基于概率图谱和Random Walker的肝脏三维分割算法

针对腹部CT图像内部结构复杂和相邻脏器灰度相近而导致分割精度较低的问题,提出了一种新的基于概率图谱和Random Walker的三维肝脏分割算法.首先利用大量的由医生分割的肝脏区域图像建立肝脏存在位置的概率图谱,表示肝脏解剖位置信息;然后提出了改进的全自动的Random Walker算法,并建立由Random Walker优化的灰度概率图谱;最后基于该灰度概率图谱从腹部CT图像进行肝脏三维分割.实验结果表明,提出的算法能够有效地进行肝脏区域的分割并具有较好的鲁棒性,与传统算法相比,分割精度得到了明显的提高.

3D Liver Segmentation Algorithm Based on Probabilistic Atlas and Random Walker

Due to the complicated structure of an abdominal CT image and the low segmentation precision leaded by the similarity of adjacent organs, a novel 3D liver segmentation algorithm based on probabilistic atlas and Random Walker methods was proposed. Firstly, a liver position probabilistic atlas was established by some liver region images segmented by doctors; then, an improved automated Random Walker algorithm was proposed and a gray probabilistic atlas improved by Random Walker algorithm was constructed; lastly, a three dimensional liver segmentation was conducted based on the proposed algorithm from abdominal CT image. Experimental results showed that the proposed algorithm could efficiently segment liver region and own good robustness. Comparing with the traditional algorithms, the segmentation precision is improved greatly.