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A algorithm of medical image segmentation based on active contour model

机译:一种基于主动轮廓模型的医学图像分割算法

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In this paper, a new algorithm based on the active contour model for medical segmentation is presented. The deformable contour in the object is optimized by a different method of minimizing the energy function based on the greedy algorithm, a novel initialization algorithm to locate the initial contour has been developed. A new term for the internal energy and another one for external energy which solve common problems associated with classical active contour model in this type of images have been introduced. The internal energy of the model depends on local behavior of the contour, while the external energy is derived from image wavelet transform modulus maxima features. The algorithm is able to detect convex and concave object, Examples are presented to demonstrate the efficiency of the approach on spinal CT/MRI images and the results are encouraging.
机译:本文介绍了一种基于医学分割活动轮廓模型的新算法。对象中的可变形轮廓通过基于贪婪算法最小化能量函数的不同方法优化,已经开发了一种新颖的初始化算法来定位初始轮廓。已经介绍了内部能量的新术语和用于在这种类型的图像中解决与经典主动轮廓模型相关的常见问题的外部能量。模型的内部能量取决于轮廓的局部行为,而外部能量来自图像小波变换模数最大特征。该算法能够检测凸凹对象,提出了示例以证明脊柱CT / MRI图像上的方法的效率,结果是令人鼓舞的。

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