  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.
