title: Topological constraint in high-density cells' tracking of image sequences.
abstract: The multi-target tracking in cell image sequences is the main difficulty in cells' locomotion study. Aim to study cells' complexity movement in high-density cells' image, this chapter has proposed a system of segmentation and tracking. The proposed tracking algorithm has combined overlapping and topological constraints with track inactive and active cells, respectively. In order to improve performance of algorithm, size factor has been introduced as a new restriction to quantification criterion of similarity based on Zhang's method. And the distance threshold for transforming segmented image into graph is adjusted on considering the local distribution of cells' district in one image. The improved algorithm has been tested in two different image sequences, which have high or low contrast ration separately. Experimental results show that our approach has improved tracking accuracy from 3% to 9% compared with Zhang's algorithm, especially when cells are in high density and cells' splitting occurred frequently. And the final tracking accuracy can reach 90.24% and 77.08%.
authors: School of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, China. tangchunminga@hotmail.com
authors: Chunming
authors: C
authors: Tang
authors: Ling
authors: L
authors: Ma
authors: Dongbin
authors: D
authors: Xu
mesh_terms: D000465:Algorithms; D002452:Cell Count; D002465:Cell Movement; D058948:Cell Tracking / Q000706:statistics & numerical data*; D019295:Computational Biology; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008856:Microscopy, Fluorescence; D008954:Models, Biological