Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening
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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.
KeywordsGlaucoma screening EDI-OCT Fundus images Hybrid feature extraction
This research is supported by the National Natural Science Foundation of China under Grant No. 61672542.
Compliance with ethical standards
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional review board and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Conflict of interest
The authors declare that they have no conflict of interest.
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