Tracking of neural stem cells in high density image sequence based on Topological constraint combined with Hungarian algorithm / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 597-603, 2012.
Article
in Chinese
| WPRIM
| ID: wpr-271726
ABSTRACT
Analysis of neural stem cells' movements is one of the important parts in the fields of cellular and biological research. The main difficulty existing in cells' movement study is whether the cells tracking system can simultaneously track and analyze thousands of neural stem cells (NSCs) automatically. We present a novel cells' tracking algorithm which is based on segmentation and data association in this paper, aiming to improve the tracking accuracy further in high density NSCs' image. Firstly, we adopted different methods of segmentation base on the characteristics of the two cell image sequences in our experiment. Then we formed a data association and constituted a coefficient matrix by all cells between two adjacent frames according to topological constraints. Finally we applied The Hungarian algorithm to implement inter-cells matching optimally. Cells' tracking can be achieved according to this model from the second frame to the last one in a sequence. Experimental results showed that this approaching method has higher accuracy compared with that using the topological constraints tracking alone. The final tracking accuracies of average of sequence I and sequence II have been improved 10.17% and 4%, respectively.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Image Processing, Computer-Assisted
/
Cell Count
/
Cell Movement
/
Cell Biology
/
Neural Stem Cells
/
Cell Tracking
/
Methods
/
Microscopy, Fluorescence
/
Models, Theoretical
Type of study:
Prognostic study
Limits:
Animals
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2012
Type:
Article
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