中文摘要：

肝胞虫疾病是在农场和牧剧区域的普通寄生疾病，它严重影响人的健康。基于这疾病的 CT 成像特征，为肝分割的一条反复的途径和胞虫损害抽取同时被建议。在每次重复，我们的算法由二主要的步组成：1 ) 根据在肝和胞虫的自定义象素种子，损害， Gaussian 概率模型试穿和弄平的贝叶斯的分类被使用得到肝和损害的起始的分割；2 ) 用 priori 形状力量地的参量的活跃轮廓模特儿被收养精制起始的分割。我们由不同病人的 CT 片的肝和胞虫损害分割的实验在建议算法有效性上做主观、客观的评估。与地面真相手册分割结果比较，试验性的结果显示我们的方法的有效性分割肝和胞虫损害。

英文摘要：

Liver hydatid disease is a common parasitic disease in farm and pastoral areas, which seriously influences people＇s health. Based on CT imaging features of this disease, an iterative approach for liver segmentation and hydatid lesion extraction simultaneously is proposed. In each iteration, our algorithm consists of two main steps： 1） according to the user-defined pixel seeds in the liver and hydatid lesion, Gaussian probability model fitting and smoothed Bayesian classification are applied to get initial segmentation of liver and lesion; 2） the parametric active contour model using priori shape force field is adopted to refine initial segmentation. We make subjective and objective evaluation on the proposed algorithm validity by the experiments of liver and hydatid lesion segmentation on different patients＇ CT slices. In comparison with ground-truth manual segmentation results, the experimental results show the effectiveness of our method to segment liver and hydatid lesion.