Multiple Sclerosis Lesions Segmentation using Spectral Gradient and Graph Cuts

Jérémy Lecoeur 1, * Sean Patrick Morrissey 1 Jean-Christophe Ferré 2 Douglas Arnold 3 D. Louis Collins 3 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 present a new tool for segmenting multiple sclerosis lesions that can take advantage of the complementary modalities we usually use for this purpose. Based on the integration of multi channel information in a scale-space paradigm, its optimization by graph cuts provides a powerful and accurate tool. After presenting the mathematical and physical background on which is based the spectral gradient, we introduce its computational optimization by the graph cuts approach. The validation on synthetic and real data shows both its accuracy and reliability on different sets of standard MRI of sequences.
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Submitted on : Friday, October 17, 2008 - 3:46:45 PM
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Jérémy Lecoeur, Sean Patrick Morrissey, Jean-Christophe Ferré, Douglas Arnold, D. Louis Collins, et al.. Multiple Sclerosis Lesions Segmentation using Spectral Gradient and Graph Cuts. Medical Image Analysis on Multiple Sclerosis (validation and methodological issues), Sep 2008, New York City, United States. ⟨inria-00323042⟩

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