白细胞图像自动识别系统的研究

Research on Automatic Recognition System for Leucocyte Image

我们所用的图像分割方法是在对图像距离变换的基础上,综合区域和边界方法,充分利用图像中包含的信息,实现白细胞图像的分割。根据细胞的形状、纹理、颜色等的特点选取并测定22个特征值,用统计分类的方法设计分类器。通过对560幅图像共831个细胞的测试表明,此系统的识别正确率为96%,经临床专家评估,本系统运用模式识别技术对外周血中的白细胞图像实现自动识别,具有较好的实用价值。

The image segmentation method we use for leucocytes is based on image distance transformation, combining the region and edge approach, taking full advantage of image information. According to the shape, texture and color appearance of cells ,we select 22 feature values and measure them. The classifier is designed on the statistical classification. A test for recognizing 831 leucocytes in 560 images shows that the classification accuracy is 96%. Clinical experts confirm this system; for it can automatically recognize leucocytes by pattern recognition technique, and it is demonstrably valid in practice.