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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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Tensor Based Blind Source Separation in Longitudinal Magnetic Resonance Imaging Analysis., , , and . EMBC, page 3879-3883. IEEE, (2019)Constrained Tensor Decomposition for Longitudinal Analysis of Diffusion Imaging Data., , , and . IEEE J. Biomed. Health Informatics, 24 (4): 1137-1148 (2020)Classification of multiple sclerosis lesion evolution patterns a study based on unsupervised clustering of asynchronous time-series., , , , and . ISBI, page 1315-1319. IEEE, (2016)A longitudinal model for variations detection in white matter fiber-bundles., , , , , , , and . IWSSIP, page 57-60. IEEE, (2015)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)White Matter Fiber-Bundle Analysis Using Non-negative Tensor Factorization., , , , and . ICIAR, volume 9730 of Lecture Notes in Computer Science, page 650-657. Springer, (2016)A More Interpretable Classifier For Multiple Sclerosis., , , , and . ISBI, page 1062-1066. IEEE, (2021)Longitudinal Neuroimaging Analysis Using Non-Negative Matrix Factorization., , , and . SITIS, page 55-61. IEEE Computer Society, (2016)