摘要： 提出了一种改进的主动轮廓线模型应用于细胞核的分割。在利用极限腐蚀检测到每个细胞核的种子点后，以种子点为中心点分别建立一个基于极坐标描述的生长Snake 模型，加入了一个基于区域相似度的生长能量，克服了传统模型须将初始轮廓置于真实边界附近的缺点；在应用贪心算法求解时，搜索空间由常规的8 邻域减少为径向的两个相邻量化点，提高了计算效率。

关键词: 图像分割；细胞图像；主动轮廓线模型；蛇模型

Abstract: This paper presents a novel cell nucleus segmentation method for esophageal cell image. Firstly the ultimate erosion operation is applied to detect the localization of each nucleus and sign it with a seed point. Then the proposed active contour model is built to track the nuclear boundaries. The proposed model describes nuclear contour with sampled points of polar coordinates. A negative constant is added as the growing energy to the energy function at the adjacent point outside when the average intensities difference between the block at this point and the block at the nuclear center point is less than a preset threshold. The growing energy can push the contour points outward. So the initial contour points need not be close to the nucleus boundary. Applying greedy algorithm, the contour points are designed to move from nuclear center to nuclear boundary along the radial directions. So the computation complexity of the model is small.

Key words: Image segmentation; Cell Image; Active contour model; Snake