Name
Title | ||
|---|---|---|
Automated Analysis of Mitotic Phenotypes in Fluorescence Microscopy Images of Human Cells |
Abstract | ||
|---|---|---|
High-throughput screens of the gene function provide rapidly increasing amounts of data. In particular, the analysis of image
data acquired in genome-wide cell phenotype screens constitutes a substantial bottleneck in the evaluation process and motivates
the development of automated image analysis tools for large-scale experiments. Here we introduce a computational scheme to
process multi-cell time-lapse images as they are produced in high-throughput screens. We describe an approach to automatically
segment and classify cell nuclei into different mitotic phenotypes. This enables automated identification of cell cultures
that show an abnormal mitotic behaviour. Our scheme proves a high classification accuracy, suggesting a promising future for
automating the evaluation of high-throughput experiments.
|
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/3-540-32137-3_76 | Bildverarbeitung für die Medizin |
Keywords | Field | DocType |
cell culture,high throughput,fluorescence microscopy,image analysis,high throughput screening | Cell culture,Analysis tools,Fluorescence microscope,Mitosis,Phenotype,Biology,Cell biology,Cell | Conference |
Citations | PageRank | References |
1 | 0.42 | 3 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nathalie Harder | 1 | 114 | 17.57 |
| Beate Neumann | 2 | 1 | 0.42 |
| Michael Held | 3 | 911 | 509.89 |
| Urban Liebel | 4 | 22 | 4.86 |
| Holger Erfle | 5 | 29 | 4.94 |
| Jan Ellenberg | 6 | 46 | 7.40 |
| Roland Eils | 7 | 644 | 70.09 |
| Karl Rohr | 8 | 33 | 7.02 |