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PDF, English (PhD thesis) - main document Download (11MB) | Lizenz: Computer vision and data-analysis solutions for phenotypic screening of small model organisms by Thomas, Laurent underlies the terms of Creative Commons Attribution 4.0

Abstract

This dissertation reports the design, development and benchmarking of novel research software inspired by the field of computer vision and data-science. The aim was to create versatile and robust solutions tailored to the requirements of microscopy-based phenotypic screening studies in small model organisms. The resulting software tools address various steps of the screening workflow, from manual ground-truth annotations, automated detection of regions of interest, targeted imaging of specific tissues or organs using feedback microscopy, image-classification, and interactive data exploration. Importantly, the tools are generic by design and were benchmarked on several microscopy datasets of zebrafish larvae and medaka embryos. They are particularly suitable for phenotypic screening studies at the tissue- and organ specific level. The software is easy-to-use and readily accessible to biomedical researchers with little to no prior knowledge of computer vision or image-processing. The tools are integrated in common scientific image-analysis packages and accompanied by extensive documentation in the form of articles in academic journals, readme files accompanying the source codes and online video tutorials. To foster their distribution and the inspiration of derived work, most of the underlying source code is available online in open-source repositories.