[1]杨利,蔡文杰,马晶.基于特征提取量化分析的体外活细胞追踪算法研究[J].中国医学物理学杂志,2018,35(9):1080-1086.[doi:10.3969/j.issn.1005-202X.2018.09.016]
　YANG Li,CAIWenjie,MAJing.Algorithm for tracking living cells in vitro based on quantitative analysis of characteristic extraction[J].Chinese Journal of Medical Physics,2018,35(9):1080-1086.[doi:10.3969/j.issn.1005-202X.2018.09.016]
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基于特征提取量化分析的体外活细胞追踪算法研究()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
35卷
期数:
2018年第9期
页码:
1080-1086
栏目:
医学生物物理
出版日期:
2018-09-27

文章信息/Info

Title:
Algorithm for tracking living cells in vitro based on quantitative analysis of characteristic extraction
文章编号:
1005-202X（2018）09-1080-07
作者:
杨利; 蔡文杰; 马晶
上海理工大学医疗器械与食品学院，上海200093
Author(s):
YANG Li;  CAIWenjie;  MAJing
School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
关键词:
细胞追踪; 阈值分割; 拓扑约束; 量化分析
Keywords:
cell tracking;  threshold segmentation;  topological constraint;  quantitative analysis
分类号:
R318.0；TN957.52
DOI:
10.3969/j.issn.1005-202X.2018.09.016
文献标志码:
A
摘要:
目的：提高显微镜下序列图像细胞追踪的效率及准确度。方法：提出双阈值形态学与拓扑约束图论法相结合的 自动细胞追踪算法，用来分析体外活细胞定向迁移轨迹及参数，并从细胞数目及细胞特征两方面分析追踪算法的准确 性。在特征分析方面，从运动速度、运动距离、趋化速度、趋化指数和方向持续性5个指标与手动采样数据进行对比。结 果：该算法可以分别识别在毛细管针部灰度较高区域的细胞及其他区域灰度较低的细胞，细胞数目准确度平均达到 91.8%，分析得到的5个特征指标与手动采样分析结果基本一致，误差不超过5%。结论：双阈值形态学与拓扑约束图论法 相结合的自动细胞追踪算法可以有效提高细胞追踪的准确度。
Abstract:
Objective To improve the efficiency and accuracy of cell tracking algorithm for sequential images under a microscope. Methods An automatic cell tracking algorithm based on two-step threshold and morphology with topology-graph theoretical approach was proposed to analyze the trajectories and motility parameters of living cells in vitro. The accuracy of the cell tracking algorithm was analyzed in the aspects of cell number and cell characteristics. In characteristic analysis, 5 characteristic parameters were compared between automatic cell tracking and manual cell tracking, including motility distance, motility speed, chemotaxis speed, chemotaxis index, and persistency. Results The proposed algorithm achieved the identification of cells in high gray-level regions in the capillary tube and those in other lower gray-level regions, and the accuracy in cell number was 91.8%. The 5 characteristic parameters of automatic cell tracking were consistent with the results of manual sampling, with an error not exceeding 5%. Conclusion The automatic cell tracking algorithm based on two-step threshold and morphology with topologygraph theoretical approach can effectively improve the accuracy of cell tracking.

相似文献/References:

[1]杨利,蔡文杰,马晶. 序列显微镜图像的细胞追踪算法[J].中国医学物理学杂志,2018,35(2):187.[doi:DOI:10.3969/j.issn.1005-202X.2018.02.013]
　YANG Li,CAI Wenjie,MA Jing. Cell tracking algorithm for sequence microscopy images[J].Chinese Journal of Medical Physics,2018,35(9):187.[doi:DOI:10.3969/j.issn.1005-202X.2018.02.013]
[2]程龙,吴昊天,魏晓为,等.一种自动确定放疗原始等中心的新方法[J].中国医学物理学杂志,2022,39(9):1057.[doi:DOI:10.3969/j.issn.1005-202X.2022.09.001]
　CHENG Long,WU Haotian,WEI Xiaowei,et al.A new method for automatically determining the original isocenter in radiotherapy[J].Chinese Journal of Medical Physics,2022,39(9):1057.[doi:DOI:10.3969/j.issn.1005-202X.2022.09.001]

备注/Memo

备注/Memo:
【收稿日期】2018-06-18 【基金项目】上海市浦江人才计划项目（15PJ1406100） 【作者简介】杨利，硕士研究生，主要研究方向：图像处理，E-mail: 547179342@qq.com 【通信作者】蔡文杰，博士，副教授，主要研究方向：图像处理，E-mail: wenjiecai@aliyun.com
更新日期/Last Update: 2018-09-28