Influence of the Training Library Composition on a Patch-based label fusion method: Application to Hippocampus Segmentation on ADNI dataset.

Pierrick Coupé 1, * Vladimir Fonov 1 Simon Eskildsen 1, 2 José Manjón 3 Douglas Arnold 1 Louis Collins 1
* Auteur correspondant
1 MNI - McConnell Brain Imaging Centre
2 AAU - Aalborg University [Denmark]
3 ITACA
Abstract : The atrophy of medial temporal lobe structures is may serve as early biomarkers of Alzheimer's disease. The evaluation of hippocampus (HC) atrophy is estimated by volumetric studies requiring a segmentation step that can be very time consuming when done manually. This limitation can be overcome by using automatic segmentation methods. In this study, we propose to validate our nonlocal patch-based method on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database by segmenting the HC of Cognitively Normal (CN) subjects and patients with early Alzheimer's Disease (AD).
Keywords : Alzheimer's disease hippocmapus segmentation brain neuroimaging nonlocal means
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Communication dans un congrès
Alzheimer's Association International Conference, Jul 2011, France. 7 (4), pp.S24, 2011
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https://hal.archives-ouvertes.fr/hal-00645526
Contributeur : Pierrick Coupé <>
Soumis le : mardi 3 janvier 2012 - 00:16:13
Dernière modification le : mardi 24 avril 2018 - 16:16:02
Document(s) archivé(s) le : mercredi 4 avril 2012 - 02:21:00

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  • HAL Id : hal-00645526, version 1

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Pierrick Coupé, Vladimir Fonov, Simon Eskildsen, José Manjón, Douglas Arnold, et al.. Influence of the Training Library Composition on a Patch-based label fusion method: Application to Hippocampus Segmentation on ADNI dataset.. Alzheimer's Association International Conference, Jul 2011, France. 7 (4), pp.S24, 2011. 〈hal-00645526〉

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