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.
作者
张宇豪
徐磊
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)
出处
《电子测量技术》
北大核心
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。
关键词
耳蜗分割
区域生长法
条件距离约束
多种子点
cochlear segmentation
region growing algorithm
conditional distance constraint
multi-seed point
作者简介
张宇豪,硕士研究生,主要研究方向为医学图像处理、通用目标检测;徐磊,博士研究生,讲师,主要研究方向为人工智能、数字图像处理等;白一清,本科生,主要研究方向为数字图像处理。E-mail:oswald@usst.edu.cn。
