Difference between revisions of "TIBM: Change detection and prediction"
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* or the geometry of the white matter fiber bundles [https://icube-publis.unistra.fr/2-GNBH13 2-GNBH13]. | * or the geometry of the white matter fiber bundles [https://icube-publis.unistra.fr/2-GNBH13 2-GNBH13]. | ||
− | In addition, work has focused on the temporal modeling of brain maturation [https://icube-publis.unistra.fr/5-PRSS12 5-PRSS12] and gyrification [https: //icube-publis.unistra.fr/2-PRSK16 2-PRSK16] in the project [[ERC_FBrain | ERC FBrain]]. | + | In addition, work has focused on the temporal modeling of brain maturation [https://icube-publis.unistra.fr/5-PRSS12 5-PRSS12] and gyrification [https://icube-publis.unistra.fr/2-PRSK16 2-PRSK16] in the project [[ERC_FBrain | ERC FBrain]]. |
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Revision as of 16:34, 7 October 2016
Automatic change detection is a tool with great potential to monitor evolving pathologies. The aim is is to identify changes over time between two examinations of a given subject. This may allow a better care of the patient (personalized medicine), either for diagnosis, prognosis or evaluation of therapeutic response. Thus, novel methods have been developed to analyze longitudinal diffusion MRI sequences:
In addition, work has focused on the temporal modeling of brain maturation 5-PRSS12 and gyrification 2-PRSK16 in the project ERC FBrain. |
PhD thesis
- C. Heimburger, Evaluation précoce de la croissance tumorale des résidus post-chirurgicaux des glioblastomes par IRM-ITD., en cours
- J. Pontabry, Construction d'atlas en IRM de diffusion : application à l'étude de la maturation cérébrale, octobre 2013
- A. Grigis, Approches statistiques pour la détection de changements en IRM de diffusion. Application au suivi longitudinal de pathologies neurodégénératives, septembre 2012
- H. Boisgontier, Détection automatique de changements en IRM de diffusion. Application à la sclérose en plaques, juin 2010
- M. Bosc, Contribution à la détection de changements dans des séquences IRM 3D multimodales, décembre 2003