[1]张天驰,张健沛,张菁,等.面向多纹理特征的脑瘤图像分割方法[J].哈尔滨工程大学学报,2019,40(02):338-346.[doi:10.11990/jheu.201712050]
 ZHANG Tianchi,ZHANG Jianpei,ZHANG Jing,et al.Segmentation method of brain tumor image for multi-texture features[J].hebgcdxxb,2019,40(02):338-346.[doi:10.11990/jheu.201712050]
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面向多纹理特征的脑瘤图像分割方法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2019年02期
页码:
338-346
栏目:
出版日期:
2019-02-05

文章信息/Info

Title:
Segmentation method of brain tumor image for multi-texture features
作者:
张天驰1 张健沛1 张菁2 安东东1
1. 哈尔滨工程大学 计算机科学与技术学院, 黑龙江 哈尔滨 150001;
2. 济南大学 信息科学与工程学院, 山东 济南 250022
Author(s):
ZHANG Tianchi1 ZHANG Jianpei1 ZHANG Jing2 AN Dongdong1
1. College of Computer Science And Technology, Harbin Engineering University, Harbin 150001, China;
2. College of Information Sience and Engineering, University of Ji’nan, Ji’nan 250022, China
关键词:
纹理图像分割纹理特征纳什均衡理论C-V模型相似区域脑瘤图像
分类号:
TP391.4
DOI:
10.11990/jheu.201712050
文献标志码:
A
摘要:
为了研究医学脑瘤图像纹理特征的选取和平滑图像分割轮廓线的问题,依据纳什均衡理论,给出了纳什均衡的多纹理特征计算方法和表示公式;并在纳什均衡多纹理计算的基础上,给出了纳什均衡计算的相似区域的判断与相似区域的合并方法,提出了用于图像分割轮廓线平滑的面向多纹理特征的改进的C-V模型。脑瘤图像分割实验结果表明:本文方法与较典型的纹理图像分割方法相比,脑瘤图像分割准确率平均提高5%,验证了本文方法的有效性。

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备注/Memo

备注/Memo:
收稿日期:2017-12-14。
基金项目:国家自然科学基金项目(51679058);高等学校博士点基金资助项目(20132304110018).
作者简介:张天驰,男,博士研究生;张健沛,男,教授,博士生导师;张菁,女,教授,博士生导师.
通讯作者:张菁,E-mail:isezhangjing@ujn.edu.cn
更新日期/Last Update: 2019-01-30