Segmentation and shape tracking of whole fluorescent cells based on the Chan-Vese model
Language English Country United States Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Cell Nucleus chemistry MeSH
- Cell Tracking methods MeSH
- Microscopy, Fluorescence methods MeSH
- Rats MeSH
- Humans MeSH
- Mesenchymal Stem Cells cytology MeSH
- Cell Line, Tumor MeSH
- Image Processing, Computer-Assisted methods MeSH
- Cell Shape physiology MeSH
- Animals MeSH
- Check Tag
- Rats MeSH
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
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.
References provided by Crossref.org
An objective comparison of cell-tracking algorithms
Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs
A benchmark for comparison of cell tracking algorithms
