摘要
对免疫细胞图像进行全自动分析在医学疾病诊断上有很高的应用价值。要完成自动图像分析,关键是要实现图像的非监督分割。根据免疫细胞图像中细胞核是一种椭圆状目标的特点,提出了一种椭圆形目标定位方法。在文献中,首先用这种目标定位方法将待分割图像中的细胞核位置找到,然后在细胞核所在的区域内运行水域分割算法(watershed变换)就可实现图像的非监督分割。这种非监督分割策略解决了在大范围内运行中算法一次分割目标时存在的容易错分割的缺点,实现了对特定细胞图像的非监督分割。实验结果表明该方法具有目标定位准确率较高、分割的准确精度和可重复性好等特点。
Automatically analyzing of immune cell image can be used for diagnosing the illness and has highly value in medical science. And automatically segmenting image is the crucial step for this analysis. In this paper, an ellipse object location detecting method is described. With this method the location of ellipse karyon can be found in the immune cell image. After having gotten the location of each karyon, watershed transform is run in each little region which karyons exists in. As a result, the image was automatically segmented. The immune cell image would often be segmented falsely if the segmentation method described in [1] is run in a large region. By using this unsupervised segmentation method the problem can be solved very well. Through experiment the locating method for ellipse object is proved to be highly precise, and the unsupervised segmentation result can meet the need.
出处
《中国体视学与图像分析》
2002年第4期224-228,共5页
Chinese Journal of Stereology and Image Analysis
关键词
水域分割
非监督分割
watershed segmentation
unsupervised segmentation
