Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs

0456332 - BFÚ 2016 RIV US eng J - Journal Article
Matula, Pavel - Maška, M. - Sorokin, D.V. - Matula, Pe. - Ortiz de Solorzano, C. - Kozubek, M.
Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs.
PLoS ONE. Roč. 10, č. 12 (2015). ISSN 1932-6203. E-ISSN 1932-6203
R&D Projects: GA MŠMT(CZ) EE2.3.30.0030
Institutional support: RVO:68081707
Keywords : FLUORESCENCE MICROSCOPY IMAGES * LINEAGE CONSTRUCTION * MANUAL VALIDATION
Subject RIV: BO - Biophysics
Impact factor: 3.057, year: 2015

Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical.
Permanent Link: http://hdl.handle.net/11104/0256896