inria-00423040, version 1
Multiple Sclerosis lesion segmentation using an automatic multimodal Graph Cuts
Daniel García-Lorenzo
a, 1Jérémy Lecoeur
a, 1Douglas L. Arnold 2D. Louis Collins 2Christian Barillot
b, 1
12th International Conference on Medical Image Computing and Computer Assisted Intervention 5762 (2009) 584-591
Résumé : Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains.We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed in synthetic and real images showing good agreement between the automatic segmentation and the target segmentation. We compare our algorithm with the state of the art techniques and with several manual segmentations. An advantage of our algorithm over previously published ones is the possibility to semi-automatically improve the segmentation due to the Graph Cuts interactive feature.
- a – INRIA
- b – CNRS
- 1 : VISAGES : Vision Action et Gestion d'Informations en Santé (VISAGES)
- INSERM : U746 – CNRS : UMR6074 – INRIA – Université de Rennes 1
- 2 : Montreal Neurological Institute
- McGill University
- Domaine : Informatique/Imagerie médicale
Informatique/Traitement des images
Informatique/Bio-informatique
Sciences du Vivant/Bio-Informatique, Biologie Systémique
- inria-00423040, version 1
- http://hal.inria.fr/inria-00423040
- oai:hal.inria.fr:inria-00423040
- Contributeur : Jérémy Lecoeur
- Soumis le : Vendredi 22 Janvier 2010, 10:35:05
- Dernière modification le : Mardi 8 Février 2011, 20:53:48






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