摘要
CB法微核图像中淋巴细胞的粘连情况可分为串联、并联、串并联三类。首先利用面积阈值、圆度阈值、延展度阈值提取串联的淋巴细胞区域;然后采用改进的基于凹点搜寻的分离方法对串联淋巴细胞区域进行分离,同时克服了崎岖边界的干扰问题;对于分离后的细胞,再判断其是否为双核淋巴细胞。这为CB法微核图像自动分析中串联淋巴细胞的判别和分离提供了一种切实可行的解决方法,有助于提高CB法微核图像分析的准确度和可靠性,而不影响自动分析的速度。
Overlapping lymphocytes in the cytokinesis- block micronucleus image can be classified into series cells, parallel cells and series-parallel cells. Three character parameters, i.e. the area, roundness and elongation were used to extract the series cell objects firstly, and then an improved separation method based on searching concave points was presented and used to separate the series cell objects. This im- proved separation method can overcome the influencing factors caused by the rugged contours of the ob- jects. The separated lymphocytes were identified as binucleated cells or not. This provides a feasible method for distinguishing and separating the series cells, which is beneficial to improve the accuracy and reliability for micronucleus frequency without delaying the entire analysis process.
出处
《中国体视学与图像分析》
2009年第3期296-301,共6页
Chinese Journal of Stereology and Image Analysis
关键词
淋巴细胞
CB法微核试验
微核图像
粘连细胞
自动分离
最短距离
凹点
lymphocytes
cytokinesis-block micronucleus assay
micronucleus image
overlapping cells
automated separation
minimum distance
concave point.