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Multiparametric Non-Negative Matrix Factorization for Longitudinal Variations Detection in White-Matter Fiber Bundles.

, , , , , and . IEEE J. Biomed. Health Informatics, 21 (5): 1393-1402 (2017)

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A Comparison of Machine Learning Approaches for Classifying Multiple Sclerosis Courses Using MRSI and Brain Segmentations., , , , , , and . ICANN (2), volume 10614 of Lecture Notes in Computer Science, page 643-651. Springer, (2017)A Graph Based Classification Method for Multiple Sclerosis Clinical Forms Using Support Vector Machine., , , , and . MLMMI@ICML, volume 9487 of Lecture Notes in Computer Science, page 57-64. Springer, (2015)A Model-Guided String-Based Approach to White Matter Fiber-Bundles Extraction., , , , , and . BIH, volume 9250 of Lecture Notes in Computer Science, page 135-144. Springer, (2015)A longitudinal model for variations detection in white matter fiber-bundles., , , , , , , and . IWSSIP, page 57-60. IEEE, (2015)Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks., , , , , , and . EMBC, page 2087-2090. IEEE, (2019)Multiparametric Non-Negative Matrix Factorization for Longitudinal Variations Detection in White-Matter Fiber Bundles., , , , , and . IEEE J. Biomed. Health Informatics, 21 (5): 1393-1402 (2017)