Title :
3-D segmentation of MR brain images using seeded region growing
Author :
Justice, R. Kyle ; Stokely, Ernest M.
Author_Institution :
Dept. of Biomed. Eng., Alabama Univ., Birmingham, AL, USA
fDate :
31 Oct-3 Nov 1996
Abstract :
A simple yet accurate method for segmenting magnetic resonance (MR) brain images has been implemented. The semi-automatic technique carries out region growing in all three dimensions guided by initial seed points. Seed voxels may be specified interactively with a mouse or automatically through the selection of intensity thresholds. The 3-D seeded region growing (3-D SRG) algorithm offers significant advantages for MR brain segmentation, particularly in terms of speed and flexibility
Keywords :
biomedical NMR; brain; image segmentation; medical image processing; 3D segmentation; MRI brain images; flexibility; global histogram analysis; image segmentation; initial seed points; seed voxels; seeded region growing; selection of intensity thresholds; semi-automatic technique; Biomedical engineering; Brain; Data mining; Data visualization; Histograms; Image segmentation; Magnetic resonance; Mice; Rendering (computer graphics); Robustness;
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.1996.652719
