NDLI: First results of an automated model-based segmentation system for subcortical structures in human brain MRI data

Content Provider	IEEE Xplore Digital Library
Author	Belitz, H. Rohr, K. Muller, H. Wagenknech, G.
Copyright Year	2006
Description	Author affiliation: Central Inst. for Electron., Res. Center Julich (Belitz, H.)
Abstract	We propose an automated model-based approach for segmenting subcortical structures, especially the basal ganglia, from 3D human brain MRI images. Our hybrid approach combines an automatic tissue classification scheme, a landmark detection algorithm and a discrete active surface model (ASM) to achieve its goal. A priori knowledge is incorporated into the different stages of the model and is used to retain shape and neighborhood information about the structures of interest throughout the segmentation process. The system is designed to require as little user interaction as possible. Sample results are given for the Brain Web simulated brain data set and for a real data set
Starting Page	402
Ending Page	405
File Size	294882
Page Count	4
File Format	PDF
ISBN	078039576X
DOI	10.1109/ISBI.2006.1624938
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain modeling Humans Magnetic resonance imaging Image segmentation Shape Basal ganglia Deformable models Topology Hybrid intelligent systems Intelligent structures
Content Type	Text
Resource Type	Article

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First results of an automated model-based segmentation system for subcortical structures in human brain MRI data