基于最大内切圆的肝影像自动分割方法

针对肝脏区域提取中的手动选择种子点以及提取时的准确性和完整性问题,提出了一种基于最大内切圆的肝影像自动分割算法。采用最大区域面积测量法锁定二值化后的肝脏区域,通过寻找锁定肝脏区域的最大内切圆的圆心来自动获取种子点位置;采用改进的区域生长算法进行图像分割。实验结果表明,该方法有效地解决了区域生长的种子点手动选取问题,并且能够精确、完整地分割出肝脏组织,避免了受主观因素影响而将种子点选取在边缘或噪声等错误位置。

Automatic Segmentation Method of Liver Image Based on Maximum Inscribed Circle

Aiming to the problem of selecting the seed points manually and the accuracy and integrity of extracting the liver region, an automatic segmentation method based on the maximum inscribed circle is proposed in this paper. Firstly, the method uses the maximum area measurement method to lock the binarized liver region, and then automatically acquires the seed point position by finding the center of the largest inscribed circle that locks the liver region. Finally, the improved region growing algorithm is used for image segmentation. The experimental results show that the method effectively solves the problem of manually selecting seed points for regional growth, and can accurately and completely segment the liver tissue. In addition, it avoids subjective factors to select seed points at the wrong positions such as edges or noise.