Name
Abstract | ||
|---|---|---|
The tracking of individual cells in time-lapse microscopy fa- cilitates the assessment of certain characteristics of difierent cell types. Since manual tracking of an adequate number of cells over a consider- able number of frames is tedious and sometimes not feasible, there is a vital interest in automated methods. We present a rather minimalistic approach for the tracking of unstained cells in cell culture assays. The proposed approach comprises background subtraction, an object detec- tion method based on discrete geometrical feature analysis together with a validation of the resulting graph-structures. The main advantage of this approach lies in its computational e-ciency. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-540-93860-6_59 | Bildverarbeitung für die Medizin |
Keywords | Field | DocType |
cell culture,background subtraction | Background subtraction,Object detection,Pattern recognition,Spatio-Temporal Analysis,Computer science,Cell culture assays,Speech recognition,Cell type,Artificial intelligence,Microscopy,Pattern recognition (psychology) | Conference |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nico Scherf | 1 | 1 | 2.71 |
| Jens-Peer Kuska | 2 | 55 | 9.84 |
| Ulf-dietrich Braumann | 3 | 66 | 14.28 |
| Katja Franke | 4 | 47 | 2.96 |
| Tilo Pompe | 5 | 0 | 0.68 |
| Ingo Röder | 6 | 0 | 0.34 |