基于条件约束的区域生长法耳蜗MR图像分割  

Cochlear MR image segmentation based on conditional constraint region growing method

作　　者：张宇豪 徐磊[1] 白一清 Zhang Yuhao;Xu Lei;Bai Yiqing(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《电子测量技术》2021年第8期105-109,共5页Electronic Measurement Technology

基　　金：上海市自然科学基金(17ZR1443500)项目资助。

摘　　要：在传统区域生长算法中,由于生长判定规则具有局限性,所以在分割医学图片时很容易产生过分割现象。为了解决过分割问题,提出了一种基于距离约束、多种子点加权的区域生长法对颞骨MR图像中的耳蜗区域进行分割。首先在区域生长法中添加一个距离约束条件,用于解决原始算法中存在的过分割问题;然后又进一步引入动态多种子加权生长规则,降低了因种子点选取不适造成的误差。经过在多组数据上进行实验,所提出改进算法的Dice系数和交并比的平均值分别达到90.13%和88.59%,面积重叠误差和相对面积差平均值仅有11.64%和9.89%,较好于其他算法。In the traditional region growing algorithm,because of the limitation of the growing rule,it is easy to produce over segmentation phenomenon in medical image segmentation.In order to solve the problem of over segmentation,a region growing method based on distance constraint and multiple sub points weighting is proposed to segment the cochlear region in temporal bone MR images.Firstly,a distance constraint is added to the region growing method to solve the over segmentation problem in the original algorithm.Then,the dynamic multi seed weighted growing rule is introduced to reduce the error caused by the unsuitable selection of seed points.After experiments on several groups of data,the average values of Dice coefficient and intersection union ratio of the improved algorithm are 90.13%and 88.59%respectively,and the average values of area overlap error and relative area difference are only 11.64%and 9.89%,which are better than other algorithms.

关 键 词：耳蜗分割 区域生长法 条件距离约束 多种子点 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]