摘要
为了提高医学图像分割质量,提出了一种基于X光医学图像的改进分水岭算法。算法在应用分水岭算法前首先对感兴趣图像进行预处理,包括对感兴趣区域进行最小阈值法,分离背景区,对前景区运用腐蚀和膨胀运算得到候选区;在分水岭变换过程中,通过像素聚类合并准则,将与主像素聚类有相同特性的次像素聚类加入到分割结果中,最终得到合并区域。试验证明,这种改进的分水岭算法使过分割现象得到减少,有效地分割和提取医学图像中的病变区域。
This paper proposes an improved watershed segmentation algorithm to improve the quality of medical image segmentation. Firstly, the medical image is pre-processed before using this algorithm, including the applica- tion of minimum threshold method to the region of interest, the separation of foreground background area, and the determination of the candidate regions by operations of dilation and erosion. Then in the process of watershed trans- form, the connected clusters of the same characteristics with the primary cluster are added to the segmentation result by the pixel clustering combination rule to give the merge area. Experiments prove that this improved watershed algo- rithm can effectively extract the lesion region from the medical image while diminishing segmentation.
出处
《电子科技》
2015年第6期9-12,共4页
Electronic Science and Technology
关键词
分水岭算法
医学图像分割
聚类合并
watershed segmentation algorithm
medical image segmentation
clustering merger
