In this article, we proposed an improved region‐based active contour model based on curve evolution theory and variational level set method. Our method can be used to segment image with intensity inhomogeneity, such as medical computed tomography images. Our model contains a local intensity fitting term that makes the evolution curve stop at boundaries of the object and a global expansion term that makes the evolution curve have the chance to get to every location in the image. Therefore, our model has a good performance to solve the problem of flexible initialization, which exposed in region‐scalable fitting energy model. For the curvature term that occurs during the calculation, we calculated it with a more efficiency and accuracy method. Compared with other models, our model shows good segmentation result and less computation expense. Finally, we will present some experimental results, especially the result of contrast experiment.

中文翻译：

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一种基于全局和局部特征混合主动轮廓模型的医学图像分割方法

在本文中，我们基于曲线演化理论和变分水平集方法提出了一种改进的基于区域的活动轮廓模型。我们的方法可用于分割强度不均匀的图像，例如医学计算机断层扫描图像。我们的模型包含一个局部强度拟合项，使演化曲线停止在对象的边界处，以及一个全局扩展项，使演化曲线有机会到达图像中的每个位置。因此，我们的模型在解决区域可扩展拟合能量模型中暴露的灵活初始化问题方面具有良好的性能。对于计算过程中出现的曲率项，我们采用了更加高效和准确的方法进行计算。与其他模型相比，我们的模型显示出良好的分割结果和更少的计算开销。最后，