ArticleJournal of medical systems2019
Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening.
Article in Journal of medical systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- SMMF: a self-attention-based multi-parametric MRI feature fusion framework for the diagnosis of bladder cancer grading.Frontiers in oncology · 2024Article
- Sodium Hyaluronate-Induced Ocular Hypertension in Rats Damages the Direction-Selective Circuit and Inner/Outer Retinal Plexiform Layers.Investigative ophthalmology & visual science · 2022Article
- A Multimodal Classification Architecture for the Severity Diagnosis of Glaucoma Based on Deep Learning.Frontiers in neuroscience · 2022Article
- Correlation Between Changes in Lamina Cribrosa Structure and Visual Field in Primary Open-Angle Glaucoma.Clinical ophthalmology (Auckland, N.Z.) · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.