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Title: Techniques in deep imaging within biological tissue
Author: Poland, Simon
ISNI:       0000 0001 3493 466X
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2006
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This thesis is concerned with the development of low-cost and practical biological optical imaging and diagnosis systems that will allow the user to image and resolve structure deep into biological tissue without the need for physical dissection. Research within this thesis can be divided into two main sections, namely (a) the development of optically sectioning microscopy systems incorporating adaptive optics to compensate for system and specimen induced aberrations, and (b) as an example of biological tissue and disease, the development of dental imaging devices to detect and diagnose dental disease (caries). Section (a) The ability of confocal and multiphoton microscopy techniques to image optical sections deep within biological samples is a major advantage in biology. Unfortunately, as one images deeper within a sample, image degradation increases due to aberrations and scattering. In this investigation, operating a confocal microscope in reflection, a deformable membrane mirror (DMM) was used to counteract for sample aberrations within a closed feedback loop. By selecting various image properties (e. g. brightness, contrast or resolution), various optimisation algorithms were used to improve this property by altering the shape of the DMM and compensate for aberrations. Taking axial and lateral point spread functions (PSFs), the improvement of the system was monitored. The ability of the adaptive optic system to optimise to a particular axial PSF (PSF engineering) was also examined. The use of various algorithms with an adaptive element in a confocal system has been demonstrated to show significant improvement in the axial resolution and signal intensity. While global optimisation algorithms such as the genetic algorithm are more likely to find the global maximum in solution space in comparison to hillclimbing, it usually takes longer to achieve an optimum solution. Particular fitness parameters have shown promise in increasing the effectiveness of the algorithmic search routines. Optimising certain axial PSF components appears to have a detrimental effect on the lateral PSF and resolution. In the situation where the best axial and lateral resolution is required, optimising for intensity appears to show the best all round result. By adapting the axial fitness parameter program, it has been shown that particular desired axial PSF shapes can be reproduced within an aberrated sample. This does appear to have some limitations due to the relative power of the mirror (stroke). Section (b) Using optical techniques, physiological changes associated with the onset of disease in biological tissue can be detected. Taking dental tissue as an example of a highly scattering biological media, a computer model based upon commercially available software was used to theoretically reproduce experimental results taken using a fibre optical confocal system on dental tissue. From simulations, it has been shown that such a system could microscopically measure the optical properties of a caries lesion within dental enamel non-invasively. A system based on the use of structured light to penetrate and quantify early stage dental caries was presented as a possible aid to dentistry. Although the system was able to optically section the carious surface as well as detect inhomogeneities greater than 60μm deep into the tooth sample, more studies must be carried out to assess the limitations of the system. On a macroscopic scale, a cost effective system known as near-infrared Lateral Illumination (L. I.) (which is based on transillumination techniques) was presented. In a preliminary study involving 15 ex-in vivo adult pre-molars and molars at various stages of dental decay, L. I. was shown to be the most effective occlusal caries diagnosis system when compared to some techniques currently available and in development.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral