Abstract
The role of Optical Coherence Tomography (OCT) technology for the assessment and management of ocular diseases has become very significant in understanding the vitreoretinal relationships and the internal architecture of the retinal structure. The current commercial OCT system (StratusOCTtm) has a nominal axial resolution of 10μm and provides quantitative measurements of the macular retinal thickness, peripapillary nerve fiber layer thickness and topographical measures of the optic nerve head. However, at its current state of development, the StratusOCTtm system needs to incorporate better quantitative methods to potentially yield a more accurate description of the local changes in the retina. Hence, there is a need for improvement in precise quantification and data analysis of the StratusOCTtm images. Segmentation is one of the most important steps in the quantitative analysis of the optical properties of the various cellular layers of the retina. It has been recently shown that retinal layers can be automatically segmented in StratusOCTtm images. However, fully automatic methods are often limited in their capabilities hence requiring the intervention of a human operator to correct image segmentation errors that may result due to algorithm failures, image acquisition errors, abnormal regions of high intra-retinal reflectivity, disruptions in the retinal morphology due to retinal diseases, among others The main objective of this thesis is to design a new stand-alone application software consisting of a Graphical User Interface (GUI) that will integrate a novel automatic segmentation of the retinal images obtained from the StratusOCTtm system along with a new developed manual correction tool that will aid in eliminating segmentation errors. Additionally, the GUI will integrate a set of programmed functions to facilitate the pre- and post-processing of the StratusOCTtm images. It will also generate a quantitative analysis report that can be exported as a spreadsheet to Microsoft Excel along with a PDF document. As a result, the GUI will facilitate the measurements of thickness and reflectance of the various retinal layers, leading to a potential improvement in the quantitative analysis of StratusOCTtm images.