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Multi-patient learning increases accuracy for Subthalamic nucleus identification in deep brain stimulation.

, , and . EMBC, page 4341-4344. IEEE, (2012)

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Tensor decomposition processes for interpolation of diffusion magnetic resonance imaging., , , and . Expert Syst. Appl., (2019)Convolved Multi-output Gaussian Processes for Semi-Supervised Learning., , and . ICIAP (1), volume 9279 of Lecture Notes in Computer Science, page 109-118. Springer, (2015)Automatic Recognition of Microcalcifications in Mammography Images through Fractal Texture Analysis., , and . ISVC (2), volume 8888 of Lecture Notes in Computer Science, page 841-850. Springer, (2014)Generalized Wishart Processes for Interpolation Over Diffusion Tensor Fields., , and . ISVC (2), volume 9475 of Lecture Notes in Computer Science, page 499-508. Springer, (2015)Analysis of the Geometry and Electric Properties of Brain Tissue in Simulation Models for Deep Brain Stimulation., , and . CIARP, volume 10125 of Lecture Notes in Computer Science, page 493-501. (2016)A Tucker decomposition process for probabilistic modeling of diffusion magnetic resonance imaging., , and . CoRR, (2016)Multi-task learning for subthalamic nucleus identification in deep brain stimulation., , and . Int. J. Machine Learning & Cybernetics, 9 (7): 1181-1192 (2018)Non-stationary Generalized Wishart Processes for Enhancing Resolution over Diffusion Tensor Fields., , , , and . ISVC, volume 11241 of Lecture Notes in Computer Science, page 371-381. Springer, (2018)NEURONAV: A Tool for Image-Guided Surgery - Application to Parkinson's Disease., , , , , , and . ISVC (1), volume 9474 of Lecture Notes in Computer Science, page 349-358. Springer, (2015)Gaussian Processes for Slice-Based Super-Resolution MR Images., , , , , and . ISVC (2), volume 9475 of Lecture Notes in Computer Science, page 692-701. Springer, (2015)