Automated image analysis of corneal structures in anterior-segment optical coherence tomography and in-vivo confocal microscopy images

Abstract

Anterior-Segment-Optical Coherence Tomography (AS-OCT) is a noninvasive imaging modality that has significantly contributed to the quantitative assessment of ocular diseases. Another tool available to ophthalmic clinicians is in-vivo confocal microscopy (IVCM), which allows anatomical structures to be observed live at the cellular level. Incorporating both of these modalities for imaging the cornea allows us to take structural measurements and characterize disease-related changes in corneal anatomy. Notable diseases that directly impact or correlate with corneal structures include glaucoma and diabetic neuropathy. Given glaucoma's impact as the second leading cause of blindness in the world, great efforts have been made in researching and understanding the disease. Diabetes is a prominent disease that affects millions of Americans every day. While not necessarily a corneal disease in its own right, diabetes has been shown to affect the corneal structures. Diabetics have decreased corneal sensitivity and a significant link has been established between neuropathic severity in diabetic patients and corneal nerve fiber density. Given the availability of these imaging tools and the significant impact these prominent diseases have on society a growing focus has developed on relating corneal structure measurements and ophthalmic diseases. However, manually acquiring structural measures of the cornea can be a labor-intensive and daunting task. Hence, experts have sought to develop automatic alternatives. The goals of this work include 1) utilizing the 3D information of AS-OCT imagery to segment all the corneal layers simultaneously, 2) increasing the region-of-interest of IVCM imagery using a feature-based registration approach to develop a panorama from the images, 3) incorporating machine-learning techniques to segment the corneal nerves in the IVCM imagery, and 4) extracting structural measurements from the segmentation results to determine correlation between the corneal structural measurements in various subject groups. vi