Voxel-wise Comparison with a-contrario Analysis for Automated Segmentation of Multiple Sclerosis Lesions from Multimodal MRI

Francesca Galassi 1, * Olivier Commowick 1 Emmanuel Vallee 2 Christian Barillot 1, *
* Auteur correspondant
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U1228, Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : We introduce a new framework for the automated and un-supervised segmentation of Multiple Sclerosis lesions from multimodal Magnetic Resonance images. It relies on a voxel-wise approach to detect local white matter abnormalities, with an a-contrario analysis, which takes into account local information. First, a voxel-wise comparison of multimodal patient images to a set of controls is performed. Then, region-based probabilities are estimated using an a-contrario approach. Finally, correction for multiple testing is performed. Validation was undertaken on a multi-site clinical dataset of 53 MS patients with various number and volume of lesions. We showed that the proposed framework outperforms the widely used FDR-correction for this type of analysis, particularly for low lesion loads.
Type de document :
Communication dans un congrès
MICCAI BrainLes 2018 workshop, Sep 2018, Granada, Spain. pp.1-10, Lecture Notes in Computer Science
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http://www.hal.inserm.fr/inserm-01888928
Contributeur : Francesca Galassi <>
Soumis le : vendredi 5 octobre 2018 - 14:41:55
Dernière modification le : jeudi 15 novembre 2018 - 11:59:00

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  • HAL Id : inserm-01888928, version 1

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Francesca Galassi, Olivier Commowick, Emmanuel Vallee, Christian Barillot. Voxel-wise Comparison with a-contrario Analysis for Automated Segmentation of Multiple Sclerosis Lesions from Multimodal MRI. MICCAI BrainLes 2018 workshop, Sep 2018, Granada, Spain. pp.1-10, Lecture Notes in Computer Science. 〈inserm-01888928〉

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