ArticleIEEE transactions on medical imaging2020
3D Shape Modeling and Analysis of Retinal Microvasculature in OCT-Angiography Images.
Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Strip-Scanning for Efficient Widefield Retinal OCTA Mosaicking.Translational vision science & technology · 2026Article
- Image-processing pipeline for diagnosing diabetic macular ischaemia in diabetic macular oedema.Scientific reports · 2025Article
- Dual acquisition scheme-based optical coherence tomography 3D angiography.Journal of biomedical optics · 2025Article
- Volumetric Measures of Capillary Nonperfusion on Optical Coherence Tomography Angiography Detect Early Ischemia in Diabetes Without Retinopathy.Investigative ophthalmology & visual science · 2025Article
- Dual-stream disentangled model for microvascular extraction in five datasets from multiple OCTA instruments.Frontiers in medicine · 2025Article
- Diameter-dependent classification of dermal vasculature using optical coherence tomography angiography.Quantitative imaging in medicine and surgery · 2024Article
- OCT angiography and its retinal biomarkers [Invited].Biomedical optics express · 2023Review
- Deep ensemble learning for automated non-advanced AMD classification using optimized retinal layer segmentation and SD-OCT scans.Computers in biology and medicine · 2023Article
- Innovative Macula Capillaries Plexuses Visualization with OCTA B-Scan Graph Representation: Transforming OCTA B-Scan into OCTA Graph Representation.Journal of multidisciplinary healthcare · 2023Article
- A two-stage framework for optical coherence tomography angiography image quality improvement.Frontiers in medicine · 2023Article
- Fully-Automatic 3D Intuitive Visualization of Age-Related Macular Degeneration Fluid Accumulations in OCT Cubes.Journal of digital imaging · 2022Article
- Dual-consistency semi-supervision combined with self-supervision for vessel segmentation in retinal OCTA images.Biomedical optics express · 2022Article
- State-of-the-art retinal vessel segmentation with minimalistic models.Scientific reports · 2022Article
- Volume rendered 3D OCTA assessment of macular ischemia in patients with type 1 diabetes and without diabetic retinopathy.Scientific reports · 2021Article
- Past, present and future role of retinal imaging in neurodegenerative disease.Progress in retinal and eye research · 2021Review
- Automated Segmentation of Trigeminal Nerve and Cerebrovasculature in MR-Angiography Images by Deep Learning.Frontiers in neuroscience · 2021Article
- Deep learning toolbox for automated enhancement, segmentation, and graphing of cortical optical coherence tomography microangiograms.Biomedical optics express · 2020Article
- 3D Retinal Vessel Density Mapping With OCT-Angiography.IEEE journal of biomedical and health informatics · 2020Article
- Optical Coherence Tomography Angiography in Neurodegenerative Disorders.Journal of clinical medicine · 2020Review
- LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionArticle
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7 authors.
Funding
Abstract
3D optical coherence tomography angiography (OCT-A) is a novel and non-invasive imaging modality for analyzing retinal diseases. The studies of microvasculature in 2D en face projection images have been widely implemented, but comprehensive 3D analysis of OCT-A images with rich depth-resolved microvascular information is rarely considered. In this paper, we propose a robust, effective, and automatic 3D shape modeling framework to provide a high-quality 3D vessel representation and to preserve valuable 3D geometric and topological information for vessel analysis. Effective vessel enhancement and extraction steps by means of curvelet denoising and optimally oriented flux (OOF) filtering are first designed to produce 3D microvascular networks. Afterwards, a novel 3D data representation of OCT-A microvasculature is reconstructed via advanced mesh reconstruction techniques. Based on the 3D surfaces, shape analysis is established to extract novel shape-based microvascular area distortion via the Laplace-Beltrami eigen-projection. The extracted feature is integrated into a graph-cut segmentation system to categorize large vessels and small capillaries for more precise shape analysis. The proposed framework is validated on a dedicated repeated scan dataset including 260 volume images and shows high repeatability. Statistical analysis using the surface area biomarker is performed on small capillaries to avoid the effect of tailing artifact from large vessels. It shows significant differences ( ) between DR stages on 100 subjects in a OCTA-DR dataset. The proposed shape modeling and analysis framework opens the possibility for further investigating OCT-A microvasculature in a new perspective.
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