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Communication Dans Un Congrès Année : 2018

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

Résumé

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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Dates et versions

inserm-01888928 , version 1 (05-10-2018)

Identifiants

Citer

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.180-188, ⟨10.1007/978-3-030-11723-8_18⟩. ⟨inserm-01888928⟩
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