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Title: Mouse embryo phenotyping using high-resolution 3D imaging
Author: Norris, F. C.
ISNI:       0000 0004 5362 9857
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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The immense challenge of annotating the entire mouse genome has stimulated development of cutting-edge imaging technologies in a drive for novel information. These techniques promise to improve our understanding of the genes involved in embryo development, at least one third of which have been shown to be essential. Aligning advanced imaging technologies with biological needs will be fundamental to maximising the number of phenotypes discovered in the coming years. International efforts are underway to meet this challenge through an integrated and sophisticated approach to embryo phenotyping, which will include advanced imaging tools. This thesis investigates advanced imaging methodologies and computational image analysis techniques for mouse embryo phenotyping using magnetic resonance imaging (MRI). Additionally, the novel application of an emerging method called photoacoustic imaging is demonstrated for imaging mouse embryos in utero. First, the lack of tissue staining capabilities that currently limits embryo MR imaging was addressed by investigating the MRI staining properties of two readily available contrast agents and their underlying contrast enhancement mechanisms. A methodological framework was developed for high-throughput screening of embryos using diffusion MRI and implemented to study the splotch mouse model of human neural tube defects. A validation study was carried out to comprehensively assess the accuracy of volumetric measurements generated using a computational image analysis method called segmentation propagation. Finally, an all-optical photoacoustic scanner and novel time-reversal image reconstruction algorithm were developed, enabling photoacoustic imaging of whole embryos in utero. Overall, this thesis presents advanced imaging methodologies and computational image analysis techniques that may form an essential part of the toolkit available for annotating the mouse genome and facilitate identification of novel phenotypes in the coming years.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available