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Medical Image Segmentation by Geodesic active contour methods

机译:测地线主动轮廓线医学图像分割

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Geodesic active contour methods are powerful numerical techniques for image segmentation and analysis. However the edge detector in the model ensures that the data on both sides of the contour is as dissimilar as possible, it cannot deal with the requirement that also the interior of a region should be as homogeneous as possible. In this paper, we present a new region based geodesic active contour method. The new method gives a global view of the boundary information within the image. The method here proposed is particularly well adapted to situations where edges are weak and overlap, and the curve initialization is a very bad guess. A number of experiments on CT medical images were performed to evaluate the new method. The experimental results demonstrate the reliability and efficiency of this new method.
机译:测地线活动轮廓线方法是用于图像分割和分析的强大数值技术。但是,模型中的边缘检测器可确保轮廓两侧的数据尽可能不同,因此无法满足区域内部也应尽可能均匀的要求。在本文中,我们提出了一种新的基于测地线的主动轮廓方法。新方法提供了图像内边界信息的全局视图。这里提出的方法特别适合于边缘较弱和重叠的情况,并且曲线初始化是非常不好的猜测。在CT医学图像上进行了许多实验,以评估该新方法。实验结果证明了该新方法的可靠性和有效性。

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