NDLI: A 3-D deformable surface method for automatic hippocampus-amygdala complex segmentation

Content Provider	IEEE Xplore Digital Library
Author	Karimi, M.M. Batmanghelich, N. Soltanian-Zadeh, H. Lucas, C.
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Tehran Univ., Iran (Karimi, M.M.)
Abstract	In this paper, we propose an atlas-based method for hippocampus-amygdala complex segmentation. An atlas is registered on all subjects and its transformation is calculated for each subject. This transformation is applied to the structural segmentation of the complex in atlas to construct an initial surface for the hippocampus-amygdala complex of each subject. A possibility approach is introduced for the segmentation process. Two different kinds of deformation based on edges and information obtained from tissue segmentation are used to find different parts of the complex. A new energy is defined to use tissue information. This energy is adopted to expand the model to embed dominant gray matter points in the volume and also withdraw from dominant white matter and CSF points. The initial shape is divided into several parts. In the normal direction of the center of each part, we construct a profile which search for the best point that maximizes this new energy. This algorithm is reliable for finding the overall shape of the complex. It overcomes the poor features of the complex such as weak edges and noise. The algorithm is examined on 5 different subjects and validated using two different validation methods.
Starting Page	3725
Ending Page	3729
File Size	712975
Page Count	5
File Format	PDF
ISBN	0780387007
ISSN	10823654
e-ISBN	0780387015
DOI	10.1109/NSSMIC.2004.1466690
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-10-16
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hippocampus Process control Intelligent control Shape Intelligent structures Physics Mathematics Image segmentation Noise shaping Helium
Content Type	Text
Resource Type	Article

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