Analysis of three dimensional retinal datasets obtained by Optical Coherence Tomography
Department: Optometry & Vision Science, University of Auckland
Main Supervisor: Dr Ehsan Vaghefi
This funded MS project is for a student interested and experienced in image processing using MATLAB.
The World Health Organization concludes that Glaucoma is the second leading cause of blindness after cataract worldwide. Globally, 60.5 million people are living with glaucoma and according to Glaucoma NZ (www.glaucoma.org.nz), this disease is the number one preventable cause of blindness in our country. Glaucoma describes a range of related diseases through which the optic nerve is being damaged. The eye’s optic nerve is responsible for relaying phototransduction-generated electrical signals from the retina to the brain.
Optical Coherence tomography (OCT) is a non-invasive technique in cross-section imaging of the eye. It has become an invaluable diagnostic aid in evaluating glaucoma. It provides three-dimensional anatomical view of the retinal layers in the macular and around the optic nerve head. The 3D anatomy of the retina however changes naturally with aging, and abnormally in due to glaucoma. Previously we recruited two cohorts of young (18 to 30 y/o) and old (50 to 65 y/o) participants with healthy vision. These groups were then imaged with high resolution NIDEK RS 3000 OCT, using ultrafine macular and optic disc map mode. These databases will be used in this project to evaluate the accuracy and validity of the developed software package. Currently, the OCT scans are being analysed by the proprietary software applications, developed by the manufacturers. In this project, we are aiming to develop an in-house and open-source image analysis package to estimate clinically relevant anatomical changes in obtained retinal datasets.