摘要
传统的分割方法难以实现医学图像准确地分割,提出了基于最大信息熵原理的医学图像分割方法。该方法集成了阈值分割、边界跟踪和数学形态学,提高了分割的精度和速度。分析和实验结果表明,采用该方法对肝肿瘤CT图像进行分割时,能自动准确地提取出医生感兴趣的区域。
Traditional segmentation methods can not realize true medical image segmentation,therefore a new approach of medical image segmentation based on principle of maximum entropy is presented in this paper.The method uses threshold segmentation, boundary tracking and mathematical morphology in a comprehensive way, and it improves the speed and accuracy of segmentation.Analysis and experiment prove that this method can extract Regions Of Interest（RO1） in the liver tumor CT images.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第34期222-224,共3页
Computer Engineering and Applications
基金
湖南省卫生厅基金项目 No.C2005029~~
关键词
医学图像分割
最大熵原理
阈值分割
边界跟踪
数学形态学
medical image segmentation
principle of maximum entropy
threshold segmentation
contour tracking
mathematical morphology
