[1]苏洁,刘帅.基于隐马尔可夫随机场的细胞分割方法[J].哈尔滨工程大学学报,2019,40(02):400-405.[doi:10.11990/jheu.201704062]
 SU Jie,LIU Shuai.Cell segmentation method based on hidden Markov random field[J].hebgcdxxb,2019,40(02):400-405.[doi:10.11990/jheu.201704062]
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基于隐马尔可夫随机场的细胞分割方法(/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:
400-405
栏目:
出版日期:
2019-02-05

文章信息/Info

Title:
Cell segmentation method based on hidden Markov random field
作者:
苏洁12 刘帅2
1. 济南大学 信息科学与工程学院, 山东 济南 250022;
2. 哈尔滨理工大学 计算机科学与技术学院, 黑龙江 哈尔滨 150080
Author(s):
SU Jie12 LIU Shuai2
1. School of Information Science and Engineering, University of Ji’nan, Ji’nan 250022, China;
2. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
关键词:
图像分割k均值聚类隐马尔可夫随机场期望最大值算法最大后验概率
分类号:
TP391
DOI:
10.11990/jheu.201704062
文献标志码:
A
摘要:
为了提高细胞聚合、粘连区域的分割准确性,本文提出一种基于空间聚类和隐马尔可夫随机场的两级分割算法。以像素点颜色特征为依据,在Lab色彩空间中采用k-means++聚类方法得到初始化标签集;通过HMRF构建细胞图像的空间表达模型,充分利用空间约束关系,减少孤立点影响,平滑分割区域;采用期望最大值算法优化模型参数,利用标记场和观测场的相互作用,通过迭代算法不断调整标签集合,迭代直至收敛得到全局最优值。对来自于骨髓涂片的61幅细胞图像中的780个6类细胞的实验表明,本文算法提高了分割的准确率(不小于95%),便于进一步提取细胞病理特征,实现检测识别。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-04-20。
基金项目:哈尔滨市科技创新人才项目(2016RAQXJ163).
作者简介:苏洁,女,副教授.
通讯作者:苏洁,E-mail:sujie0001@sina.cn
更新日期/Last Update: 2019-01-30