Paper Info
Title
Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening.
Abstract
Glaucoma is an eye disease that damages the optic nerve and can lead to irreversible loss of peripheral vision gradually and even blindness without treatment. Thus, diagnosing glaucoma in the early stage is essential for treatment. In this paper, an automatic method for early glaucoma screening is proposed. The proposed method combines structural parameters and textural features extracted from enhanced depth imaging optical coherence tomography (EDI-OCT) images and fundus images. The method first segments anterior the lamina cribrosa surface (ALCS) based on region-aware strategy and residual U-Net and then extracts structural features of the lamina cribrosa, such as lamina cribrosa depth and deformation of lamina cribrosa. In fundus images, scanning lines based on disc center and brightness reduction are used for optic disc segmentation and brightness compensation is utilized for segmenting the optic cup. Afterward, the cup-to-disc ratio (CDR) and textural features are extracted from fundus images. Hybrid features are used for training and classification to screen glaucoma by gcForest in the early stage. The proposed method has given exceptional results with 96.88% accuracy and 91.67% sensitivity.
Year
DOI
Venue
2019
10.1007/s10916-019-1303-8
Journal of Medical Systems
Keywords
Field
DocType
Glaucoma screening, EDI-OCT, Fundus images, Hybrid feature extraction
Data mining,Glaucoma,Optical coherence tomography,Segmentation,Ophthalmology,Fundus (eye),Optic disc,Optic cup (anatomical),Lamina,Medicine,Optic nerve
Journal
Volume
Issue
ISSN
43
6
0148-5598
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Zailiang Chen1439.10
Xianxian Zheng210.68
Hailan Shen3304.07
Ziyang Zeng411.37
Qing Liu5292.20
Zhuo Li62811.11