Abstract: To develop an automatic claasifying and diagnostic system for the hematopoietic cells from the blood and bone marrow smears stained with wright，an automated segmentation algorithm fusing gray space，colorful information and mathematical morphological gradient is proposed for segmentation of the nucleated hematopoietic cells（including nucleus and cytoplasm）.For the accurate segmentation of the nucleus，the conventional iterative threshold segmentation are improved.Color information and prior knowledge are fully used by transaction of color spaces.In order to prevent over-segmentation，the morphological gradient information is used to mark the background，nucleus and cytoplasm.The edge detection is implemented in gray gradient image since the morphological gradient can detect the contour better than other conventional edge detection operators.The success rate is 95.5％ for nucleus and 92.6％ for cytoplasm．The results show that the method is valid and efficient to segment color images from blood and bone marrow smears.

Key words: automatic segmentation of color celluar image, gray space, iterative threshold segmentation, mathematical morphological gradient

摘要： 为了开发血及骨髓涂片中白细胞自动分类及计算机辅助诊断系统，提出了一种融合灰度空间、彩色信息和数学形态学形态梯度信息的血细胞图像自动分割算法，以完成对白细胞（胞核和胞浆）的分割。在灰度空间，通过改进的迭代阈值分割算法，对白细胞的胞核进行了精确的定位和检出。通过彩色空间变换，有效地利用了图像中血细胞胞浆的颜色信息及先验知识，并且为了抑制过度分割，充分利用梯度信息，合理地对白细胞的胞核和胞浆进行了标记。在灰度梯度图像上提取血细胞的轮廓，并分别赋予不同的标记，表明数学形态梯度算法较传统的边缘检测算子具有更好的边缘提取能力。结果表明，胞核和胞浆的分割正确率分别为95.5％和92.6％，验证了该算法对彩色白细胞图像分割的有效性。

关键词: 彩色细胞图像自动分割, 灰度空间, 迭代阈值分割, 数学形态学梯度