摘要
提出一种基于模糊数学的方法来融合多模医学图像。采用改进的FCM算法分割图像,用自动模糊重分布的算法确定隶属度。在融合步骤中考虑到了16种不同图像组织的交混情况和16种上下文关系,总共256种模糊关系。实验结果表明:该方法有很强的抗配准偏差能力和抗分割干扰能力,并具有稳健、快速、精确等特点。
In this paper, a method based on fuzzy mathematics to fuse multimodality medical images was presented. The improved FCM algorithm was adopted to segment images, and automatic fuzzy redistribution algorithm to define the subject degree. 16 different combinations of image tissues and 16 context relations, 256 models altogether, were considered. The result showed that the method had the great ability of anti-error and antisegmentation interference and had the characteristics of robustness, quickness, and accuracy.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2005年第6期1085-1089,共5页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(30370417)
关键词
模糊数学
图像融合
图像分割
Fuzzy mathematics Image fusion Image segmentation