Analytical tools for high resolution OCT imaging of human retina

With the advent of optical coherence tomography (OCT), remarkably detailed information about retina is now available. However, most of the clinical use of OCT relies on qualitative analysis of the data. While technological advances have provided increased resolution and quicker data acquisition, the clinical utility of OCT has not been fully realized as quantitative methods for image analysis have not kept pace with the technological advances. Hence, there is a pressing need to develop analytical tools that allow OCT to achieve its full potential as an early diagnostic tool of early degenerations. This study examined the practical improvement in image quality afforded by a broadband light source in a clinical setting and defined image quality metrics for future use in evaluating spectral domain optical coherence tomography (SD-OCT) images. Significant improvement in local contrast, resolution and contrast to noise ratio was found using a commercial broad-band light source. Horizontal striations within the IPL were also observed and believed to represent synaptic sub lamination, though further investigation is required. A novel automated segmentation algorithm to extract four retinal boundaries was developed and verified against the current gold standard - manual segmentation. This algorithm provided accurate, reliable and reproducible thickness measurements for linear and volumetric scans. The algorithm was developed for segmenting healthy retinal images, and hence can be used for normative database for thickness profiles of retinal layers