结合FCM和RSF模型的医学图像分割方法  

MEDICAL IMAGE SEGMENTATION METHOD COMBINING FCM WITH RSF MODEL

作　　者：郑伟[1] 潘正勇[1] 

机构地区：[1]河北大学电子信息工程学院,河北保定071002

出　　处：《计算机应用与软件》2014年第2期198-200,204,共4页Computer Applications and Software

摘　　要：针对现有活动轮廓模型初始化敏感的缺点,提出一种新的基于区域的活动轮廓模型。该模型采用模糊c均值聚类(FCM)算法对图像进行预分割,将预分割结果二值化为种子标记矩阵,作为下一步水平集演化的初始轮廓,解决了初始化敏感问题;引用RSF(Region-Scalable Fitting)模型的局部区域项作为能量项,提高了分割灰度分布不均匀图像能力;使用高斯滤波方法正则化水平集函数,避免了重新初始化过程,提高了分割效率。实验结果表明:该模型避免了初始化,具有分割结果精确、分割效率高的特点。Aiming at the defect of existing active contour model that it is sensitive to initialisation,we propose a new region-based active contour model in this paper.This model uses the fuzzy C-means clustering （FCM）algorithm to pre-segment the image,and binarise the results of pre-segmentation to the seed tagged matrix,which solves the problem of initialisation sensitivity;The local area item of the RSF（region-scalable fitting）model is adopted as the energy item,which improves the ability of segmenting the images with inhomogeneous grey distribution;In numerical calculation,Gaussian filtering is utilised to regularise the level set function,which prevents the process of re-initialisation and improves segmentation efficiency.Experimental results show that the proposed model prevents the re-initialisation,it has the characteristics of accurate in segmentation result and high in segmentation efficiency.

关 键 词：图像分割 活动轮廓模型 FCM聚类 RSF模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]