Abstract : Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We define and use a conditional random field for segmenting the output of a watershed algorithm. The tumoral and normal classes are thus characterized by their respective distribution of watershed region size interpreted as local vascular territories.
Type de document :
Communication dans un congrès
ISBI - International Symposium on Biomedical Imaging, 2011, Chicago, United States. IEEE, pp.1113 - 1116, 2011, Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. 〈10.1109/ISBI.2011.5872596〉
https://hal.inria.fr/hal-00793687
Contributeur : Xavier Descombes
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Soumis le : vendredi 22 février 2013 - 17:50:57
Dernière modification le : mercredi 19 avril 2017 - 01:09:44
Xavier Descombes, Franck Plouraboue, Habdelhakim Boustani, Caroline Fonta, Geraldine Leduc, et al.. Brain tumor vascular network segmentation from micro-tomography. ISBI - International Symposium on Biomedical Imaging, 2011, Chicago, United States. IEEE, pp.1113 - 1116, 2011, Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. 〈10.1109/ISBI.2011.5872596〉. 〈hal-00793687〉
