Research on Multi-Target Organs’ Segmentation of Abdominal CT
Image Based on Super-Pixel Method
ZHANG Haitao1, LIU Jingxin2, Wang Chunyue1, ZHAO Xiaoqing1, LI Huiying1
1.College of Computer Science and Technology, Jilin University, Changchun Jilin 130012, China;
2.China-Japan Union Hospital of Jilin University, Changchun Jilin 130033, China
Abstract：In order to address the typical problems in the medical image, such as unclear boundaries between organs and loud
imaging noises, we proposed a method of automatic segmentation to get the target organs’ images from abdominal medical images
by building super-pixels. The super-pixel based segmental method adapted to various imaging conditions in the CT image and
considered the interrelationship and constraints among multiple organs. In this method, we firstly clustered the super-pixels in the
light of pixel correlation and location adjacency, then the spatial distribution of organs was used to modify the segmentation process
of multiple organs. The experimental results showed that this proposed method could effectively segment the organs in the abdominal
CT images compared with some other traditional segmental algorithms.
张海涛1，刘景鑫2，王春月1，赵晓晴1，李慧盈1. 基于超像素方法的腹部CT影像多目标器官分割研究[J]. 中国医疗设备, 2018, 33(1): 24-28.
ZHANG Haitao1, LIU Jingxin2, Wang Chunyue1, ZHAO Xiaoqing1, LI Huiying1. Research on Multi-Target Organs’ Segmentation of Abdominal CT
Image Based on Super-Pixel Method. China Medical Devices, 2018, 33(1): 24-28.
