郑州大学学报（理学版）2017，Vol.49Issue(1)：34-38,44,6.DOI:10.13705/j.issn.1671-6841.2016329
改进RSF主动轮廓模型的医学图像分割方法
The Medical Image Segmentation Method of ImprovedRSF Active Contour Model
摘要
Abstract
A modified region-scalable fitting model was put forward against the defects such as being less divided and the slow convergence of outline during the segmentation of certain medical images by the RSF model.K-means was employed to process the medical image globally, and then a new kernel function replaced the Gaussian function.On the basis of the new kernel function, a new energy function was re-established, and the internal energy was introduced into the level set model as a penalty function.Compared with traditional RSF model, the results showed that the accuracy of the improved model increased by nearly 40%, and the rate increased by about 30%.关键词
主动轮廓模型/水平集方法/RSF模型/K均值/核函数Key words
active contour model/level set method/RSF model/K-means/kernel function分类
信息技术与安全科学引用本文复制引用
元昌安,郑彦,覃晓,周凯,赵庆北..改进RSF主动轮廓模型的医学图像分割方法[J].郑州大学学报（理学版）,2017,49(1):34-38,44,6.基金项目
国家自然科学基金项目(61363037). （61363037）
