An Approach of Automatically Selecting Seed Point Based on Region Growing for Liver Segmentation
Yongquan Xia, Xiwang Xie, Xin-Wen Wu, Zhi Jun Ma, Sihai Qiao · 2019
Liver region extraction in abdominal CT images is a very important research field, a method of liver segmentation based on region growing for automatic selection of seed points is proposed in this paper. Firstly, the original image is binarized, and the initial area of the liver is extracted by the maximum area measurement method; After that, the improved region growth algorithm was used to segment the liver, and the location of seed points was automatically obtained by finding the center of the maximum inscribed circle locked in the initial liver area, which was used as the basis for the selection of seed points; Finally, the segmented liver region is treated by morphological methods. The experimental results show that the approach effectively solves the problem of manually selecting seed points for regional growth, and can improve the efficiency and accuracy of seed point selection, which avoids the selection of seed points at the wrong positions such as edges or noise due to subjective factors.