1 - Brain tumor vascular network segmentation from micro-tomography.
X. Descombes et F. Plouraboue et El Boustani Habdelhkim et Fonta Caroline et |LeDuc Geraldine et Serduc Raphael et Weitkamp Timm. Dans Internation Symposium of Biomedical Imaging (ISBI), Chicago, USA, avril 2011.
Mots-clés : Segmentation, Markov random field, Tomography, Brain, vascular network.
Copyright : IEEE
@INPROCEEDINGS{isbi11,
|
| author |
= |
{Descombes, X. and Plouraboue, F. and Boustani Habdelhkim, El and Caroline, Fonta and Geraldine, |LeDuc and Raphael, Serduc and Timm, Weitkamp}, |
| title |
= |
{Brain tumor vascular network segmentation from micro-tomography}, |
| year |
= |
{2011}, |
| month |
= |
{avril}, |
| booktitle |
= |
{Internation Symposium of Biomedical Imaging (ISBI)}, |
| address |
= |
{Chicago, USA}, |
| url |
= |
{http://dx.doi.org/10.1109/ISBI.2011.5872596}, |
| keyword |
= |
{Segmentation, Markov random field, Tomography, Brain, vascular network} |
| } |
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. |
|
haut de la page
Nouvelle page de démos
bibtex
