Optical Coherence Tomography (OCT) is a non-invasive volumetric imaging technique that offers micron scale resolution over several millimetres of depth penetration in tissue. The aim of the project was to develop Full Field Swept Source OCT (FFSSOCT), charting the specifications of the system throughout and drawing comparisons with available Fourier domain OCT (FDOCT) systems. A super luminescent diode (SLD) light source was tuned to different optical frequencies using an acousto-optical tunable filter. The successive optical frequencies were distributed across the sample in parallel and the sequential interference spectra were recorded with a high speed digital camera. Using a 5mW optical source at 850nm, 70dB sensitivity was ultimately achieved in a single five second acquisition, improving the original performance by 5dB and increasing acquisition and processing time significantly. Ex vivo retinal images of rat and tree shrew were recorded with multiple layers visible. All software was custom written in Labview, improving the user interface and processing time over the existing Matlab code. To enhance the performance of the system, the camera was subsequently upgraded from 15 to 45% quantum efficiency and from 250k to 1.3M pixels. The light source was also upgraded to 20mW. The software was improved with spectral processing and dispersion compensation. 85dB sensitivity was ultimately achieved. Further ex vivo retinal images were taken, showing comparative image quality to those of the same retinal samples recorded with FDOCT. Further attempts to increase the system performance were limited by internal reflections and interfering surfaces within the FFSSOCT design leading to saturation of the digital camera. In vivo imaging was attempted using software based phase jitter compensation. Improvement could be seen with simple reflecting structures.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:577917 |
| Date | January 2013 |
| Creators | Fergusson, James |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/49959/ |
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