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Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing  

Mun, Kyeong-Jun (School of Electrical Engineering, Pusan National University)
Kang, Hyeon-Tae (Korea Hydro and Nuclear Powe)
Lee, Hwa-Seok (School of Electrical Engineering, Koje Colleg)
Yoon, Yoo-Sool (School of Electrical Engineering, Pusan National University)
Lee, Chang-Moon (School of Electrical Engineering, Pusan National University)
Park, June-Ho (School of Electrical Engineering, Pusan National University)
Publication Information
International Journal of Control, Automation, and Systems / v.2, no.1, 2004 , pp. 100-106 More about this Journal
Abstract
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.
Keywords
Genetic algorithm; image preprocessing; object contour detection; wavelet.;
Citations & Related Records

Times Cited By Web Of Science : 2  (Related Records In Web of Science)
Times Cited By SCOPUS : 4
연도 인용수 순위
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[ D. J. Willams;M. Shah ] / Computer Vision, Graphic, and Image Processing
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[ L. Ballerini ] / Proc. of first European Workshop on Evolutionary Computation in Image Analysis and Signal Processing
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