一种基于水平集的三维肝脏磁共振图像混合分割方法

针对腹部复杂的内部结构、各组织之间存在相互浸润，使得腹部磁共振(Magnetic resonance, MR)图像存在大量弱边缘的问题，以及使用传统水平集（Level set）方法对肝脏进行分割时易在弱边缘处产生泄露，采取阈值分割等算法进行预处理以获取更好的分割效果，并使用一种改进的水平集方法分割提取三维腹部MR图像中的肝脏。使用阈值分割进行粗分割可以有效减少干扰，将粗分割的结果进行亮度映射，增强边缘信息，然后将预分割的结果作为初始水平集，使用改进的水平集方法对其进行进一步分割。实验证明多种算法的有效结合能够改善传统水平集分割方法在弱边缘处过度演化的问题，获得较为理想的分割效果，拓展了水平集方法的应用。

Hybrid Segmentation for 3D Liver Magnetic Resonance Imaging Based on Level Set Method

Aiming at the complicated internal structure of abdomen and the mutual infiltration between organizations, an improvement of level set method is used to extract the 3D abdomen magnetic resonance image segmentation of liver area. Level set method is easy to leak in weak edges. Therefore, this problem is solved by preprocessing threshold segmentation. Certain interference in further processing is reduced and the edges is more clear through remapping the intensity of pre segmentation results, and then the improved level set method is used for further segmentation. Experiments proves that the method is superior to traditional level set methods. The leaking problem of weak edges is reduced, and the desired segmentation result is obtained. The applicability of level set is expended.