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서지반출
Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing
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  • Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing
  • Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing
저자명
Mun. Kyeong-Jun,Kang. Hyeon-Tae,Lee. Hwa-Seok,Yoon. Yoo-Sool,Lee. Chang-Moon,Park. June-Ho
간행물명
International Journal of Control, Automation and Systems
권/호정보
2004년|2권 1호|pp.100-106 (7 pages)
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제어로봇시스템학회
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정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.