Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.765122
Title: Computer vision for sequential non-invasive microscopy imaging cytometry with applications in embryology
Author: Molder, Anna
ISNI:       0000 0004 7659 0166
Awarding Body: Manchester Metropolitan University
Current Institution: Manchester Metropolitan University
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
Many in vitro cytometric methods requires the sample to be destroyed in the process. Using image analysis of non-invasive microscopy techniques it is possible to monitor samples undisturbed in their natural environment, providing new insights into cell development, morphology and health. As the effect on the sample is minimized, imaging can be sustained for long un-interrupted periods of time, making it possible to study temporal events as well as individual cells over time. These methods are applicable in a number of fields, and are of particular importance in embryological studies, where no sample interference is acceptable. Using long term image capture and digital image cytometry of growing embryos it is possible to perform morphokinetic screening, automated analysis and annotation using proper software tools. By literature reference, one such framework is suggested and the required methods are developed and evaluated. Results are shown in tracking embryos, embryo cell segmentation, analysis of internal cell structures and profiling of cell growth and activity. Two related extensions of the framework into three dimensional embryo analysis and adherent cell monitoring are described.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.765122  DOI: Not available
Share: