inria-00073125, version 1
Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis
David Rey 1Gérard SubsolHervé Delingette
Nicholas Ayache
N° RR-3559 (1998)
Résumé : Physicians often perform diagnoses based on the evolution of lesions, tumors or anatomical structures through time. The objective of this report is to automatically detect regions with apparent local volume variation with a vector field operator applied to the local displacement field obtained after a non-rigid registration between successive temporal images. In studying the information of apparent shrinking areas in the direct and reverse displacement fields between images, we are able to segment evolving lesions. Then we propose a method to segment lesions in a whole temporal series of images. In this report we apply this approach to the automatic detection and segmentation of multiple sclerosis lesions in time series of MRI images of the brain.
- 1 : EPIDAURE (INRIA Sophia Antipolis)
- INRIA
- Domaine : Informatique/Autre
- Mots-clés : 3D MEDICAL IMAGING / AUTOMATIC DETECTION AND SEGMENTATION / EVOLVING PROCESSES / VECTOR FIELD ANALYSIS / VECTOR FIELD OPERATOR / MULTIPLE SCLEROSIS
- Référence interne : RR-3559
- inria-00073125, version 1
- http://hal.inria.fr/inria-00073125
- oai:hal.inria.fr:inria-00073125
- Contributeur : Rapport De Recherche Inria
- Soumis le : Mercredi 24 Mai 2006, 11:56:02
- Dernière modification le : Mercredi 31 Mai 2006, 14:24:27






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