基于模糊膨胀模型的细胞核轮廓提取方法

针对细胞核之间经常出现重叠聚堆的现象，提出了一种新的基于模糊膨胀模型的细胞核轮廓提取方法．结合细胞核的椭圆边界信息，将图像数据映射到反映与细胞核颜色和位置关系的多个模糊域；基于这些模糊映射关系，建立了一种新的主动轮廓模型进行细胞核轮廓跟踪．采用一种自适应的膨胀机制帮助曲线克服局部极小值快速膨胀直到收敛到真实边界．多种信息的融合使得模型具有较强的边界跟踪能力．实验表明，对细胞核边界的残缺或重叠部分具有较好的分割效果，且分割性能很稳定．

Cell Nucleus Segmentation Based on Fuzzy Growing Snake

In this paper an automated cell nucleus segmentation method is proposed based on a novel fuzzy growing snake model for color cell images from esophageal smears. After estimating the ellipse parameters for each cell nucleus, the image point is mapped into several fuzzy domains which measure tinctorial uniformity and positional proximity of the pixel to the nucleus. Based on these fuzzy measures, a growing active contour model is developed to track the nucleus boundary. To help the model overcome local minimum, a self-adaptive growing energy is added to inflate the contour until it expands out of the nucleus. The utilization of ellipse estimation gives the model the strong edge reconstruction ability for the overlapped nucleus. Experiments show that the method has excellent segmentation results and stable performance.