Attribute-filtering and knowledge extraction for vessel segmentation - Université de Reims Champagne-Ardenne
Communication Dans Un Congrès Année : 2010

Attribute-filtering and knowledge extraction for vessel segmentation

Résumé

Attribute-filtering, relying on the notion of component-tree, enables to process grey-level images by taking into account high-level a priori knowledge. Based on these notions, a method is proposed for automatic segmentation of vascular structures from phase-contrast magnetic resonance angiography. Experiments performed on 16 images and validations by comparison to results obtained by two human experts emphasise the relevance of the method.
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Dates et versions

hal-01695035 , version 1 (03-03-2018)

Identifiants

Citer

Benoît Caldairou, Nicolas Passat, Benoît Naegel. Attribute-filtering and knowledge extraction for vessel segmentation. International Symposium on Visual Computing (ISVC), 2010, Las Vegas, United States. pp.13-22, ⟨10.1007/978-3-642-17289-2_2⟩. ⟨hal-01695035⟩
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