基于活动轮廓和Gabor滤波器的细胞分割

将Tony F Chan提出的基于曲线进化、Mumford-shah泛函和level set技术的没有边界泛函的活动轮廓模型与Gabor滤波器相结合,利用Tony F Chan提出的不依赖于边界梯度的活动轮廓能够检测出边界梯度较弱的物体边界与Gabor滤波器能在不同方向和频率增强图像的特点,先对原始细胞图像进行不同角度、不同频率Gabor滤波从而在不同方向增强细胞边界削弱细胞内部信息,然后把不同方向滤波后的图像融合以得到边界增强噪声减少的图像,最后在该图像上应用活动轮廓取得了较好的分割效果.

Wall-pasted Cells Segmentation Based on Active Contour Models and Gabor Filters

In order to segment cells images accurately and efficiently we combine the model proposed by Tony F. Chan with Gabor filter. The model proposed by Tony F. Chan can detect very weak boundary based on function energy instead of the gradient. Gabor filter can enhance the cells boundaries in different angle and denoise the image. In the experiments,we firstly use Gabor filter to enhance the image with different angle,and then fuse the enhanced images to get better images. At last we use the active contour model to the fused image. The result shows the model we proposed is better than the model which dose not use Gabor filter.