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Anatomical-driven segmentation of the 3rd and 4th ventricles in MR data

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2 Author(s)
Chun Dong ; Dept. of Comput. Sci., Alabama Univ., Huntsville, AL, USA ; Newman, T.S.

A method for automatic segmentation of the brain's 3rd and 4th ventricles in MRI (magnetic resonance imaging) datasets is introduced. The method exploits anatomical knowledge about these structures and uses gradient-based edge detection and volume-growing to complete the segmentation. Nearby anatomic landmarks, including the longitudinal fissure, cerebellum and callosum are also automatically extracted in our approach. The method has been tested on a variety of T1- and T2- weighted MR images

Published in:

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint  (Volume:2 )

Date of Conference:

Oct 1999

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