Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361513
Title: Automated visual measurement of body shape in scoliosis
Author: Pearson, Jeremy D.
Awarding Body: Liverpool John Moores University
Current Institution: Liverpool John Moores University
Date of Award: 1996
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Abstract:
This thesis describes the content and progression of research into automated non-contact methods for measuring the three-dimensional shape of the human back in scoliosis. Scoliosis is a condition in which the spine becomes distorted and a rib-hump appears on the surface of the back. The research was driven by the needs of the scoliosis clinician and was supported by the Royal Liverpool Children's Hospital, Merseyside. A number of optical methods for measuring back surface shape are considered. Moire contouring and Fourier transform profilometry are investigated through practical research in the laboratory. Stereophotogrammetry, phase stepping profilometry, optical scanning and raster pattern contouring are investigated through consideration of theory and literature review. However, none of these approaches is found to be free from limitations. The main novel content of the work presented in this thesis lies in the research into a new method for reconstructing back shape. A new optical method is proposed in which a modified multi-stripe structured light pattern is projected onto the surface of the back. Image processing operations, specialised for this application, process the image of the pattern to reconstruct three-dimensional shape. Further research demonstrates that the computer reconstruction can be interrogated to measure parameters of clinical significance such as Angle of Trunk Inclination and Standardised Trunk Asymmetry Score. A working clinical system was implemented and tested on scoliosis patients at the hospital. The method is evaluated in terms of technical qualities and as a usable clinical tool and was found to satisfy the criteria for a successful automated system.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.361513  DOI: Not available
Keywords: R Medicine (General) ; TK Electrical engineering. Electronics. Nuclear engineering Pattern recognition systems Pattern perception Image processing Biomedical engineering Biochemical engineering
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