Image-based Microscale Particle Velocimetry in Live Cell Microscopy

Abstract: Background: Nowadays, one of the medical problem is rolling cell adhesion. Rolling cell adhesion is a complex process that requires the analysis of the challenging environment such as body fluid and is the process responsible for recruiting the cell to specific organs. In order to explore the rolling cell adhesion, mathematical model is proposed. Different image processing methods are created, such as optical flow - Lucas Kanade algorithm, and other type of methods related to mechanical fluid, namely PIV (Particle Image Velocimetry). Aim: The aim of this master thesis is the identification of challenges while using PIV in live cell images and propose the algorithm, which may analyze the rolling cell adhesion problem. Methods: In order to understand properly the rolling cell adhesion problem from biological site, literature review combined with the expert consultation is performed. According to gather information, mathematical model is proposed. Particle Image Velocimetry is explained according to literature review, where at the beginning the expert recommends some books as a primary research. As a result of this research, PIV challenges are identified and generally PIV idea is explained. Then two experiments are performed. The first experiment evaluates detection algorithms and the second one, analyses track algorithm vs. PIV. In order to evaluate the mentioned algorithms, some evaluation method are selected and some criteria are defined. Unfortunately the found methods are not perfect, therefore a new method related to performance evaluation using time series is proposed. Thesis result: The result of this thesis is a proposition of the algorithm, which can be used in the rolling cell adhesion. The algorithm is formed according to the detailed exploration of the rolling cell adhesion and analysis of the selected algorithms related to the image analysis during the theoretical research and experiments.