基于局部颜色熵的免疫组化图像边缘检测

Edge detection of IHC tissue images based on local color entropy

针对免疫组化图像边缘提取中经常出现的染色区域颜色混叠现象,提出了一种局部的颜色熵方法,由免疫组化图像在R、G、B单颜色通道的局部图像熵来合成最终的图像熵,并根据图像熵使用类间最大方差法提取目标边缘。Matlab仿真实验表明,与传统的图像熵分割方法相比,该方法对图像中有颜色变化但亮度近似的边界区域有很好的边界提取效果,而且还有效避免了传统图像熵在图像边缘拐角处的熵值丢失或阶跃的情况,算法分割的准确性和鲁棒性都得到明显的提高。

The immunohistochemical （IHC） image segmentation often appears some problems caused by uneven or overlapping stain, resulting in bad edge detection. This paper proposed a local color entropy method based on the properties of R,G,B color channels in IHC images. For IHC images, the better result of entropy for edge detection in this paper can be obtained by adding color information for image entropy in order to target areas which have a different color but approximate grey scale, and a good edge detection can be got by OTSU. By comparing the result of Matlab simulation experiment and that of traditional image entropy for edge detection, this method can be proved that it efficiently extract the contours with a high ratio for detection of targets.