中文摘要：

房间图象分割是在 cytopathological 分析的必要的步。尽管他们的执行速度是快的，由常规基于象素、基于边、基于连续性的方法的房间图象分割的结果经常是粗糙的。在一幅房间图象的好结构能与快速调整阀值层次的一个方法被获得。然而，如此的一个方法的处理时间通常长，最后的结果可能对紧张差别和另外的因素敏感。在这篇文章，一个新精力模型被建议综合一个微分方程从常规并且水平集合方法，并且利用房间图象的不一致性质(例如细胞质比背景更不平) 。建议模型的可行性和坚韧性被处理相对复杂的背景图象表明模仿并且真实房间图象。

英文摘要：

Cell image segmentation is an essential step in cytopathological analysis. Although their execution speed is fast, the results of cell image segmentation by conventional pixel-based, edge-based and continuity-based methods are often coarse. Fine structures in a cell image can be obtained with a method that quickly adjusts the threshold levels. However, the processing time of such a method is usually long and the final results may be sensitive to intensity differences and other factors. In this article, a new energy model is proposed that synthesizes a differential equation from the conventional and level set methods, and utilizes the nonuniformity property of cell images （e.g. cytoplasms are more uneven than the background）. The feasibility and robustness of the proposed model was demonstrated by processing relatively complicated background images of both simulated and real cell images.