| publication name | Graph-based segmentation of corneal epithelium and endothelium in Optical Coherence Tomography images |
|---|---|
| Authors | Amr Elsawy, Vatookarn Roongpoovapatr, Taher Kamel Eleiwa, Giovanni Gregori, Mohamed Abdel-Mottaleb, Mohamed Abou Shousha |
| year | 2019 |
| keywords | |
| journal | Investigative Ophthalmology & Visual Science |
| volume | 60 |
| issue | 9 |
| pages | 2138 |
| publisher | The Association for Research in Vision and Ophthalmology |
| Local/International | International |
| Paper Link | https://iovs.arvojournals.org/article.aspx?articleid=2746892&resultClick=1 |
| Full paper | download |
| Supplementary materials | Not Available |
Abstract
Epithelial and the Endothelial surfaces of abnormal cornea images obtained using high definition optical coherence tomography (HD-OCT). Methods: Thirty-six patients were imaged using HD-OCT (Envisu R2210, Bioptigen, Buffalo Grove, IL, USA). These included patients with different pathologies: Dry eye (6 eyes), Keratoconus (6 eyes), Fuchs Dystrophy (6 eyes), Corneal Graft Rejection (6 eyes), Stem Cells Deficiency (6 eyes) and normal controls (6 eyes). All the images were manually segmented by two expert graders. The graph-based automated segmentation algorithm is based on a two stages approach. A directed graph was constructed using image pixels as the graph vertices. The Epithelial and the Endothelial boundaries were initially segmented using an edge energy between graph vertices based on the normalized gradient .