Difference between revisions of "TIBM: Segmentation"
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* A multi-atlas segmentation framework based on patch fusion has been proposed for parcellating both the cortex and the deep brain structures [https://icube-publis.unistra.fr/2-RHS11 2-RHS11]. | * A multi-atlas segmentation framework based on patch fusion has been proposed for parcellating both the cortex and the deep brain structures [https://icube-publis.unistra.fr/2-RHS11 2-RHS11]. | ||
− | * In the context of the [http://icube-vivabrain.unistra.fr/index.php/Main_Page ANR Vivabrain], a method based on component-trees has been set | + | * In the context of the [http://icube-vivabrain.unistra.fr/index.php/Main_Page ANR Vivabrain], a method based on component-trees has been set up to segment the cerebral vascular tree [https://icube-publis.unistra.fr/2-DTNT13 2-DTNT13]. |
* Specific and original algorithms have also been developed in the project [http://icube-miv.unistra.fr/fr/index.php/ERC_FBrain FBrain ERC] for segmenting brain tissues from the fetal MRI [https://icube-publis.unistra.fr/2-RHS11 2-RHS11], [https://icube-publis.unistra.fr/2-CPHS11 2-CPHS11], [https://icube-publis.unistra.com/2-PNRK11 2-PNRK11]. | * Specific and original algorithms have also been developed in the project [http://icube-miv.unistra.fr/fr/index.php/ERC_FBrain FBrain ERC] for segmenting brain tissues from the fetal MRI [https://icube-publis.unistra.fr/2-RHS11 2-RHS11], [https://icube-publis.unistra.fr/2-CPHS11 2-CPHS11], [https://icube-publis.unistra.com/2-PNRK11 2-PNRK11]. | ||
* Finally, Markov approaches have been implemented for the automatic identification of multiple sclerosis lesions in multimodal [https://icube-publis.unistra.fr/2-BCA14 2-BCA14] and temporal [https://icube-publis.unistra.fr/4-LCA14 4-LCA14] MRI sequences. | * Finally, Markov approaches have been implemented for the automatic identification of multiple sclerosis lesions in multimodal [https://icube-publis.unistra.fr/2-BCA14 2-BCA14] and temporal [https://icube-publis.unistra.fr/4-LCA14 4-LCA14] MRI sequences. |
Revision as of 11:09, 10 October 2016
This research topic gathers all contributions related to the automatic extraction of anatomical or functional structures from biomedical images.
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PhD thesis
- T. Kensicher, Protocole d'extraction de caractéristiques dans une base de données de scanners angiographiques pour la prédiction de complications post-opérative après des opérations de type EVAR, en cours
- A. Dufour, Segmentation et modélisation des structures vasculaires cérébrales en imagerie médicale 3D, octobre 2013
- B. Caldairou, Contribution à la segmentation des structures cérébrales en IRM foetale, juin 2012
- B. Bouraoui, Segmentation automatique de l'arbre coronarien à partir d'images angiographiques 3D+t de scanner, octobre 2009
- S. Bricq, Segmentation d'images IRM anatomiques multimodales et détection de lésions de sclérose en plaques, novembre 2008
- J. Lamy, Calcul du chemin central du côlon pour une analyse locale des pathologies, novembre 2005
- N. Passat, Contribution à la segmentation des réseaux vasculaires cérébraux obtenus en IRM. Intégration de connaissance anatomique pour le guidage d'outils de morphologie mathématique, septembre 2005
- B. Naegel, Segmentation des organes de l'abdomen par des critères topologiques et morphologiques, octobre 2004