基于熵分割算法对CT肝脏兴趣区的提取

基金项目:

咸宁学院青年科研项目

详细信息

Extraction of ROI from CT Liver Based on Entropy Image Segmention Algorithm

1. Department of Biomedical Engineeringof Xianning University, Xianning 437100, China;
2. Department of Mathematics and Statistics of Xianning University, Xianning 437100, China

摘要: 目的:在计算机辅助诊断(CAD)和未来治疗中,提取已分割好的CT肝脏组织中的兴趣区。方法:利用熵分割算法对CT肝脏组织的兴趣区进行自动分割,并和专业医生手工分割的兴趣区作比较。结果:分割的兴趣区与专业医生分割的兴趣区相比,该方法具有良好的获取兴趣区的能力。结论:在不同条件下对肝脏做相应预处理,然后分别对手工分割的兴趣区与熵分割的兴趣区相应数据作比较,得出熵分割算法是一种极为有效的图像自动分割方法。
- 熵分割 /
- 兴趣区提取 /
- CT图像
Abstract: Objective: In the computer-aided diagnosis and treatment of the future,in order to extract a good CT liver tissue has been divided in the interest area.Methods: Using entropy segmentation algorithm for CT liver tissue region of interest of automatic segmentation,and professional doctor’s manual segmentation in the zone of interest relative ratio.Results: Segmentation of the region of interest and specialty physician’s segmentation of the region of interest,with good access to the capacity of region of interest.Conclusion: In different conditions of the liver to do the corresponding pretreatment,and then the manual segmentation of the region of interest and entropy in the corresponding data for comparison,the entropy method is very effective.
- iterative segmentation /
- ROI segmentation /
- CT image