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Proceedings Paper

Automated segmentation of three-dimensional MR brain images
Author(s): Jonggeun Park; Byungjun Baek; Choong-Il Ahn; Kyo Bum Ku; Dong Kyun Jeong; Chulhee Lee
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Paper Abstract

Brain segmentation is a challenging problem due to the complexity of the brain. In this paper, we propose an automated brain segmentation method for 3D magnetic resonance (MR) brain images which are represented as a sequence of 2D brain images. The proposed method consists of three steps: pre-processing, removal of non-brain regions (e.g., the skull, meninges, other organs, etc), and spinal cord restoration. In pre-processing, we perform adaptive thresholding which takes into account variable intensities of MR brain images corresponding to various image acquisition conditions. In segmentation process, we iteratively apply 2D morphological operations and masking for the sequences of 2D sagittal, coronal, and axial planes in order to remove non-brain tissues. Next, final 3D brain regions are obtained by applying OR operation for segmentation results of three planes. Finally we reconstruct the spinal cord truncated during the previous processes. Experiments are performed with fifteen 3D MR brain image sets with 8-bit gray-scale. Experiment results show the proposed algorithm is fast, and provides robust and satisfactory results.

Paper Details

Date Published: 15 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61444R (15 March 2006); doi: 10.1117/12.655532
Show Author Affiliations
Jonggeun Park, Yonsei Univ. (South Korea)
Byungjun Baek, Yonsei Univ. (South Korea)
Choong-Il Ahn, INFINITT Co. Ltd. (South Korea)
Kyo Bum Ku, INFINITT Co. Ltd. (South Korea)
Dong Kyun Jeong, INFINITT Co. Ltd. (South Korea)
Chulhee Lee, Yonsei Univ. (South Korea)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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