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MICCAI
2009
Springer

Multiple Sclerosis Lesion Segmentation Using an Automatic Multimodal Graph Cuts

10 years 1 months ago
Multiple Sclerosis Lesion Segmentation Using an Automatic Multimodal Graph Cuts
Abstract. 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.
Daniel García-Lorenzo, Jérémy
Added 05 Mar 2010
Updated 08 Mar 2010
Type Conference
Year 2009
Where MICCAI
Authors Daniel García-Lorenzo, Jérémy Lecoeur, Douglas L. Arnold, D. Louis Collins, Christian Barillot
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