Earticle

초록

영어

Object recognition is usually processed based on region segmentation algorithm. Region segmentation in the IT field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on Susceptibility Weighted Imaging (SWI) within the magnetic resonance (MR) theory. When we do pre-processing, proposed method was composed of SWI process. And then we do the Gray-white matter segmentation by Active Contour Model(ACM) in post-processing. In this study, the experiment had been conducted using images including the brain region and by getting up contrast enhancement image of SWI for segmentation to extract region (white matter) segmentation even when the border line was not clear. As a result, an average area difference of 8.2%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained.

목차

Abstract
 1. Introduction
 2. Proposed Method
  2.1. Susceptibility Weighted Imaging (SWI)
  2.2. Gray-white Matter Segmentation by ACM
 3. Experiment
 3. Conclusion
 Acknowledgement
 References

키워드

저자

• Eun-Young Jung [ u-Healthcare Center, Gachon University Gil Medical Center ]
• Sung-Jong Eun [ Department of Computer Science Gachon University ]
• Dong Kyun Park [ u-Healthcare Center, Gachon University Gil Medical Center ] corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605