Title :
3D MRI segmentation of brain structures
Author :
Vérard, Laurent ; Fadili, Jalal ; Ruan, Su ; Bloyet, Daniel
Author_Institution :
CNRS, Caen, France
fDate :
31 Oct-3 Nov 1996
Abstract :
Some complex applications in medical imaging require to combine results coming from different numerical operators referred as to edges-and regions-detectors. Combining “static” contours and regions methods, named cooperative methods, takes advantage of these two compatible segmentation results. To improve success of segmentation, we propose the idea of combining region and active contour segmentations. In a first step, we use tools from mathematical morphology and region growing algorithm for the region segmentation in order to get the automated initialisation of the active contour model. In the second step, the physically-based active model considers the contour undergoing an elastic deformation as a set of masses linked by springs and converging to an equilibrium state. Segmentation results are shown on cerebellum, brain stem and hemispheres on 3D MRI data sets
Keywords :
biomedical NMR; brain; image segmentation; mathematical morphology; medical image processing; 3D MRI segmentation; active contour segmentation; automated initialisation; brain stem; brain structures; cerebellum; compatible segmentation; cooperative methods; equilibrium state; hemispheres; masses linked by springs; mathematical morphology; medical imaging; numerical operators; physically-based active model; region growing algorithm; region segmentation; regions methods; static contours; Active contours; Biomedical imaging; Brain modeling; Deformable models; Detectors; Image edge detection; Image segmentation; Magnetic resonance imaging; Shape; Springs;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.652718