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, *
* Corresponding author
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.
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Conference papers
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https://www.hal.inserm.fr/inserm-01888928
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Submitted on : Friday, October 5, 2018 - 2:41:55 PM
Last modification on : Monday, March 4, 2019 - 2:07:44 PM
Long-term archiving on : Sunday, January 6, 2019 - 5:41:15 PM

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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, Alessandro Crimi; Spyridon Bakas, Sep 2018, Granada, Spain. pp.1-10, ⟨10.1007/978-3-030-11723-8_18⟩. ⟨inserm-01888928⟩

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