STREM: a robust multidimensional parametric method to segment MS lesions in MRI.: STREM: A Robust Multidimensional Parametric Method to Segment MS Lesions in MRI

Laure Aït-Ali 1, * Sylvain Prima 1 Pierre Hellier 1 Béatrice Carsin 2 Gilles Edan 2 Christian Barillot 1
* Corresponding author
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : We propose to segment Multiple Sclerosis (MS) lesions overtime in multidimensional Magnetic Resonance (MR) sequences. We use a robust algorithm that allows the segmentation of the abnormalities using the whole time series simultaneously and we propose an original rejection scheme for outliers. We validate our method using the BrainWeb simulator. To conclude, promising preliminary results on longitudinal multi-sequences of clinical data are shown.
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Conference papers
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https://www.hal.inserm.fr/inserm-00137568
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Submitted on : Tuesday, March 20, 2007 - 3:48:00 PM
Last modification on : Tuesday, March 5, 2019 - 1:45:45 AM

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Laure Aït-Ali, Sylvain Prima, Pierre Hellier, Béatrice Carsin, Gilles Edan, et al.. STREM: a robust multidimensional parametric method to segment MS lesions in MRI.: STREM: A Robust Multidimensional Parametric Method to Segment MS Lesions in MRI. MICCAI 2005, Oct 2005, Palm Springs, United States. pp.409-16, ⟨10.1007/11566465_51⟩. ⟨inserm-00137568⟩

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