 2004.
Arribas, J. I., J. Cid-Sueiro, T. Adali, and A. R. Figueiras-Vidal, "Neural networks to estimate ML multi-class constrained conditional probability density functions", Proceedings of the International Joint Conference on Neural Networks, Washington, DC, USA, IEEE, United States, 1999.
Arribas, J. I., C. Alberola-Lopez, A. Mateos-Marcos, and J. Cid-Sueiro, "Neural posterior probabilities for microcalcification detection in breast cancer diagnoses", Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on: IEEE, pp. 660–663, 2003.
Sabzi, S., Y. Abbaspour-Gilandeh, and J. I. Arribas, "A new method based on computer vision for non-intrusive orange peel sorting", 2017 56th FITCE Congress: IEEE, 2017.
San-Jose-Revuelta, L. Miguel, M. Martin-Fernandez, and C. Alberola-Lopez, "A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images", Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on: IEEE, pp. 1–4, 2007.
Aja-Fernández, S., G. Vegas-Sánchez-Ferrero, R. de Luis-García, and A. Tristán-Vega, "Noise estimation in magnetic resonance SENSE reconstructed data", Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE: IEEE, pp. 1104–1107, 2013.
Aja-Fernández, S., G. Vegas-Sánchez-Ferrero, and A. Tristán-Vega, "Noise estimation in MR GRAPPA reconstructed data", Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on: IEEE, pp. 1815–1818, 2011.
Sabzi, S., Y. Abbaspour-Gilandeh, and J. I. Arribas, "Non-intrusive image processing Thompson orange grading methods", 2017 56th FITCE Congress: IEEE, 2017.
Jiménez-Galindo, D., P. Casaseca-de-la-Higuera, and L. M. San-José-Revuelta, "A Novel Design Method for Digital FIR/IIR Filters Based on the Shuffle Frog-Leaping Algorithm", 2019 27th European Signal Processing Conference (EUSIPCO): IEEE, pp. 1–5, 2019.
Martin-Fernandez, M. Angel, C. Alberola-Lopez, and J. Ruiz-Alzola, "A novel error criterion for multiresolution volume data compression", [Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint, vol. 2: IEEE, pp. 1159–vol, 1999.
García-Pérez, V., A. Tristán-Vega, and S. Aja-Fernández, "NURBS for the geometrical modeling of a new family of Compact-Supported Radial Basis Functions for elastic registration of medical images", Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE: IEEE, pp. 5947–5950, 2010.
Conference Proceedings
de Luis-García, R., J. I. Arribas, S. Aja-Fernández, and A. C Lopez, "A neural architecture for bone age assessment", Proc. of the IASTED International Conference on Signal Processing, Pattern Recognition & Applications, pp. 161–166, 2002.
San-Jose-Revuelta, L. Miguel, M. Martin-Fernandez, and C. Alberola-Lopez, "A new method for fiber tractography in diffusion tensor magnetic resonance images", Proc. of the IEEE Int’l Conf. on Signal and Image Processing, ICSIP, vol. 6, pp. 380–385, 2006.
Journal Article
San-Jose-Revuelta, L. M., and J. I. Arribas, "A new approach for the design of digital frequency selective FIR fillters using an FPA-based algorithm", Expert Systems with Applications, vol. 106, 2018.
San-José-Revuelta, L. M., and P. Casaseca-de-la-Higuera, "A new flower pollination algorithm for equalization in synchronous DS/CDMA multiuser communication systems", Soft Computing: Springer Berlin Heidelberg, pp. 1–15, 2000, 2020.
Tristán-Vega, A., C-F. Westin, and S. Aja-Fernández, "A new methodology for the estimation of fiber populations in the white matter of the brain with the Funk–Radon transform", NeuroImage, vol. 49, no. 2: Academic Press, pp. 1301–1315, 2010.
Aja-Fernández, S., C. Alberola-Lopez, and C-F. Westin, "Noise and signal estimation in magnitude MRI and Rician distributed images: a LMMSE approach", Image Processing, IEEE Transactions on, vol. 17, no. 8: IEEE, pp. 1383–1398, 2008.
Brion, V., C. Poupon, O. Riff, S. Aja-Fernández, A. Tristán-Vega, J-F. Mangin, D. Le Bihan, and F. Poupon, "Noise correction for HARDI and HYDI data obtained with multi-channel coils and Sum of Squares reconstruction: An anisotropic extension of the LMMSE", Magnetic resonance imaging, vol. 31, no. 8: Elsevier, pp. 1360–1371, 2013.
Krissian, K., and S. Aja-Fernández, "Noise-driven anisotropic diffusion filtering of MRI", Image Processing, IEEE Transactions on, vol. 18, no. 10: IEEE, pp. 2265–2274, 2009.
Aja-Fernández, S., G. Vegas-Sánchez-Ferrero, and A. Tristán-Vega, "Noise estimation in parallel MRI: GRAPPA and SENSE", Magnetic resonance imaging, vol. 32, no. 3: Elsevier, pp. 281–290, 2014.
Aja-Fernández, S., A. Tristán-Vega, and C. Alberola-Lopez, "Noise estimation in single-and multiple-coil magnetic resonance data based on statistical models", Magnetic resonance imaging, vol. 27, no. 10: Elsevier, pp. 1397–1409, 2009.

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