Image Processing Techniques for PV-OCT Imaging of Human Eye
Authors:Jeff Fingler, Dae Yu Kim, Malvika Verma
Mentor:Scott Fraser, Professor of Biology and Professor of Bioengineering, California Institute of Technology
Phase-variance optical coherence tomography (pv-OCT) visualizes retinal vasculature non-invasively and thus has potential in the early diagnosis of retinal vascular diseases that include diabetic retinopathy and macular degeneration. Currently, circulation of the retina in clinical settings makes use of fundus fluorescein angiography (FA), which involves injection of a fluorescein dye to view the perfusion into the blood stream. The injection makes this an invasive procedure with complications like nausea and vomiting to anaphylaxis and limited axial resolution and information regarding structural and functional consequences of vascular disease. These factors necessitate the development of a non-invasive optical tool for early diagnosis of retinal vascular diseases. The project concentrates on the clinical development of pv-OCT, which has the advantage of being a non-invasive, three-dimensional microvascular imaging method. Developing image processing algorithms for feature extraction and noise and shadow removal is essential to overcome the restrictions of human motion during imaging and hardware restriction of the pv-OCT. This project will focus on improving image quality for scientists and ophthalmologists by removing eye motion effects and artifacts and shadows, producing en face visualizations of the three-dimensional vascular data with segmented features.