Dissertation

Development of automatic image analysis methods for high-throughput and high-content screening

Promotor: B. van de Water, Co-Promotores: J.H.N. Meerman, F.J. Verbeek

Author: Z. Di
Date: 10 December 2013
Links: Thesis in Leiden Repository

This thesis focuses on the development of image analysis methods for ultra-high content analysis of high-throughput screens where cellular phenotype responses to various genetic or chemical perturbations that are under investigation. Our primary goal is to deliver efficient and robust image analysis platforms which can 1) automatically detect cellular structures of interest from florescence microscope images and 2) quantify dynamics and organization of multi-cellular systems with phenotypic features. To recover heterogeneity of cellular behavior, we aim to develop single-cell-based image analysis methods so that cell subpopulations can be distinguished and investigated. Furthermore, we intend to develop methods to extract an ultra-high level of phenotypic details from images. This would enable system-level studies of phenotype characterization.