"FiBar": a Tool for Automated Analysis of Complex Biomaterials from Microscopy Images
Name
Marilin Moor
Abstract
The success or failure of many microbiological experiments depends on the image analysis of microscopy images, be it determining the livelihood of bacteria by measuring the fluorescence of individual cells or evaluating the quality of a fibrous mat by assessing the distribution of individual fiber diameters. Often a lot of image data is being generated from experiments, leading to a heightened demand of automated image analysis tools. This also holds true in the creation of complex biomaterials, which contain both fibrous textures and some other biocompound, like bacteria. Additionally, manual image analysis is deemed to be time inefficient and biased — both issues which this work aims to alleviate. This work presents the first version of "FiBar": a tool for the automated analysis of complex biomaterials. The tool consists of a fiber diameter measuring and bacteria analysis pipeline. "FiBar" was validated against other tools as well as manual measurements taken from microscopy images. The tool showed to be useful for speeding up the analysis while being relatively accurate.
Graduation Thesis language
English
Graduation Thesis type
Master - Data Science
Supervisor(s)
Dmytro Fishman, Marta Putrinš, Karin Kogermann
Defence year
2023