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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.
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.
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.
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.
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.
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 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.
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.
Royuela-del-Val, J., L. Cordero-Grande, F. Simmross-Wattenberg, M. Martin-Fernandez, and C. Alberola-Lopez, "Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruction of Breath-Hold Cardiac Cine MRI", Magnetic Resonance in Medicine, 2015.
Pieciak, T., S. Aja-Fernández, and G. Vegas Sánchez-Ferrero, "Non-Stationary Rician Noise Estimation in Parallel MRI using a Single Image: a Variance-Stabilizing Approach", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, issue 10, pp. 2015-2029, 2017.
Abbaspour-Gilandeh, Y., S. Sabzi, F. Azadshahraki, R. Karimzadeh, E. Ilbeygi, and J. I. Arribas, "Non-destructive Estimation of Chlorophyll a Content in Red Delicious Apple Cultivar Based on Spectral and Color Data", Journal of Agricultural Sciences, vol. 26, pp. 339–348, 2020.
Pourdarbani, R., S. Sabzi, D. Kalantari, and J. I. Arribas, "Non-destructive visible and short-wave near-infrared spectroscopic data estimation of various physicochemical properties of Fuji apple (Malus pumila) fruits at different maturation stages", Chemometrics and Intelligent Laboratory Systems, pp. 104147, 2020.
Sabzi, S., Y. Abbaspour-Gilandeh, and J. I. Arribas, "Non-intrusive image processing Thompson orange grading methods", 2017 56th FITCE Congress: IEEE, 2017.
Martín-Martínez, D., P. Casaseca-de-la-Higuera, S. Alberola-Lopez, J. Maria Andres-de-Llano, JA. López-Villalobos, J. Ardura-Fernández, and C. Alberola-Lopez, "Nonlinear analysis of actigraphic signals for the assessment of the attention-deficit/hyperactivity disorder (ADHD)", Medical engineering & physics, vol. 34, no. 9: Elsevier, pp. 1317–1329, 2012.
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.
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.
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Alberola-Lopez, C., C. -Corredera, JR, and G. de Miguel-Vela, "Object CFAR detection in gamma-distributed textured-background images", IEE Proceedings-Vision, Image and Signal Processing, vol. 146, no. 3: IEE, pp. 130–136, 1999.
Amado-Caballero, P., P. Casaseca-de-la-Higuera, S. Alberola-Lopez, J. Maria Andres-de-Llano, J. Antonio Lopez-Villalobos, J. Ramon Garmendia-Leiza, and C. Alberola-Lopez, "Objective ADHD diagnosis using Convolutional Neural Networks over Daily-Life Activity Records", IEEE Journal of Biomedical and Health Informatics, 2020.
Simmross-Wattenberg, F., M. Rodríguez-Cayetano, J. Royuela-del-Val, E. Martín-González, E. Moya-Sáez, M. Martín-Fernández, and C. Alberola-Lopez, "OpenCLIPER: An OpenCL-Based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices", IEEE Journal of Biomedical and Health Informatics, vol. 23, pp. 1702-1709, July, 2019.
Peña-Nogales, O., Y. Zhang, R. de Luis-García, S. Aja-Fernández, J. H. Holmes, and D. Hernando, "Optimal Diffusion-weighting Gradient Waveform Design (ODGD): Formulation and Experimental Validation", International Society of Magnetic Resonance in Medicine 26th Annual Meeting and Exhibition, Paris, France, pp. 685, 2018.
Peña-Nogales, Ó., R. de Luis-García, S. Aja-Fernández, Y. Zhang, J. H. Holmes, and D. Hernando, "Optimal design of motion-compensated diffusion gradient waveforms ", International Society of Magnetic Resonance in Medicine 25th Annual Meeting and Exhibition, Honolulu, HI, USA, pp. 3340, 2017.

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