Automated brain segmentation algorithm for 3D magnetic resonance brain images

Jong Geun Park, Taeuk Jeong, Chulhee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a new brain segmentation method for 3D magnetic resonance (MR) brain images. The proposed method consists of four steps: background rejection, image normalization, initial slice segmentation, and brain segmentation. In the image normalization step, intensity non-uniformity is removed. In the brain segmentation step, we use mathematical morphological operators and masking. The proposed algorithm was tested with twenty 3D MR normal brain image sets. Experiment results showed the proposed algorithm is fast and provides robust and satisfactory results.

Original languageEnglish
Title of host publication2nd IEEE International Workshop on Soft Computing Applications Proceedings, SOFA 2007
Pages57-61
Number of pages5
DOIs
Publication statusPublished - 2007
Event2nd IEEE International Workshop on Soft Computing Applications, SOFA 2007 - Oradea, Romania
Duration: 2007 Aug 212007 Aug 23

Publication series

NameSOFA 2007 - 2nd IEEE International Workshop on Soft Computing Applications Proceedings

Other

Other2nd IEEE International Workshop on Soft Computing Applications, SOFA 2007
CountryRomania
CityOradea
Period07/8/2107/8/23

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software

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  • Cite this

    Park, J. G., Jeong, T., & Lee, C. (2007). Automated brain segmentation algorithm for 3D magnetic resonance brain images. In 2nd IEEE International Workshop on Soft Computing Applications Proceedings, SOFA 2007 (pp. 57-61). [4318305] (SOFA 2007 - 2nd IEEE International Workshop on Soft Computing Applications Proceedings). https://doi.org/10.1109/SOFA.2007.4318305