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.
Domaines
Ingénierie biomédicale
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GalassiFrancesca_brainLes_Miccai2018.pdf (684.91 Ko)
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| Origine | Fichiers produits par l'(les) auteur(s) |
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| Format | Figure, Image |
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| Origine | Fichiers produits par l'(les) auteur(s) |
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