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Communication Dans Un Congrès Année : 2016

Classification of multiple sclerosis lesion evolution patterns a study based on unsupervised clustering of asynchronous time-series

Simon Mure
  • Fonction : Auteur
Thomas Grenier
Hugues Benoit-Cattin

Résumé

Based on weekly up to monthly follow-up of MS patients over one year with T2-weighted magnetic resonance images, a new clustering scheme is proposed to automatically identify lesions sharing similar temporal behaviors. The proposed method, based on spatiotemporal mean-shift and dynamic time warping, allows to detect intra and inter-patient similarities in lesion evolution patterns, which provides a quantitative approach towards the understanding of lesion evolution heterogeneity.
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Dates et versions

hal-01432982 , version 1 (12-01-2017)

Identifiants

Citer

Simon Mure, Thomas Grenier, Charles R G Guttmann, François Cotton, Hugues Benoit-Cattin. Classification of multiple sclerosis lesion evolution patterns a study based on unsupervised clustering of asynchronous time-series. IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016), Apr 2016, Prague, Czech Republic. ⟨10.1109/ISBI.2016.7493509⟩. ⟨hal-01432982⟩
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