High Throughput (HT) methods are high volume experimental approaches that are common in the fields of the life-sciences. The instrumentation for these methods differs per application. We will focus... Show moreHigh Throughput (HT) methods are high volume experimental approaches that are common in the fields of the life-sciences. The instrumentation for these methods differs per application. We will focus on the HT methods that are concerned with imaging. The aim of this thesis is to find robust methods for object extraction and analysis. We focus on the Computer Science aspects of such analysis, namely pattern recognition. Pattern Recognition can be seen in the context of object recognition and data mining. Both aspects will be described in this thesis. We present a framework for segmenting and recognizing the objects of interest based on Template Matching. This approach was designed for an application in the HT screening of zebrafish embryos. All proposed methods are fully automated. We further elaborate on the segmentation algorithms to apply these in software that can be used in a HT context to derive measurements. Then we apply the software on a real life problem involving zebrafish infected with Mycobacterium marinum. Show less