Development Of Image Analysis Methods Applied To Collagen Imaged With Different Techniques



Leibl, MA
(2018) Development Of Image Analysis Methods Applied To Collagen Imaged With Different Techniques. PhD thesis, University of Liverpool.

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Abstract

This thesis is concerned with the development of analysis strategies for microscopic images of collagen, with the specific aim to minimise as far as possible the need for user input, thereby reducing potential bias. Images of collagen were chosen for analysis, as collagen is an easily available and biologically important molecule, whose organisation in tissues is of great interest due to its pivotal role in biomechanics, and its implication in many disease states. Quantifying its structure and organisation can facilitate better understanding of the physiological and mechanical role of collagen, as well as provide the basis for a more detailed knowledge of the structural foundation of the body. We had access to a limited number of collagen images from porcine sclera obtained by Atomic Force Microscopy, Polarised Light Microscopy, Second Harmonic Generation Microscopy and Transmission Electron Microscopy. The challenges in developing analysis strategies arose from collagen itself, from the intrinsic differences in the data gathered by different microscopies, and from the presence of artifacts. We developed successful methods to analyse data relevant to collagen characterisation from Atomic Force Microscopy, Polarised Light Microscopy and Second Harmonic Generation Microscopy images, and propose a quantification method where our analysis attempts were not successful. This thesis aims to contribute to a growing body of work in image analysis, which can be applied across disciplines wherever image data are used. It is hoped that further development and refinement of the work presented here may be the focus of future work.

Item Type: Thesis (PhD)
Divisions: Faculty of Science and Engineering > School of Physical Sciences
Depositing User: Symplectic Admin
Date Deposited: 20 Nov 2018 16:42
Last Modified: 19 Jan 2023 01:31
DOI: 10.17638/03023028
Supervisors:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3023028