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Publications of F. Plouraboue
Result of the query in the list of publications :
Article |
1 - Gap Filling of 3-D Microvascular Networs by Tensor Voting.
L. Risser and F. Plouraboue and X. Descombes. IEEE Trans. Medical Imaging, 27(5): pages 674-687, May 2008.
Copyright :
@ARTICLE{xavTMI3,
|
| author |
= |
{Risser, L. and Plouraboue, F. and Descombes, X.}, |
| title |
= |
{Gap Filling of 3-D Microvascular Networs by Tensor Voting}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| journal |
= |
{IEEE Trans. Medical Imaging}, |
| volume |
= |
{27}, |
| number |
= |
{5}, |
| pages |
= |
{674-687}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/42/4497376/04389807.pdf?isnumber=4497376&prod=JNL&arnumber=4389807&arSt=674&ared=687&arAuthor=Risser%2C+L.%3B+Plouraboue%2C+F.%3B+Descombes%2C+X.}, |
| keyword |
= |
{} |
| } |
|
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3 Conference articles |
1 - Extraction et caractérisation de régions saines et pathologiques à partir de micro-tomographie RX du système vasculaire cérébral.
X. Descombes and A. Gamal Eldin and F. Plouraboue and C. Fonta and S. Serduc and G. Le Duc and T. Weitkamp. In Proc. GRETSI Symposium on Signal and Image Processing, Bordeaux, France, September 2011.
@INPROCEEDINGS{XavierGRETSI11,
|
| author |
= |
{Descombes, X. and Gamal Eldin, A. and Plouraboue, F. and Fonta, C. and Serduc, S. and Le Duc, G. and Weitkamp, T.}, |
| title |
= |
{Extraction et caractérisation de régions saines et pathologiques à partir de micro-tomographie RX du système vasculaire cérébral}, |
| year |
= |
{2011}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Bordeaux, France}, |
| url |
= |
{http://hal.inria.fr/inria-00625525/fr/}, |
| keyword |
= |
{} |
| } |
Abstract :
In this paper, we consider X-ray micro-tomography representing the brain vascular network. We define the local vascular territories as the regions obtained after a watershed algorithm applied on the distance map. The obtained graph is then regularized by a Markov random field approach. The optimization is performed using a graph cut algorithm. We show that the resulting segmentation exhibits three classes corresponding to normal tissue, tumour and an intermediate region. |
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2 - Brain tumor vascular network segmentation from micro-tomography.
X. Descombes and F. Plouraboue and El Boustani Habdelhkim and Fonta Caroline and |LeDuc Geraldine and Serduc Raphael and Weitkamp Timm. In Internation Symposium of Biomedical Imaging (ISBI), Chicago, USA, April 2011.
Keywords : 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 |
= |
{April}, |
| 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. |
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3 - Gap Filling in 3D Vessel like Patterns with Tensor Fields.
L. Risser and F. Plouraboue and X. Descombes. In Proc. International Conference on Computer Vision Theory
and Applications, 2007.
Keywords : tensor voting, vascular network.
@INPROCEEDINGS{XDbarca1,
|
| author |
= |
{Risser, L. and Plouraboue, F. and Descombes, X.}, |
| title |
= |
{Gap Filling in 3D Vessel like Patterns with Tensor Fields}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. International Conference on Computer Vision Theory
and Applications}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_XDbarca1.pdf}, |
| keyword |
= |
{tensor voting, vascular network} |
| } |
|
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