Neural Integration Approach for Subcortical Structure Segmentation

Author

Shichun, Peng ; Jian, Liu ; Guoping, Yan

Author_Institution

Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol.

Volume

1

fYear

2005

Firstpage

244

Lastpage

248

Abstract

A neural approach is presented to automatically segment subcortical brain structures from MR image. Spatial information from anatomy and tissue characteristics of the brain structures is employed in the method. The spatial locations of the structures are learned by an improved fuzzy neural approach. The decision of a particular voxel belonging to a particular structure, rendered by spatial and tissue characteristics information are combined by a fuzzy fusion algorithm. Experiments on an ensemble of MR brain scans show promise of the current approach

Keywords

biomedical MRI; brain; medical image processing; neural nets; fuzzy fusion algorithm; fuzzy neural approach; magnetic resonance images; neural integration approach; subcortical brain structures; subcortical structure segmentation; Anatomical structure; Anatomy; Brain modeling; Fuzzy logic; Fuzzy neural networks; Image segmentation; Magnetic noise; Rendering (computer graphics); Resonance; Shape; MR(magnetic resonance) image; Neural approach; fuzzy logic; information fusion; subcortical brain structures;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614607

Filename

1614607