Medical image series segmentation using watershed transform and active contour model

F. Zhu, Jie Tian, Xiping Luo, Xingfei Ge
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引用次数: 3

Abstract

In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorithm with the watershed method. Then the computer will segment the nearby slice using the modified active contour model. We introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the grayscale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows. that our algorithm can obtain the boundary of the desired object from a series of medical images reliably with only little user intervention.
基于分水岭变换和活动轮廓模型的医学图像序列分割
本文提出了一种基于活线算法和活动轮廓模型相结合的医学图像序列半自动分割算法。首先,将livewire算法与分水岭法相结合,对医学图像序列中的一个或多个切片进行精确分割。然后利用改进的活动轮廓模型对附近的切片进行分割。我们在活动轮廓模型的边界点上引入灰度模型,记录分割切片中目标的局部区域特征,并用灰度模型的似然值决定的能量代替传统活动轮廓模型的外部能量。此外,我们还引入了蛇的活动区域概念来提高分割精度。实验显示。该算法可以在用户干预较少的情况下,从一系列医学图像中可靠地获得目标的边界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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