Journal
NEUROIMAGE
Volume 23, Issue -, Pages S85-S96Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2004.07.040
Keywords
magnetic resonance images; simplex mesh surfaces; 3-D segmentation system
Funding
- NATIONAL CENTER FOR RESEARCH RESOURCES [R21RR019771] Funding Source: NIH RePORTER
- NCRR NIH HHS [R21 RR19771] Funding Source: Medline
- NIBIB NIH HHS [EB01651] Funding Source: Medline
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We describe an automated 3-D segmentation system for in vivo brain magnetic resonance images (MRI). Our segmentation method combines a variety of filtering, segmentation, and registration techniques and makes maximum use of the available a priori biomedical expertise, both in an implicit and an explicit form. We approach the issue of boundary finding as a process of fitting a group of deformable templates (simplex mesh surfaces) to the contours of the target structures. These templates evolve in parallel, supervised by a series of rules derived from analyzing the template's dynamics and from medical experience. The templates are also constrained by knowledge on the expected textural and shape properties of the target structures. We apply our system to segment four brain structures (corpus callosum, ventricles, hippocampus, and caudate nuclei) and discuss its robustness to imaging characteristics and acquisition noise. (C) 2004 Elsevier Inc. All rights reserved.
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