The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Automatic segmentation of magnetic resonance images using error back-propagation algorithm

오류 역전파 알고리즘을 이용한 자기 공명 영상 자동 세그멘테이션

  • 최재호 (조선대학교 대학원 컴퓨터공학과) ;
  • 조범준 (조선대학교 공과대학 컴퓨터공학과)
  • Published : 1997.11.01
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Abstract

The increased usage of Magnetic Resonance Image (MRI) required the method for automatic segmentation of medical image that is more useful so as to diagnose the dissecitive information of a atient quickly and effectively through MR scans.The use of neural networks may give much hep to solving the complex problems concerned the matter. This paper proposes the new method for automatic segmentation of magnetic resonance (MR) images of the brain by using neural networks brained by back-propagation algorithm. The trained neural networks by the segmenting MR images of a patient produce an output that networks can segment MR images of the other patients automatically, too and show a clear image of the brain.

자기 공명 영상의 사용이 빈번해 짐에 따라 환자의 해부학적인 정확한 정보와 이를 빠르고 효과적으로 진단하는데 유용한 자동 영상 세그멘테이션 방법이 요구되고 있다. 본 논문에서는 오류 역전파 알고리즘으로 학습한 신경망을 이용하여 뇌의 자기 공명 영상을 자동적으로 세그멘테이션하는 방법을 제안한다. 특정 환자의 자기 공명 영상을 분할하여 학습시킨 신경망은 다른 환자의 자기 공명 영상도 자동적으로 세그멘테이션하여 뇌의 윤곽을 뚜렷하게 나타내었다.

Keywords

References

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