ArticleComputational and mathematical methods in medicine2021
Choroid Segmentation of Retinal OCT Images Based on CNN Classifier and
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Deep learning-based automated classification of choroidal layers in en face swept-source optical coherence tomography images.BMC ophthalmology · 2025Article
- A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT.Frontiers in cell and developmental biology · 2025Article
- Choroidal Optical Coherence Tomography Angiography: Noninvasive Choroidal Vessel Analysis via Deep Learning.Health data science · 2024Article
- A Deep Learning-Based Fully Automated Program for Choroidal Structure Analysis Within the Region of Interest in Myopic Children.Translational vision science & technology · 2023Article
- Correlation of choroidal thickness with age in healthy subjects: automatic detection and segmentation using a deep learning model.International ophthalmology · 2022Article
- Application of Artificial Intelligence and Deep Learning for Choroid Segmentation in Myopia.Translational vision science & technology · 2022Article
- Choroidal layer segmentation in OCT images by a boundary enhancement network.Frontiers in cell and developmental biology · 2022Article
- Applications of Artificial Intelligence in Choroid Visualization for Myopia: A Comprehensive Scoping Review.Middle East African journal of ophthalmologyArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Optical coherence tomography (OCT) is a noninvasive cross-sectional imaging technology used to examine the retinal structure and pathology of the eye. Evaluating the thickness of the choroid using OCT images is of great interests for clinicians and researchers to monitor the choroidal thickness in many ocular diseases for diagnosis and management. However, manual segmentation and thickness profiling of choroid are time-consuming which lead to low efficiency in analyzing a large quantity of OCT images for swift treatment of patients. In this paper, an automatic segmentation approach based on convolutional neural network (CNN) classifier and
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Registered trials
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