Abstract
Contours are important in computer vision. Among many algorithms proposed to describe the contours, snake is one of them. In snakes, the energy is minimized by the set of replacements. In natural images, Snake is easy for finding the traditional boundaries by the spline smoothness term. However, medical images are of a difficult problem. In this paper, we propose a method for active contour in medical images by combining the curvelet transform and B-spline. Our algorithm is to increase the ability for smoothing before reducing energy between boundaries which detects in curvelet domain. Compared with other recent methods, the proposed method is better.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Tuyet, V.T.H. (2016). Active Contour Based on Curvelet Domain in Medical Images. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_29
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DOI: https://doi.org/10.1007/978-3-319-46909-6_29
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