Segmentation and shape tracking of whole fluorescent cells based on the Chan-Vese model.
We present a fast and robust approach to tracking the evolving shape of whole fluorescent cells in time-lapse series. The proposed tracking scheme involves two steps. First, coherence-enhancing diffusion filtering is applied on each frame to reduce the amount of noise and enhance flow-like structures. Second, the cell boundaries are detected by minimizing the Chan-Vese model in the fast level set-like and graph cut frameworks. To allow simultaneous tracking of multiple cells over time, both frameworks have been integrated with a topological prior exploiting the object indication function. The potential of the proposed tracking scheme and the advantages and disadvantages of both frameworks are demonstrated on 2-D and 3-D time-lapse series of rat adipose-derived mesenchymal stem cells and human lung squamous cell carcinoma cells, respectively.
Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, 60200 Brno, Czech Republic. xmaska@fi.muni.cz
Martin
M
Maška
Ondřej
O
Daněk
Saray
S
Garasa
Ana
A
Rouzaut
Arrate
A
Muñoz-Barrutia
Carlos
C
Ortiz-de-Solorzano
D000818:Animals; D045744:Cell Line, Tumor; D002467:Cell Nucleus / Q000737:chemistry; D048430:Cell Shape / Q000502:physiology; D058948:Cell Tracking / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D059630:Mesenchymal Stem Cells / Q000166:cytology; D008856:Microscopy, Fluorescence / Q000379:methods*; D051381:Rats