Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/802812
- Title
- Interactive and intelligent approach for brain extraction from high-resolution volumetric MR neuroimages
- Author/Creator
-
Qian, Guoyu;
Luo, Suhuai;
Jin, Jesse S.;
Park, Mira;
Nowinski, Wieslaw L.
- Institution
- The University of Newcastle. Faculty of Science & Information Technology, School of Design, Communication and Information Technology
- Description
- This paper introduces an interactive and intelligent approach for accurate brain segmentation. A high resolution 3-Tesla magnetic resonance (MR) dataset was tested by state of the art automated algorithms as well as segmented by making use of the proposed interactive tools. The results show that the automated algorithms gave an incomplete or anatomically incorrect brain surface. About 4% false positive and 10% false negative error rates were reported by evaluating three automated methods. The proposed approach improved the quality and accuracy of the segmented results.
- Relation
- Second International Symposium on Intelligent Information Technology Application, 2008 (IITA '08). Proceedings: 2008 International Symposium on Intelligent Information Technology Application: IITA 2008 (Shanghai, China 21-22 December, 2008) p. 885-889
- Publisher Link
- http://dx.doi.org/10.1109/IITA.2008.542
- Date
- 2008
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Keyword(s)
-
brain extraction;
brain segmentation;
image resolution;
magnetic resonance dataset;
volumetric MR neuroimages
- Resource Type
- conference paper
- Rights
- Copyright © 2008 IEEE. Reprinted from the Proceedings: 2008 International Symposium on Intelligent Information Technology Application: IITA 2008. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Identifier
- http://hdl.handle.net/1959.13/802812
- Identifier
- ISBN:9780769534978
- Reviewed
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