Konzept für Bildanalysen in Hochdurchsatz-Systemen am Beispiel des Zebrabärblings
This provides biologists with an approach for high-throughput zebrafish image analysis, though it appears incremental as it builds on existing high-throughput methods with domain-specific adaptations.
The paper tackles the challenge of handling massive data in image-based high-throughput experiments by proposing an optimized experiment layout method and new zebrafish-specific image analysis modules. The result is reduced data volume, redundant information, workload, and classification errors.
With image-based high-throughput experiments, new challenges arise in both, the design of experiments and the automated analysis. To be able to handle the massive number of single experiments and the corresponding amount of data, a comprehensive concept for the design of experiments and a new evaluation method is needed. This work proposes a new method for an optimized experiment layout that enables the determination of parameters, adapted for the needs of automated image analysis. Furthermore, a catalogue of new image analysis modules, especially developed for zebrafish analysis, is presented. The combination of both parts offers the user, usually a biologist, an approach for high-throughput zebrafish image analysis, which enables the extraction of new signals and optimizes the design of experiments. The result is a reduction of data amount, redundant information and workload as well as classification errors.