内皮细胞图像自动分割与荧光强度测量方法

针对内皮细胞提出了一种自动分割与细胞区域荧光强度测量方法。通过形态学重建和背景减除消除图像的光照不均匀背景；利用直方图均衡化进行图像增强；增强图像经自动阈值分割与形态学滤波得到二值化粗分割结果；在粗分割结果上利用形态学细化和分水岭算法获取前景与背景的标记点；结合增强图像的梯度及标记点，利用标记点控制的分水岭算法完成分割；最终通过求取分割所得细胞区域内的平均荧光强度完成测量。在实际图像上的实验结果表明，相比于直接使用阈值分割方法，所提出的方法能更准确地完成图像分割及荧光强度的测量。

Automatic segmentation and fluorescent intensity measurement for endothelial cell images

Quantitative measurement of fluorescent emission is important. An automatic segmentation and cell region fluorescent intensity measuring method was proposed for endothelial cells. Morphological image reconstruction and background subtraction were used to eliminate the uneven image background. Histogram equalization was adopted for image enhancement. Automatic thresholding and morphological filtering were subsequently carried out on the enhanced image, resulting in the binary coarse segmentation, which was afterwards processed by morphological thinning and watershed transform to obtain foreground and background markers, respectively. Marker-controlled watershed was performed on the gradient map of the enhanced image to give the final segmentation. Average fluorescent intensity over the segmented cell regions was calculated and the measurement was completed. The experimental results on real-world images show that, compared with the direct thresholding approach, the proposed method can achieve more accurate segmentation and fluorescent intensity measurement.